Research Collection

Doctoral Thesis

Using virtual reality as a home-based stroke rehabilitationapproach

Author(s): Wüest, Seline

Publication Date: 2015

Permanent Link: https://doi.org/10.3929/ethz-a-010546679

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ETH Library

USING VIRTUAL REALITY AS A HOME-BASED STROKE REHABILITATION APPROACH—

Seline Wüest

DISS.ETHNO.22848

USINGVIRTUALREALITYASAHOME-BASED

STROKEREHABILITATIONAPPROACH

Athesissubmittedtoattainthedegreeof

DOCTOROFSCIENCESofETHZURICH

(Dr.sc.ETHZurich)

presentedby

SELINEWÜEST

MScETHinHMS

bornon01-02-1985

citizenofGrosswangen(Lucerne)

acceptedontherecommendationof

PDDr.ElingD.deBruinProf.Dr.DavidP.Wolfer

2015

TableofContents

1Prologue 1–112Computationalintelligenceandgamedesignforeffectiveat-homestroke 12–27rehabilitationGamesforHealthJournal2013;2(2):81-883Designconsiderationsforatheory-drivenexergame-basedrehabilitation 28–47programtoimprovewalkingofpersonswithstrokeEuropeanReviewofAgingandPhysicalActivity2014;11(2):119-1294Usabilityandeffectsofanexergame-basedbalancetrainingprogram 48–66GamesforHealthJournal2014;3(2):106-1145Reliabilityandvalidityoftheinertialsensor-basedTimedUpandGotestin 67–95post-strokeindividualsJournalofRehabilitationResearch&Development2015,inpress6Epilogue 96–107Summary/Zusammenfassung 108–114DanksagungenCurriculumvitae

1

1

Prologue

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Stroke is a centralnervous systempathology that theWorldHealthOrganization (WHO)definesas “a

clinical syndrome, of presumed vascular origin, typified by rapidly developing signs of focal or global

disturbanceofcerebralfunctions”[1].Thesymptomsofstrokepersistformorethan24hoursandmight

leadtodeath[1].Astrokeoccurswhenbloodsupplytothebrainisinterrupted,damagingaffectedbrain

areas. The resulting loss of brain function commonly implies serious cognitive, visual and motor

complaintsinthosesurvivingastroke[2].Withover15millionoccurrenceseachyear,strokeconstitutes

one of themost important causes of death and disability [3] and can be said to be one of themost

devastating diseases worldwide [4]. The concern over stroke becomes even more pressing if one

considers thedemographic changes thatarecurrently leading toaneverhigherquotaofpeopleaged

65+: Stroke is bothmost prevalent andmost devastating in this age group. According to theWHO’s

Europeanpopulationprojections,thenumberofnewstrokeeventseveryyearisestimatedtoincrease

from1.1millionin2000tomorethan1.5millionin2050solelyduetodemographicshiftstowardsolder

populations[5].

Given this shift, stroke rehabilitation should be a primary focus of attention in stroke research. The

present doctoral thesis represents an effort to improve long-term stroke rehabilitation. Its main

hypothesis is that home-based stroke rehabilitation programs specifically targeting balance have the

potentialtosupportrecoveryoflocomotorfunction–oneofthemostimportantdeterminantsofquality

oflifeafterstroke.

1.1Stroke-inducedmotordeficits

Large research efforts are directed at the prevention of stroke. Here the primary focus is on lifestyle

factorsrelatedtostrokerisk.However,becausetheaforementioneddemographicdevelopment istoa

largeextentgiven,strokerehabilitationisanimportantlineofattackaswell.Althoughstrokecausesa

widerangeofproblems(e.g.,pain,memoryproblems,speechimpairments, lossofvision,alteredlevel

of consciousness), patients often express impaired locomotor function as a main cause of decreased

qualityoflife.Thelossoflocomotorfunctionisoftencausedbystroke-inducedhemiparesis–aone-side

partiallossofmotorfunction[6-7].Ithasbeennoticedthatalargeproportionofhemiparalizedpatients

showdiminishedbalanceskillsandadeviatedwalkingpattern [8-10] involvingreducedwalkingspeed,

cadence, stride length and an increased left-right asymmetry: so-called ‘hemiparetic gait’. Not

surprisingly,thereisagreatneedinstrokerehabilitationtoachieveahighlevelofwalkingskillsaimedat

regaining independence in walking. In this context balance, endurance, muscle strength and motor

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coordinationarekeycontributingfactorsaffectingstrokepatients’walkingfunction[11-13].Sincegood

balance iswidelyconsideredasan indispensableprerequisite fornormalwalking[14-15], the focuson

balance in rehabilitative interventions seems mandatory. Accordingly, a therapy program targeting

balanceshouldconstituteapromisingapproachtoimprovewalking–andhencequalityoflife–instroke

survivors.

Alargeliteraturebodyexistssuggestingthattheinitialrecoveryperiodafterstrokeisthemostsensitive

phaseintermsofmotordeficitrestoration[16-17].Specifically,thefirstthreemonthsofrehabilitation

seem critical formotor recovery after stroke [18].Nevertheless, there is an increased awareness that

meaningful improvementscanstillbeachievedinthelaterphasesofrehabilitation[18].Consequently,

strokerehabilitationshouldnotberestrictedtoonlytheinitialperiodfollowingstroke;itwillhavetobe

continued on a long-term basis. Since the treatment of stroke sufferers in hospitals or specialized

rehabilitation units is expensive and hence places a large burden on theNationalHealth Service, it is

oftennotfeasibletoextendthelengthofstayinrehabilitationfacilities.Consequently,forbestrecovery

results,long-termandcost-effective(i.e.,largelyautonomous)rehabilitationisneededafterpatientsare

dischargedfromrehabilitationfacilities.

In what follows, the development of a treatment approach that enables long-term rehabilitation for

strokepatientsdischargedfromhospitalsorrehabilitationunitswillbepresented.Thisdoctoralthesisis

basedonresearcheffortswithintheproject‘RehabilitativeWayoutInResponsivehomeEnvironments’

(REWIRE) [19] funded by the European Commission under the FP7 framework. As such, the idea that

strokesufferersmightbenefitfromanintensivehome-therapyprogramusingvirtualreality(VR)formed

thegeneralframeworkforthisdoctoralthesis.

1.2Virtualrealityforrehabilitation

BecauserecentliteratureexposedavarietyofbenefitsassociatedwiththeuseofVRinhealthcare,this

technologyhasbecomeagrowingareawithin rehabilitation interventions [20-21].Apotent featureof

VRisitsgreatpotentialtocreateawidevarietyofrealisticscenariosadaptedtopatients’characteristics

and needs. By simulating interactive environments, rehabilitation practice under controlled and safe

conditionsisprovided.Afterall,avirtualenvironmentcanbecontrolledmoreeasilythanarealone,and

anyaccidentswillmerelybevirtualaswell.Furthermore,VRseemstofarewell intermsofmotivating

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patientsforrehabilitationandbetterengagingtheminthetreatmentplan[20,22-25].Thiswill leadto

improvedcontinuity,whichinturnpositivelyimpactsrecovery[26].

Thegamingindustryhasrecentlyprovidedasetofmodernlow-cost,VR-basedgamingconsoles(i.e.,the

NintendoWii,theSonyPlayStation,andMicrosoftX-box)thatallowmotion-controlledinteractionswith

thesystem.Byreliablytrackingandrespondingtousers’naturalbodymovements,thesecommercially

available gaming consoles have revolutionized the way videogames are played. Videogames have

become more intuitive and, thereby, more accessible to a wider audience [27]. As such, they have

become a source of inspiration for health care researchers and sparked the introduction of a novel

gaming approachwithin rehabilitation interventions. In one study, the commercial VR gaming system

NintendoWiiFitwasusedasabalancetrainingtoolforolderadults[28].Thestudyincluded12healthy

participantsaged53to91yearswithahistoryoffallsandreportedimprovementsinbalancefollowing

use of the Wii Fit system. The actual clinical effect induced by Wii Fit training in the presence of

pathologies, however, remains speculative. A study by Deutsch et al. [29] suggested that VR-based

approacheshavegreatpotentialtopositivelyaffectrehabilitation.A13-years-oldpatientdiagnosedwith

cerebral palsywas included in this study. The training intervention consisted of playing commercially

available games provided by the Nintendo Wii Fit sports software and resulted in positive therapy

outcomes[29].Similarly,astudyperformedbyFlynnetal.[30]appliedalow-costcommerciallyavailable

gaming platform to promote the post-stroke recovery process. The study intervention included the

PlayStation2Eyetoysoftwarewhichconsistedof23differentvideogames.Flynnetal.[30]reportedthat

VRcreatedanengagingandmotivatingtherapysituationand,moreimportantly,thatthegamingsystem

beneficially impacted the recovery process andwas able to reduce functional impairments stemming

from stroke [30]. This study had one substantial limitation though: Based on participant’s feedback,

some of the PlayStation 2 Eyetoy games were perceived as too complex for the use by functionally

impaired individuals [30]. Therefore, the authors emphasized the need for customization in order to

optimallyaddresstherapeuticneeds.Thisdrawbackisnotsurprising,giventhatthePlayStation2gaming

systemwas (and is stillbeing)developed for the leisure industry. In linewith the resultofFlynnetal.

[30], several other studies highlighted that videogames designed for entertainment rather than

therapeuticpurposesarenotperfectlysuitablefortheuseinrehabilitation[3,24,31-32].Inall,thereis

clearlyaplaceforVR-basedsystemsinrehabilitation,butthesesystemsmustbetailoredtothecognitive

andphysicalconstraints–aswellasthetreatmentgoals–ofthetargetpopulation.

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Recently, the development of such tailored videogames has begun. For example, the VR-based

RehabilitationGamingSystem(RGS)proposedbyCameirãoetal.[33]focusedonthetreatmentofupper

extremity disorders following stroke. Likewise, the ongoing EU funded project FITREHAB [34] aims at

developingaVR-based rehabilitationand trainingplatform toprovidea customizedexerciseprogram.

Althoughthis isdefinitelyawelcomedevelopment,wefeelthatthesepioneeringstudiessufferfroma

lackoftightcooperationbetweenrehabilitationspecialistsandgamedevelopers.Moreconcretely,since

establishedgamedesignprincipleswere largelyunheeded, ratherboringandunattractivevideogames

resulted, which arguably lessened the aforementionedmotivationalmerit of the gaming approach to

rehabilitation. Importantly, rehabilitation games should not only be tailored to therapeutic goals in

which both therapist and patient needs are explicitly considered, but also be based on fundamental

gamedesignprinciplesmakingvideogamesfascinatingand,thereby,rehabilitationmoreengaging.

1.3Gentile’smotorskilltaxonomyforrehabilitation

Strongevidenceexists thataneffective therapyprogram in rehabilitation shouldbe theory-basedand

guidedbyestablishedmotorlearningprinciples[35-39].Foursuchprinciplesaretask-specificity[40-42],

highrepetitionintensity[43],variablepractice [44-48]andprogression[49-50],allofwhichpromisean

increased motor recovery effect and hence serve to ground a physical rehabilitation program

theoretically.However,severalresearchershaverecognized–andcriticized–theabsenceofapractical

framework within which such principled training programs can be developed.What is required is an

adequate template to createagraduallyprogressing rehabilitationprogram including task-relatedand

variabletrainingexercises.Gentile’staxonomy–aclassificationsystemtodifferentiatemotorskills[51]

– provides just such a template and hence constitutes a practical tool for developing theory-based

trainingprograms.Inthefollowing,IwilldescribeGentile’staxonomyinmoredetail.

Gentile posits that anymotor skill can be specified according to two general dimensions; namely the

skill’senvironmentalcontextandtheskill’sfunction[51-52].Shesubsequentlydivideseachofthesetwo

orthogonaldimensions(i.e.,environmentalcontextandactionfunction)intofourdiscretelevelssothat

they form a 4x4-table of 16 so-called skill categories (see Table 3.1, Chapter 3). This table of skill

categoriesformsthebasicframeworkofthetaxonomy.

Within the firstdimension (environmentalcontext), the four levelsaredefinedwithtwo indicators: (a)

regulatory conditions (i.e., relevantobjectsorpeople influencingaperson’s skill performance)and (b)

intertrialvariability.Theregulatoryconditionscaneitherbestationary(stationaryregulatoryconditions)

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or in motion (in-motion regulatory conditions) and these, hence, represent the first two levels of

environmental context. Indicator (b) then furtherdivideseachof these levels according towhetheror

not these regulatoryconditionsvary fromtrial to trial: intertrial variabilityandno intertrial variability,

respectively.

Theseconddimension(actionfunction)alsoconsiderstwoindicators:(a)bodyorientationand(b)object

manipulation.Thetermbodyorientation indicateswhetherachangeinbodylocationisrequired(body

transport)ornot(bodystability)inordertoperformaskillsuccessfully.Thisindicatorformsthefirsttwo

levelsofactionfunction.Indicator(b)thenfurtherdivideseachoftheselevelsaccordingtowhetheror

nottheskillrequiresobjectmanipulation:objectmanipulationandnoobjectmanipulation,respectively

(seeTable3.1,Chapter3).

Gentile’s structured differentiation of 16 skill categories is simple yet accommodates all four training

principlesmentioned above: It ensures (1) variable practicebecause each of the 16 skill categories is

characterized by unique features and (2) systematicprogressionbecause difficulty increases from the

top left to lower right taxonomy corner. Furthermore, it allows for the flexible definition of (3) task-

specific skill practice and (4) high repetition intensity. These favorable characteristics instigated the

developmentofavirtualrehabilitationapproachbasedonthetaxonomyproposedbyGentile.

1.4TheinstrumentedTimedUpandGotestforrehabilitationefficacyassessment

Monitoring activities performed by individuals with chronic conditions (e.g., stroke) participating in

home-based treatment programs has been considered a matter of paramount importance [53]. A

valuabletoolforthecliniciansindiseasemanagementwouldbetheuseofwearablesensortechnology

toautomateclinical testingprocedures [53].Thepatientscouldbeable toperformtheclinical testing

procedures independently at home. This would make the regular assessment of the effectiveness of

home-basedrehabilitationinterventionspossible.Well-establishedtoolsformotorfunctionassessment

are,therefore,neededtooptimize–foreachindividualpatient–monitoringofthechangeprocessafter

stroke.Onefundamentalpreconditionofsuchatool isthefulfillmentofreliabilityandvaliditycriteria.

Moreover, in a training program focusing on regaining normal walking function, the assessment tool

shoulddetectbalanceandmobility impairmentswithhighsensitivitysothat interventioneffectiveness

canbeadequatelyevaluated.TheTimedUpandGotest(TUG)hasbeenshowntomeetallthosecriteria

[54-57]andhenceitcomesatnosurprisethatitisoneofthemostfrequentlyusedmotorfunctiontests

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inthestrokepopulation[54,58-59].TheTUGdoes,however,havethedrawbackoffocusingonlyonthe

singleoutcomeparameter ‘time’neededtocompletetheentire testprocedure [57,60].Furthermore,

the TUG procedure is only considered as a whole and does not allow separate analysis of the

subcomponentsincludedinthetest(i.e.,sit-to-walk,gait,turningandturn-to-sit)[57,60].

In order to overcome the limitations associated with the original test protocol, the TUG has been

‘instrumented’ in the sense that small inertial sensors are strategically placed on patients’ bodies. By

means of these sensors,many additional gait- and transition-related outcomes can be revealed [60].

Previous studiesdemonstrated that this so-called instrumentedTUG (iTUG) is a reliable and valid gait

analysissysteminbothhealthypeopleandsubjectswithParkinson’sdisease(PD).Althoughthisclearly

renderstheiTUGapromisingtoolinclinicalpractice[57,60],itsreliabilityandvalidityasabalanceand

mobilityassessmenttoolinpeoplewithstroke-inducedmotordeficitsremainstobeconfirmed.

1.5Theaimandscopeofthisdoctoralthesis

Overall,thepresentthesisattemptstodevelopandevaluateatreatmentapproachusingVRforat-home

rehabilitation following stroke. The thesis focuses on the development and testing of VR-based

rehabilitationgamestargetingchronicstroke.

Chapter 2 offers the technical context by describing the main gaming functionalities that determine

rehabilitationoutcome.Specifically,itcoversthedevelopmentofanadaptivegameenginesystemusing

specifically designed rehabilitation games based on Gentile’s two-dimensional classification system of

motorskills.

InChapter3, the focus ison themainclinicalguidelines thatcontribute topositivemotor recovery. It

discusses Gentile’s taxonomy as a promising framework for the development of virtual treatment

programsthatareconsistentwithprimarymotor learningprinciples.Aprogramispresentedthatuses

sixbasicrehabilitationgamestogenerate16virtualrehabilitationscenariosthateachrepresentoneof

Gentile’s16 skill categories. Finally, a formalprocedure forguidingpatients through the rehabilitation

processisdiscussed.

Chapter4and5constitutetheexperimentalsectionofthisdoctoralthesis.

Chapter4isbasedonausabilitystudyinwhichnovelrehabilitationgames–developedinthecontextof

the REWIRE project – were applied. The study aimed to investigate whether the VR-based approach

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wouldbeusableandeffective in improvingpeoples’ gait andbalance. Themethodological framework

recommended by Campbell et al. [61] was used as a basis for this study. Accordingly, the study

represents a preliminary exploratory phase (i.e., with untrained healthy elderly) of the large-scale

REWIREprojectthatfocusesonstrokepatients.

Since, to our knowledge, no study used the sensor-based iTUG tomeasure functional recovery post-

stroke, the study described inChapter 5of this thesis served to investigate the iTUG’s reliability and

validityinpeoplewithstroke.Thischapterprovidestheresultsofanexperimenttoassessthetest-retest

reliabilityandvalidityofgait-andtransition-relatedmetricsduring iTUGperformance.Fourteenstroke

patients and 25 healthy controls were observed by one researcher in two measurement sessions.

Outcomemeasuresweretherelativereliability(i.e.,intraclasscorrelationcoefficient(ICC)),theabsolute

reliability (i.e., standard error ofmeasurement (SEM), limits of agreement (LOA) and smallest clinical

detectabledifference (SDD))and the iTUGmetrics’discriminatorycapabilitiesbetweenstrokepatients

andhealthycontrols.

Finally,Chapter 6 provides a general discussion of themain results presented in this doctoral thesis.

WithrespecttosubsequentresearchstudiesintheframeworkoftheREWIREproject,implicationsofthe

results and limitations are considered.Additionally, new researchquestions generatedby thepresent

resultsandgeneralconclusionsarepresented.

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57. ZampieriC,SalarianA,Carlson-KuhtaP,AminianK,NuttJG,HorakFB.Theinstrumentedtimedupandgotest:potentialoutcomemeasurefordiseasemodifyingtherapiesinParkinson'sdisease.JNeurolNeurosurgPsychiatry.2010;81(2):171-6.

58. FlansbjerUB,HolmbackAM,DownhamD,PattenC,LexellJ.Reliabilityofgaitperformancetestsinmenandwomenwithhemiparesisafterstroke.JRehabilMed.2005;37(2):75-82.

59. deOliveiraCB,deMedeirosIRT,FrotaNAF,GretersME,ConfortoAB.Balancecontrolinhemipareticstrokepatients:Maintoolsforevaluation.JRehabilResDev.2008;45(8):1215-26.

60. SalarianA,HorakFB,ZampieriC,Carlson-KuhtaP,NuttJG,AminianK.iTUG,asensitiveandreliablemeasureofmobility.IEEETransNeuralSystRehabilEng.2010;18(3):303-10.

61. CampbellM,FitzpatrickR,HainesA,KinmonthAL,SandercockP,SpiegelhalterD,TyrerP.Frameworkfordesignandevaluationofcomplexinterventionstoimprovehealth.BMJ.2000;321(7262):694–6.

12

2

Computational intelligence and game design for effective at-home

stroke rehabilitation

BorgheseNA1,PirovanoM1,2,LanziPL2,WüestS3,deBruinED3

1DepartmentofComputerScience,UniversityofMilan,Italy

2DipartimentodiElettronica,InformazioneeBioingegneria–PolitecnicodiMilano,Italy

3InstituteofHumanMovementSciencesandSport,DepartmentofHealthSciencesandTechnology,ETH

Zurich,Switzerland

GamesforHealthJournal2013;2(2):81-88

13

Abstract

Objective:Theaimofthisarticleistodescribeagameenginethathasallthecharacteristicsneededto

supportrehabilitationathome.Thelow-costtrackingdevicesrecentlyintroducedintheentertainment

market allowmeasuring reliably at home, in real time, players’motionwith a ‘hands-free’ approach.

Such systems have also become a source of inspiration for researchers working in rehabilitation.

Computer games appear suited to guide rehabilitation because of their ability to engage the users.

However, commercial videogames and game engines lack the peculiar functionalities required in

rehabilitation: Games should be adapted to each patient’s functional status, and monitoring the

patient’smotionismandatorytoavoidmaladaptation.Feedbackonperformanceandprogressionofthe

exercises should be provided. Lastly, several tracking devices should be considered, according to the

patient’spathologyandrehabilitationaims.

SubjectsandMethods:Wehaveanalyzedtheneedsof thecliniciansandofthepatientsassociated in

performingrehabilitationathome,identifyingthecharacteristicsthatthegameengineshouldhave.

Results:Theresultofthisanalysishas ledustodevelopthe IntelligentGameEngineforRehabilitation

(IGER) system, which combines the principles upon which commercial games are designed with the

needsofrehabilitation.IGERisheavilybasedoncomputationalintelligence:Adaptationofthedifficulty

leveloftheexerciseiscarriedoutthroughaBayesianframeworkfromtheobservationofthepatient’s

successrate.Monitoringisimplementedinfuzzysystemsandbasedonrulesdefinedfortheexercisesby

clinicians.SeveraldevicescanbeattachedtoIGERthroughaninputabstractionlayer,liketheNintendo®

(Kyoto, Japan)WiiTM Balance BoardTM, theMicrosoft® (Redmond,WA) Kinect, the Falcon fromNovint

Technologies(Albuquerque,NM),ortheTyromotion(Graz,Austria)Tymo®platebalanceboard.IGERis

complementedwithvideogamesembeddedinaspecifictaxonomydevelopedtosupportrehabilitation

progressionthroughtime.

Conclusion:Afewgamesaimedatposturalrehabilitationhavebeendesignedanddevelopedtotestthe

functionalitiesoftheIGERsystem.Thepreliminaryresultsoftestsonnormalelderlypeopleandpatients

with the supervision of clinicians have shown that the IGER system indeed does feature the

characteristicsrequiredtosupportrehabilitationathomeandthatitisreadyforclinicalpilottestingat

patients’homes.

14

2.1Introduction

Novel tracking devices, like the Nintendo® (Kyoto, Japan)WiiTM and Balance BoardTM andMicrosoft®

(Redmond,WA)Kinect,havemadetheinterfacewithvideogamesmorenaturalandintuitive,leadingto

the success of these devices and their associated games. The capability of measuring the players’

movements has been early recognized as a major step forward in realizing cheap and reliable

rehabilitationsystemsinwhichthepatientcanbeguidedthroughrehabilitationexercisesbyadequate

videogames. Such capabilityhasbeenexplored in the rehabilitation field [1-3] andby recently funded

EuropeanCommissionprojects[4-7].

However,itwassoonrecognizedthatthevideogamesdevelopedfortheentertainmentmarketarenot

adequateforthepaceandthegoalsofrehabilitation[8-10]:Theirfastinteraction,whichcanbebarely

matched to the patient’s residual functional abilities, and thewealth of targets and distractorsmake

usabilitylowandmayproducestrainandanxiety.Thus,onehurdlefacingthesuccessfuluseofexercise

videogames (or exergames) in older adults and functionally impaired population is thatmany off-the-

shelf videogames are too complex for use by these groups [8]. Videogames must, therefore, be

developedtotakeintoconsiderationthecognitiveandphysicallimitationsofthepopulation(s)forwhich

theyareintended.Thisisthereasonwhygamesexplicitlydedicatedtorehabilitationhavebeenrecently

developed.

In addition, in the REWIRE [4] project, the need for developing game engines of a new generation,

specificallytargetedforrehabilitationpurposes,hasbeenclearlyidentified.Suchenginesshouldhavea

twofoldgoal:The first, commontoallgameengines, is toprovideall functionalities for thegameplay,

andthesecond,associatedwiththeirtherapeuticrole,istoprovidereal-timemonitoringandadviceto

thepatient.Rehabilitationgameenginesshould(1)adaptthedifficultyandthegameplaytothepatients’

abilities to avoid frustration and, most importantly, (2) should monitor maladaptation and wrong

postures,asthesewouldmakerehabilitationmoreharmfulthaneffective.Thegameengineshouldalso

beable(3)togiveanadequatereal-timefeedbacktothepatientwhileexercising.

Another open problem when applying games in rehabilitation is the definition of a rehabilitation

schedule based on important training principles (e.g., objective progression in the therapy, with an

increasinglevelofdifficultymappedontotherehabilitationplanandgoals).

In the following, we discuss how these issues have been addressed inside the REWIRE platform. In

particular, we illustrate the Intelligent Game Engine for Rehabilitation (IGER) system, developed

15

specificallytosupportrehabilitationthroughgames,andhowthiscanbeintegratedwiththedefinition

of an adequate taxonomy for rehabilitation progression through time inspired by thework ofGentile

[11].

2.2Materialsandmethods

Thedevelopmentofaneffectivegameengineforrehabilitationhastobebasedoninputsfromclinicians

andpatients. Severalmeetings havebeenorganized to elicit such specifications. The key issue is that

rehabilitation games cannot work as stand-alone applications but must be included into a broader

structure involving patients, therapists, clinicians, hospitals, and institutions at the regional/national

level. This is specifically the approach pursued inside the REWIRE project, recently funded by the

EuropeanCommission.TheREWIREplatformimplementssuchabroadperspectivebyintegratingthree

mainhierarchicalcomponents:Ahospitalstation(HS),anetworkingstation(NS),andapatientstation

(PS),undertheassumptionthatsuchastructureenableseffectivesupportofat-homerehabilitation.

The HS is used by clinicians to define and schedule the rehabilitation at home. It also monitors the

patient’s progression remotely and supports a virtual communityof patients and clinicians thathelps,

educates,andmotivatesthepatients.TheNSisinstalledatthehealthprovidersite,ataregionallevel.It

providesadvanceddatamining functionalities todiscoverpatterns in rehabilitation treatmentsamong

hospitals and regions. ThePS is installed at patients’ homes andhas at its core the IGER (Figure 2.1),

which guides patients through their actual rehabilitation schedule using engaging and targeted

videogamesandmonitorspatients’movementsandtheircorrectexecutionoftheexercises.

An additional hospital communication module of the station allows patients to interact with the

clinicians at the hospital and to download the rehabilitation program and the configuration of the

associated games. REWIRE contains also a lifestyle module that collects data on the patient’s daily

activitythroughabodysensornetworkthatisused,alongwithenvironmentalandphysiologicaldata,to

tunethegames’difficultylevel,assesspotentialrisks,andadvisecliniciansonthetherapy.

Finally,avirtualcommunitymodule,managedbythehospital,actsasaclientofthepatients’community

andallowspatientstointeractwithapeergroup.

16

Figure2.1:TheIntelligentGameEngineforRehabilitation(IGER)anditsgameandcontrolmodules.Theconnectionswiththepatient and the therapist at the hospital and the virtual therapist, which provides real-time feedback to the patient, arehighlighted.

Rehabilitationscheduling

Rehabilitation exercises are designed by therapistswith specific goals, for example, (1) to increase or

maintainmobilityofthejointsandsurroundingsofttissues,(2)todevelopcoordinationthroughcontrol

ofindividualmuscles,(3)toincreasemuscularstrengthandendurance,or(4)topromoterelaxationand

reliefoftension[12].

For each exercise, therapists define the correct way to perform it, and, in one-on-one sessions, they

check that patients perform only correct movements and maintain correct postures so as to avoid

maladaptationand,therefore,inadequaterehabilitation.

Thevarietyofexercisesisquitelargeanddependsonthetherapists’idiosyncrasies.Thus,itisdifficultto

map the therapists’ rehabilitation exercises, their goals, and the mandatory posture/movement

constraintstotheirimplementationasvideogames.

In our work, we guide the mapping between therapy and engaging videogames by using Gentile’s

taxonomy of motor skills [11], which identifies high-level features of rehabilitation routines and

organizestheminahierarchicalstructure(Figure2.2).

Gentile’staxonomy[11] isatwo-dimensionalmatrixthatcontainsexerciseswith increasingcomplexity

oftheaddressedfunctionality(frombodystabilitytobodymovement)initscolumns.Initsrowsarethe

17

conditions under which the exercises are executed, from simple static environments to time-varying

situationswithintertrialvariability.

With this taxonomy, it becomes easier to design and configure games for rehabilitation. In fact, any

exerciseformotorskillrehabilitation(proposedbyanytherapist)canbeclassifiedinoneelementofthe

taxonomy according to a progression in recovering functionality. At the same time, rehabilitative

videogamescanbedevelopedbytargetingoneelementofthetaxonomyratherthanaspecificexercise

proposedbyaspecifictherapist,thusbroadeningthenumberoftherapistsandpatientswhomightuse

it.

Figure2.2:Gentile’s taxonomy[11],withapossiblemappingofexercisesandapossibleprogression forbalanceandposturerehabilitation.Thearrowindicatesapossibleprogressionofthepatientandthepossiblemappingsofthe‘Fruitcatcher’gamedescribedhereafter.

TheIGERgameengine

TheIGERisthecorecomponentofthePS.Itcomprehendsagameengineandagamecontrolunit.The

formerprovidesallthebasicgamingfunctionalities(inputdata,animation,collisiondetection,rendering,

andgamelogic);thelattercontrolsthegame,andithasbeendevelopedtomatchtheneedsofgames

forrehabilitation:

18

1. Itschedulesthegames,chosenandconfiguredaccordingtotheframeworkshowninFigure2.2.

2. It adapts the game difficulty level to the actual patient’s performance capacity, so that an

adequatechallengelevelismaintained.

3. It supervises thegamingsessionsandmonitorswhetheror if thepatient’smovementscomply

withthespecificationssetbythetherapist.

4. Itdisplaysavirtualtherapist(VT)toadviseandprovidefeedbacktothepatientonthetherapy.

Games defined for rehabilitation have to be parametric. Specifically, games should be defined by

parameters that can be regulated and adapted, depending on the level of game difficulty. Such

parameters are initialized inside the hospital, where the clinician prescribes the therapy and are

continuously adapted to each patient’s progression. Such parameters can be, for instance, either the

frequencyof theobstaclesandof the targets inside thegameor therangeofmovements required to

complete a game successfully. The control unit implements a real-time adaptation of the parameters

through a Bayesian model [10]: The patient’s performance is monitored, and the success rate is

computedonline. Theparameters are then increasedor decreased such that a certain success rate is

maintained,wheretheamountofchangeisprovidedbythemodel.

Thepatient’smovement isalsoused formonitoring.To thisaim,a setof rulesof correctexecution is

defined inside theHS.Suchrules representaknowledgebase fromthe therapist’sexperienceandare

coded into logical propositions like, for instance, “do not bend the trunk” or “keep your feet slightly

apart”. Such rules are then fuzzyfied, defining a maximum range allowed for correct execution (e.g.,

maximum trunk bending allowed in 20°) and associating automatically intermediate ranges with the

valuesinbetween(Figure2.3).Avisualinterface,showinganavatarinsidethegameenvironment,helps

thetherapistsindefiningtheconstraintsonthepatient’smotion.

Atrun-timetheknowledge-basedmonitor insidethecontrolunit(Figure2.1)comparesthemovement

ofallthebodysegmentswiththerulesdefinedinsidetheHSbythecliniciansandraisesanalarmlevel

thatcanbegraded:riskysituation,badmovement,orwrongmovement.Ifmorethanoneconstraintis

violated, the most severe alarm level is raised, implicitly combining the fuzzy rules with the logical

operator.

19

Figure2.3:Thegraphicalinterfaceusedtodefinethemotionconstraintinsidethehospitalstation.Theautomaticfuzzyficationofaparameteronwhicharulehasbeendefinedisshown.

The monitor supervises also the online adaptation process. Depending on the severity of the alarm

raised, themonitor can stop increasing thegamedifficultyuntil thepatientachievesa correctwayof

playing.

Oncethealarmhasbeenraised,thecontrolunithastogiveanadequatefeedbacktothepatient.Inside

theIGERwehaveimplementedseveralmethodstoprovidesuchfeedback.Thefirstmethodconsistsof

displayingavisualfeedbackintheformofatextoranicon(e.g.,asmileyface)andanaudiofeedbackin

theformofawarningsound(Figure2.4d).Thesecondmethodconsists inshowingaVTthatcanwarn

thepatientthatheorsheisnotdoingtheexercisecorrectly(Figure2.4a).Thisisanavatartherapist;her

face is animated throughmorphing expressions that are combined randomly to give her a variety of

expressions,occasionallytiltingtheheadorblinkingtheeyes.Thethree-dimensionalmodelfeaturesalso

simplifiedlipsyncingforamorerealisticvoicefeedback,allowingplayingbackstandardrecordedaudio

messageswhilethelipsofthethree-dimensionalmodelmovereasonably.Thesecondformofanavatar

isa three-dimensionalmascot (Figure2.4b), similar towhatNintendodoeswith itsWiiBalanceBoard

avatar in the Wii Fit games. The third form of feedback is a video of a real therapist (Figure 2.4c),

recordedandplayedbackwhenneeded.

Inallcases,whenthealarmrisestothewronglevel,thegameispaused,andtheavatarinsidethegame

showsthecorrectpostureandmovementsuperimposedonthepatient’slastmovementonthescreen

tothepatient.

20

Figure2.4:ThefeedbackimplementedinsidetheIntelligentGameEngineforRehabilitation:(a)avirtualtherapist,(b)amascot,(c)arealtherapist,and(d)anicon(smileyface)showninsidethegame.

Principlesofgamedesign

Wehavebuiltthroughourframeworkasetofminigames,eachdesignedaccordingtothegoalsandthe

requirements of the underlying exercises and on the good game design practice [13-15]:Meaningful

play,flowtheory,andsenseofpresencehavebeenallincorporatedintothedesign.

Meaningfulplaystatesthateachgameactionmusthaveadirectandclearlydistinguishablefeedbackas

wellasareasonablylastingeffect.Thishelpsthepatientinunderstandingwhatheorshecanandcannot

do. Itwas achievedhere through a clear video-audio feedbackof the success or failure of a patient’s

action,representedrespectivelywitha‘P’greensymboldisplayedonthescreenandanicebeepanda

‘X’redsymbolandanannoyingbeep.

Thesecondbasicprincipleisthetheoryofflow,whichstatesthatwhentheskillsoftheuserarematched

bythelevelofchallengeposedbythegame,theuserentersastateofcompletefocusandimmersionin

whichheorshelosestrackoftime[14].Thepatient’sappropriatelevelofexercisedifficultyisachieved

inside IGER through an adaptation mechanism based on a Bayesian framework [10]. Scenarios and

positionoftargetsanddistractorsofeachgamearerandomized,makingthepatientfeelchallengedby

always different situations. Music matched to the game scenarios is played during the rehabilitation

sessions. The scoring system reflects the rehabilitation nature of the games [8-10, 16]: No negative

pointsaregiven,orno ‘death’occurs,andanactualscorevaluereflects theaccuracyand/orspeedof

21

execution of the movement. Former scores are shown along with the actual score to demonstrate

improvement over time. All these elements contribute to create a flow experience that, in turn,

contributes in focusing on the game. This hides the burden of therapeutic repetitive tasks and the

difficulties arising from impairments, under the entertaining experience of a game. This is evenmore

importantwhenweconsiderthatpost-strokepatientsoftenfallintodepression[17].

ThesenseofpresenceisanotherstrongpointassociatedwithIGER.Astheavatarfollowsthepatient’s

movementswithnoappreciabledelays, thepatientcanfeel that theavatarrepresentshim-orherself

insidethevirtualenvironmentand,therefore,thepatienthasastrongperceptionofbeingtheactorin

thegame[18].Thisisassociatedwiththeuseof‘hands-free’trackingofmotion,whichdoesnotrequire

attachinganydevicetothepatient,allowingthemostnaturalinterfacingwiththegames.

Gamesforrehabilitation

Inourwork,weaimtocreateasetofminigamesbuiltonclinicallyvalidexercisesandcomprehending

bothmonitoringandadaptability.Wedesignedandrealizedseveralgameconceptsthataddressposture

andbalancerehabilitation.ThesegamescanbemappedonasetofexercisesdefinedthroughGentile’s

taxonomy [11] and share the same theme (in our case, the farm theme) to provide a continuity in

gaming during the patient’s rehabilitation process. To exemplify, we present here two of these

minigames:‘Animalfeeder’and‘Fruitcatcher’(Figure2.5),whichhighlighttheflexibilityofourapproach

andthemonitoringandadaptationcapabilities.

Figure2.5:Twominigamesofthepatientstation:(a)‘Animalfeeder’and(b)‘Fruitcatcher’.

The‘Animalfeeder’minigameaimstotrainpatients’balancebyimplementingadualtask.Theexercise

requires thepatient to kneel in frontof thedisplay and tomove the impairedarm to touchdifferent

targets,whicharerepresentedbythreehungrycowsthathavetobefed.Thecowskeeprequestingfood

22

bymooingwhileopening theirmouths (Figure2.5a). Theplayer controls a virtualhand in first-person

view.Heorshehasfirsttocollectsomehayandthenfeedittooneofthehungrycows;whenthecow

has been fed, the player’s score increases. If a cow remains hungry for too long, it groans, and the

player’sscoredecreases.Inaddition,apitchforkpositionedtotheleftoftheplayermustbekeptupright

bytheplayerwithhisorherotherhand.Iftheplayerfailstodoso,thepitchforkbreaks,andtheplayer’s

scoredecreases. ‘Animal feeder’ canbecurrentlyplayedwithdifferentdevices. Inparticular,here the

player’shandwastrackedthroughaKinectcamerapositionedabovethedisplay,whilethepitchforkwas

controlledbyNovintTechnologies(Albuquerque,NM)Falcon®hapticdevice,whichproducesanelastic

force to the patient’s hand proportional to the hand displacement. Note that devices not used for

gameplaycanstillbeusedforadditionalmonitoringofthepatient.Forinstance,Figure2.5bshowshow

Nintendo’sBalanceBoardisusedtomonitorthepositionofthefootcenterofpressurewhileperforming

agame.Inthiscase,theoscillationsdonotaffectthegameplay,butprovideusefulinformationinterms

ofapatient’sbalancecapability.

The‘Fruitcatcher’game(Figure2.5b)isbuiltontwodifferentexercises.Forthefirstexercise,thepatient

isrequiredtoshifthisorherupperbodytotheleftandtotherightside,whilekeepingthefeetstillon

theground.Forthesecondexercise,thepatientmustmove laterally insidetheminigame. Inthebasic

conceptof ‘Fruitcatcher’, theplayermustcatchfruits falling fromthetopofatree.Theplayeravatar

standsbelowthetreewithavirtualbasketonitsheadandcanmovethebodylaterallytocatchthefruits

with the basket. The player’s score increases when a fruit falls into the basket. The fruits fall from

differentheightsandfromdifferentpositionsonthehorizontalaxisandatadifferentfrequency.Likethe

‘Animal feeder’game, itcanbeplayedwithdifferentdevices (e.g., theNintendoWiiBalanceBoardor

theMicrosoftKinect).Thechoiceoftheinputdevice,inthiscase,dependsalsoontheexerciserationale,

showinganexampleofseparationbetweengameandexercise.Whenusing theNintendoWiiBalance

Board,theplayerisconstrainedtokeepthefeetontheboard.Thus,onlythefirstexercisecanbedone

inthisway.WhenusingtheMicrosoftKinect,instead,theplayercanmovefreelyaroundtheplayarea.

Inthislattercase,theexercisecanbeeitherofthetwodescribedabove.InFigure2.2,wecanseewhere

thetwoexercisesaremappedoverGentile’staxonomy[11].Apossibleprogressioninsidethetaxonomy

isshowninFigure2.2:Thepatientstartswithanexerciseclassifiedas1A,whichbelongstothelowest

classification,defininganeasyexercise. In thiscase,using the ‘Fruitcatcher’gameasanexample, the

patientmayonlyhavetostandstillandnottomoveinordertonotdisturbthetree;otherwise,itsfruits

wouldfalldown.Asthepatientprogressesandimprovesstrengthandbalancecapability,thegamemay

movetowardthe1Dbox,addingbothbodytransport(requiringthepatienttomovearound)andobject

23

manipulation(addingthebasketontheheadandtherequirementtocatchfruits).Then,thepatientmay

be presented with intertrial variability, moving the classification to 2D. At last, the patient may be

required tomeetbirds flyingaround thevirtual areaanddisturbinghisorher focus, thusmoving the

classificationtoward4D.

Toaccommodatesuchavarietyoftrackingdevices,wehaveinsertedanInputAbstractionLayerinside

theIGER.OurprototypecurrentlysupportstheSony(Tokyo,Japan)PlayStation®PS3TMEyecamera,the

Microsoft Kinect camera and its microphone array, theWii Balance Board, or the Tyromotion (Graz,

Austria)Tymo®plateandtwohapticdevices(theOmni®Phantom®[SensableTechnologies,Wilmington,

MA] and the Novint Falcon). The input devices can be combined for additional control over game

elementsorforimplementingdualtasks.

2.3Discussion

Manyauthorshaveacknowledgedthepowerofimmersionassociatedwithvirtualrealityandgamesin

particular [19, 20]. This is referred to as presence; it would facilitate the rehabilitation sessions by

providingafun,interactiveenvironmentthatchallengestheskillsoftheplayerandimmersestheplayer

in a virtual world. Such an approach would limit the typical boredom and fatigue in traditional

rehabilitation:Thepatient,whileexercising,shouldfeellikeaplayer,focusedonhavingfunwhileplaying

thegame.Tofullyachievethis,gamesshouldbedesignedaccordingtogoodgamesdesignprinciplesto

avoidcomingupshortinengagingthepatients.

However, engaging games are not enough: Adaptation, monitoring, and real-time evaluation of the

movements should be provided to the patient in real time. Such functionalities are not provided by

commercial games, but are indeed incorporated inside the IGER system. In fact, (1) IGER allows

configuring thegame inside theHS, setting theparametersassociatedwith the levelofdifficultymost

adequate to the patient’s functional status, and then it continuously adapts these parameters to the

patient’sperformancetocontinuouslychallengethepatientattheproperlevelatanypointduringthe

rehabilitationprocess.(2)IGERallowsthecontinuousmonitoringofpatients’actionsandpostureswithin

thegameengine,and itaimstoenforceacorrectexecutionoftherehabilitationmovements. (3) IGER

integrates a real-time feedback to the patient of his or her performance and of possible wrong

movements,accordingtotherulessetbythetherapists.

Monitoringandreal-timefeedbackhavebeendesignedtosubstitutefor,althoughtoa limiteddegree,

thetherapist.Inone-on-onesessions,thesefunctionsareprovidedbythehumantherapist,whocannot

24

be present at home during rehabilitation. Themonitoring role is achieved by the fuzzymonitor that

implementstheruledefinedbythetherapisthim-orherself,mainlytoavoidmaladaptation.Therules

operateinrealtimeonthemotiondataandaredownloadedfromtheHSatgameconfigurationtime.

The social aspects of rehabilitation are very important for patients and must be considered when

designing a platform for home rehabilitation. For instance, in one-on-one sessions, the therapist is a

major source of motivation for the patient [21], but this component is missing during home

rehabilitation.Toavoidisolation,whichdiminishestheappealofarehabilitationsession,IGERprovides

aninformativeevaluationtothepatient,besidesdisplayingabalancedscorethatreflectsperformance

ontheactualexercise,bymeansofaVTthat, throughspeech,evaluatesthepatient’sperformanceof

theexercise.

Giventheimportanceoftheissue,wehaveevaluatedseveralfeedbackmodalities.Icons(e.g.,asmiley

face)andsoundsareespeciallyusefulbecausetheyprovideimmediateandeasilyunderstoodfeedback

tothepatient.Moreover,visual iconsandsoundshaveamoreimmediateeffectthantheVT;theyare

less intrusiveandlessannoyingwhenrepeatedoften.Forthisreason,weusethemforthesimpleand

morefrequentwarnings.

TheVT,becauseofitsresemblancetoarealtherapist,allowsthepatienttofeelthepresenceofamore

seriouscharactersupervisinghisorheractivity.Themascot,ontheotherhand,canbebeneficialasa

motivatorbecauseofitsfunnyaspectandmovements,enhancingtheplayfulaspectoftheapplication.

Thevideoisusefulbecauseofitsrealismandthepresenceofarealperson,whocouldbepreferredby

the patient for a greater degree of empathywith the therapist. This implies a somehow stereotyped

videostyle,astheamountofvariabilityinthevideoappearanceismuchlessthanwithmascotsorthree-

dimensionalmodels.Webelievethatthereisnotasinglebestfeedback,buteachpatientwillhavehisor

herownpreference,dependingonpersonalidiosyncrasies.

The VT and themascot can also be displayed between two games (exercises) of the same session to

introduce the exercises and accompany the patient along his or her training period. In addition, they

appear during the introduction of the game to explain its rules and during the course of the game,

encouragingandmotivating theplayers according to theirperformance. Lastly, theyappearwhen the

gameisstoppedbecauseofwrongmovements,explainingtothepatientwhatwentwrongandwhatthe

patientshoulddo.

25

A proper game design and games specifically designed for therapeutic purposes are not sufficient. A

complete rehabilitation program is required, and this can be defined only by a clinician. Besides the

game engine, a clear definition of a rehabilitation path is required to support intensive prolonged

rehabilitation processes. The therapist has still the fundamental role of the supervisor, although

remotelyfromthehospital.Thesuccessionofgamesinsidetherehabilitationprogramiscustomizedby

the therapist for each patient according to his or her impairments; the program is defined at the

hospital,accordingtotherehabilitationgoalssetwiththepatientandthecurrentpositionofthepatient

inside the taxonomy (Figure 2.2). The therapist can also fully configure each game, thus tailoring the

underlying exercise to the patient’s health status. For instance, the therapist can define, for each

exercise,what inputdeviceshouldbeused,howlongtheexerciseshould last,howfarthetargetscan

travel,andhowfasttheycanmove.Finally,thetherapisthasanimportantroleconcerningthedefinition

oftheknowledgebaseonwhichtherulesmonitorapatient’smovementsandhisorherconstraintsare

builtupon.Apersonalizedrehabilitationprogramcanthereforebeobtained.

2.4Conclusion

Thisworkistheresultofatightcollaborationamonggamedevelopers,humanmovementscientists,and

physicaltherapistsandaimsatbuildingengaginggamesthatimplementtherapeuticexercisestargeted

toat-homerehabilitation.WedesignedtheIGERplatformtotakeupsomeofthetherapist’sfunctions

duringhomerehabilitation.Althoughcompletelyreplacingthetherapist’sskillisbeyondreach,theIGER

system can make rehabilitation at home a viable option, especially if intertwined with periodic

rehabilitation sessionsat the referencehospitalwith the reference cliniciansmaintaining, therefore, a

personalrelationshipthatispresumablyfundamentalforprolongedrehabilitation.

Authors’contributions

NABcontributedtotheconceptionanddesignof themanuscript,andwritingthemanuscript.MPand

PLL have been involved in drafting the manuscript and critically revised the manuscript. SW made

substantial contributions to conceptionanddesignof themanuscript, andparticipated indrafting the

manuscript. EDdB participated in drafting the manuscript and revising it critically for important

intellectualcontent.Allauthorsreadandapprovedthefinalmanuscript.

26

Acknowledgments

This work was partially supported by the REWIRE project (www.rewire-project.eu), funded by the

EuropeanCommissionundertheFP7frameworkwithcontract287713.

Conflictofintereststatement

Nocompetingfinancialinterestsexist.

27

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controlintheelderly.Sometheoreticalconsiderations.ZGerontolGeriatr2010;43:229.9. CameirãoMS,BadiaSB,OllerED,VerschureP.Neurorehabilitationusingthevirtualrealitybased

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professionals’attitudes.Stroke2002;33:444.

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3

Design considerations for a theory-driven exergame-based rehabilitation program to improve walking of persons with stroke

WüestS1,vandeLangenbergR1,deBruinED1

1InstituteofHumanMovementSciencesandSport,DepartmentofHealthSciencesandTechnology,ETH

Zurich,Switzerland

EuropeanReviewofAgingandPhysicalActivity2014;11(2):119-129

29

Abstract

Virtualrehabilitationapproachesforpromotingmotorrecoveryhasattractedconsiderableattentionin

recent years. It appears to be a useful tool to provide beneficial and motivational rehabilitation

conditions. Following a stroke, hemiparesis is one of themost disabling impairments and, therefore,

manyaffectedpeopleoftenshowsubstantialdeficitsinwalkingabilities.Hence,oneofthemajorgoals

of stroke rehabilitation is to improve patients' gait characteristics and hence to regain their highest

possible levelofwalkingability.Becauseprevious studies indicatea relationshipbetweenwalkingand

balanceability,thisarticleproposesastrokerehabilitationprogramthattargetsbalanceimpairmentsto

improve walking in stroke survivors. Most currently, available stroke rehabilitation programs lack a

theory-driven,feasibletemplateconsistentwithwidelyacceptedmotorlearningprinciplesandtheories

in rehabilitation. To address this hiatus, we explore the potential of a set of virtual reality games

specificallydevelopedforstrokerehabilitationandorderedaccordingtoanestablishedtwo-dimensional

motorskillclassificationtaxonomy.Wearguethattheensuing‘exergame’-basedrehabilitationprogram

warrantsindividuallytailoredbalanceprogressioninalearningenvironmentthatallowsvariablepractice

andhenceoptimizestherecoveryofwalkingability.

Keywords:Strokerehabilitation,Gentile'staxonomy,Virtualreality,Exergames,Motorlearning

30

3.1Introduction

Virtual reality technique can be combined with targeted exergames development with the aim to

promotemotorrehabilitation.Recently,anumberofresearchershavepointedtothepotentialofvirtual

reality applications in health care [6, 20, 28, 36, 47, 49] and hence sparked the introduction of this

technologywithinrehabilitationmedicine.Theuseofso-called‘exergames’–virtualrealitygamesthat

involve physical exercise – has been proposed as a valuable instrument to encourage participation in

rehabilitationandimprovetheadherencetotherapyprogramsbecauseofengagingtheuser[6,12,47].

For example, a study by Rizzo and Kim [47] demonstrated that virtual reality-based games reduce

patients'drearinessandsimultaneouslyincreasetheirmotivationforrehabilitationpractice.Accordingly,

virtualrealityprovidesthecapacitytosimulatescenariosthatareeffectiveinattractingtheperformers'

attention.Simulatedcircumstancescanbeused toelicita thrillingambience,whereas thepatient can

stillperformmovementandbehaviorsinasafeandcontrolledenvironment.

For best results in rehabilitation, videogames specifically designed for therapy should be used [5].

Becauseconventional videogameswereprimarilydeveloped forentertainmentpurposes [62],mostof

these are not practical for rehabilitation [5]. One hurdle facing the successful use of exergames in

rehabilitation is thatmany off-the-shelf videogames are too complex for use by functionally impaired

personsorelderlypeople[12].Videogamesmustthereforebedevelopedtotakeintoconsiderationthe

cognitiveandphysicallimitations,aswellastheinterestsets,ofthetrainees[12].Todate,however,the

vastmajorityofresearchhasfocusedongamesdevelopedfortheentertainmentmarketwhichfailsto

adaptthegameplayaccordingtopatients'rehabilitationrequirements[43].

FP7 is the short name for the ‘Seventh Framework Programme for Research and Technological

Development’,theEuropeanUnion'smaininstrumentforfundingresearchinEuroperunningfrom2007

to2013.FP7isalsodesignedtorespondtoEurope'semploymentneeds,competitiveness,andqualityof

life[c.f.http://ec.europa.eu/research/fp7/index_en.cfm].Theresearchproject‘RehabilitativeWayoutIn

ResponsivehomeEnvironments’(REWIRE)[45],whichisfundedbyFP7,aimstodevelop,integrate,and

fieldtestaninnovativevirtualreality-basedrehabilitationplatformforpeoplewithstroke.Theplatform

shouldallowpatients,dischargedfromthehospital,tocontinueintensiverehabilitationathomeunder

remote monitoring by the hospital. The main idea is to combine off-the-shelf components (e.g., the

trackingdeviceMicrosoftKinect[30],theforceplateTymo[57])inarobustandreliablewayandrender

asystemthatcanbeusedinthestrokepatients'homes.InthecontextoftheREWIREproject,theneed

hasbeenrecognizedforexergamesspecificallytargetedatwalkingrehabilitation[5].

31

When creating a virtual reality-based stroke treatment approach, the development of suitable

exergamesisundoubtedlyanimportantrequirement.Therehavebeen,todate,somestudiesthatdeal

with the development of videogames adequate for therapy purposes. Based on specific game design

principles,theyintendtoprovideengagingandchallengingtreatmentconditionstoachieveahighlevel

ofmotivation for rehabilitation practicing [1, 6, 7, 24, 33, 42, 58].Moreover, it is important that the

developed exergames are functionally integrated in a well-elaborated therapy program. On the one

hand,therehabilitationprogramshouldbeaimedatappropriaterehabilitationgoals.That is, itshould

be aimed at those goals that are considered to be essential for (andby) stroke victims.On the other

hand,therehabilitationprogramshouldbeconsistentwithestablishedtrainingprinciplestosuccessfully

reach these goals. In this article, we describe how tailored exergames for stroke patients can be

developedbasedonatheoreticalframework.Wewilldiscusskeyexergamedesignandtrainingprogram

contentconsiderations forpatientswithstroke,whichmaybetheoretically linkedto impairedwalking

performanceduetothestrokeevent.

3.2Stroke-inducedmotorimpairmentsandtheirtreatmentapproach

In the United States of America1, there are about 4.8million survivors of stroke of whom about 1.1

million suffer lasting functional disabilities [14]. The specific disabilities caused by stroke vary greatly

dependingonthebrainareathatisdamaged.Hemiparesis–aparalysisthatcharacteristicallyaffectsan

armandlegononesideofthebody–isoneofthemostcommonstroke-inducedimpairments[34]and

often leadstoanumberofnegativewalking-relatedconsequences.Thetypical ‘hemipareticgait’post-

strokeisassociatedwithareducedwalkingvelocity,cadenceandstridelength,withgaitasymmetry,and

withaprolongeddoublesupportandstancephasedurationofboth lowerextremities [15,26,27,44,

60].Itisforthisreasonthatmanystrokevictimsshowmarkeddeficitsinwalkingabilities[50].Thereis

generalagreementthatanassociationexistsbetweenthedegreeofindependentmobilityandqualityof

life [46, 53, 55]. Consequently, a central goal of stroke rehabilitation should be to improve gait

characteristics and to retrain the patient to the highest possible level of walking ability [16, 34]. The

findings demonstrated by Vincent et al. [59] confirmed the importance of enhancing stroke patients'

functionalmobility through rehabilitation. Vincent and colleagues [59] set out to reveal rehabilitation

needsfromtheperspectiveoffourdifferentpartiesinvolvedinthestrokerehabilitationprocess(stroke

patients,caregivers,healthprofessionals,andhealthcaremanagers)soastobetterplanthepost-stroke

treatment service. According to patients' statements – which, in our view, should have high priority

1This doctoral thesis considers the corrigendum to:Design considerations for a theory-driven exergame-basedrehabilitationprogramtoimprovewalkingofpersonswithstroke,EuropeanReviewofAgingandPhysicalActivity2014;11(2):119-12911(2):119-129

32

when designing rehabilitation programs – continued rehabilitation should focus primarily on motor

activities,suchaswalking.Patients'statementsthusfurtherhighlighttheimportanceofgaitrecovery.

Goodbalanceskillsareanimportantdeterminantofwalkingperformanceandimpairedbalanceabilityis

assumedtoberelatedtoadecreasedlocomotorfunction[18,61].Consideringthathemiparesisnotonly

affectsgaitcharacteristics,butalsooftenleadstodiminishedbalanceskills,apost-strokerehabilitation

programtargetingdeficitsinstaticanddynamicbalancemaybeaneffectivewaytorestoreindependent

functionalwalking.Inrecentyears,anotherfactorcontributingtowalkingrecoveryhasbeensuggested:

Several authorsnoted that task-relatedactivities lead to greater improvements inpost-strokewalking

competency thannon-task-relatedpractices [13,41,48]. Specifically, they suggested that intervention

protocolsthatincludeactualwalkingtasksimprovewalkingskillstoagreaterextentthanrehabilitation

programsthatdonot.Additionally,thereisrobustevidenceinthemotorlearningliteraturethatthebest

outcomes in termsof long-termretentionand transferof skillsareachievedwhenprinciplesofmotor

learning are integrated into treatment protocols. In rehabilitation, it is widely accepted that more

practiceisbetterandthatanintensestructuredtherapyprogramwithnumerousrepetitionsofvarious,

challenging tasks supports motor skill acquisition [38]. Specifically, two important elements in our

considerationare themotor learningprinciplesvariablepractice andprogression. Theseprinciplesare

known to positively affect gait rehabilitation and, hence, should be considered in developing a

rehabilitationprogram.

The literature todatehas found thatvariablepractice leads tobetter transferand retentionofmotor

skills than if a constant practice structure is used [22, 23, 31, 38, 51]. Insteadof performingone task

repeatedly and always in the same manner (constant practice), a specific task should be practiced

differentlythroughoutatreatmentsessionbyvaryingtheconditionsofpractice(variablepractice)[38].

Krakauer[31]–inhiscontributionpublishedintheCurrentOpinioninNeurology–statedthatvariable

practice is a fundamental principle in terms of retaining learning over time and that a consistent

agreement inthe literatureexists indicatingthatvariedpractice issuperiortorepetitive identicaltasks

when it comes to motor learning. The principle of progression holds that motor learning and

rehabilitationprogramsbenefit froma continuous adaptationof task difficulty to increasing skill level

[19]. For successful learning, an optimal challenging training situation should be given providing an

appropriate task difficulty level according to individuals' capacities [17]. Furthermore, it can be

hypothesizedthatthetrainingeffectswillbeenhancedwhenthelocomotorpracticegetscombinedwith

direct feedback; e.g., visual feedback. Visual feedback can be used to provide information about a

33

patient'smovementortheresultofamovementandisknowntopromoteposturalcontrolandstability

[2,19,25,52,61].

From the above, it follows that rehabilitation programs for stroke survivors are well-advised to train

balanceandwalkingskillsbymeansofavarietyofbalance-andwalking-specificexercises,thedifficulty

ofwhich isprogressivelyadapted topatients' skill level, in combinationwithdirectvisual feedbackon

performance.

Althoughpreviousstudieshaveemphasizedtheimportanceoftheory-basedpracticeandrehabilitation

[3, 11, 37, 56], there is still a lack of established concepts underlying the practical implementation of

motorskill learningprinciplesandtheories inrehabilitation.Adesirabletemplatewouldbeonethat is

simpleandfeasibleandthatfacilitatesthetask-specific,progressive,andvariabletrainingofbalanceand

walking skills. The motor skill taxonomy proposed by Gentile [21] seems to constitute just such a

templateforrehabilitationprogramsbecauseitprovidesatwo-dimensionalbasisforclassifyingavariety

of motor skills. Based on the above, the aim of this article is to develop and describe a tailored

exergame-basedstrokerehabilitationprogramthatisbasedonatheoreticalframework.

3.3Methods

Fourprevalentclassificationsystemsexistforidentifyingcommoncharacteristicsofmotorskills.Threeof

these categorize motor skills according to one common characteristic of the skill and lead to one-

dimension classification systems. In contrast, Gentile's taxonomy considers two general skill

characteristics and offers, therefore, a broader concept leading to a two-dimensional classification

system of motor skills. To highlight the high potential of Gentile's two-dimensional approach, it is

worthwhile to focus at first on the one-dimensional classification systems and discus some of their

limitations:

A description of these classification systems is given by Magill [35] (pp. 5–16). One one-dimension

classificationsystemdifferentiatesskillsdependingonthesizesoftheprimarymusclegroupsrequiredto

produceanaction(grossmotorskillsvs.finemotorskills).Asecondone-dimensionalsystemconsiders

thespecificityofamovement'sbeginningandendpoints tocategorizemotorskills (continuousmotor

skills vs. discrete motor skills). The third one-dimension classification system makes a distinction

according to the stability of the environmental context in which an action is being performed (open

motor skills vs. closed motor skills) [35, 38]. These one-dimensional classification systems raise the

34

problemthattheyfail tocapturethecomplexityofmanymotorskills [35]byonlyfocusingonasingle

aspectofmotorskills.

3.4Gentile'smotorskilltaxonomy

Gentilepresentedasystematicclassificationsystemtocategorizemotorskillsandmovementaccording

totwogeneraldimensionsofphysicalactions[32].Thefirstdimension,environmentalcontext,refersto

the environmental conditions towhich the performer has to react in order to successfully perform a

task. This dimension is characterized by two indicators: (a) regulatory conditions and (b) intertrial

variability.Theregulatoryconditionsindicaterelevantenvironmentalfeaturesthatconstrainmovement

execution and may either be stationary (stationary regulatory conditions) or moving (in-motion

regulatoryconditions).Withtheindicatorintertrialvariability,Gentile'staxonomydifferentiatesbetween

regulatory conditions that change between trials (intertrial variability) and those that do not (no

intertrialvariability).Theseconddimension,actionfunction, isalsocharacterizedbytwoindicators:(a)

bodyorientationand(b)objectmanipulation.Bodyorientationindicateswhetheranactionrequiresthe

performer to move from one location to another (body transport) or not (body stability). Object

manipulation indicateswhether an object has to be controlled during the action performance (object

manipulation)ornot(noobjectmanipulation).

Through the interaction of the resulting four environmental context characteristics and four action

functioncharacteristics,Gentiledefines16differentmotorskillcategoriesthatprovideacomprehensive

template toclassifymotorskills (Table3.1).The taxonomy isagoodmeansofbecomingawareof the

skill characteristics thatmakeskillsdistinct from,aswell as related to,other skills, and isanexcellent

guideforestablishingpracticeortrainingroutines[35].

AccordingtoGentile,theeasiestskillcategorycanbefoundatthetopleftposition(1A).Movingeither

rightwardordownward in the table renders theskill categorymoredifficult, so that themostdifficult

skillcategorycanbefoundatthebottomrightofthetable(4D).Fortheactionfunctiondimension,this

implies thatbody transport ismoredifficult thanbodystabilityandobjectmanipulationmoredifficult

than no object manipulation. Importantly, it also assumes a hierarchy in the action function

characteristics:skills involvingbodytransportbutnoobjectmanipulationaremoredifficult thanthose

involving objectmanipulations but not body transport. For the environmental context dimension, the

samepatternofprogressionisassumed.

35

Thus, Gentile's taxonomy allows a systematic progression in difficulty of motor tasks and meets the

demandofthemotor learningprincipleprogression.Moreover,eachofthe16categories isassociated

withuniquefeaturesbasedonthetwo-dimensionalapproachand,consequently,thetaxonomyinvolves

taskvariations.Obviously,Gentile'sclassificationsystemisconsistentwiththemotor learningprinciple

variablepractice.

Table3.1:Gentile’staxonomyofmotorskills[35].

There are several reasons for assuming that this taxonomy provides a valuable tool for developing a

theory-based rehabilitation program using virtual reality. Considering the explanations above, it is

evidentthatGentile'staxonomyis inaccordancewiththegenerallyacceptedmotor learningprinciples

progression and variable practice. The taxonomy provides a well-structured framework and the 4×4-

36

table can serve as a useful guide for preparing a systematically coherentmotor learning concept in a

simplemanner. For implementingGentile's taxonomy-based approach, exergamesmight demonstrate

anoptimalopportunityforprovidingbeneficialtreatmentconditions.Ontheonehand,aswereferred

above,there ishighpotential forcreatingamotivatingrehabilitationenvironmentusingvirtualreality.

Ontheotherhand, thetaxonomyseemssuitedforvirtual realityapplicationswheretheenvironment,

task complexity, and other contextual factors related to exercise performance can be manipulated.

Exergameparameterscanbeeasilymodifiedand,thereby,adjustedtothedemandsofthetaxonomy-

includedskillcategories.

3.5 Gentile's taxonomy-based exergames to improve stroke patients' balance and walking

skills

To provide a post-stroke rehabilitation program focused on improved balance skills in standing and

walking inaccordancewithGentile's framework,wedesigned sixbasicexergames.Basedon these six

basicexergames,wecreated16virtualrealityscenarios,eitherbymakinggameparametermodifications

or by substituting another basic game. Each scenario corresponds to one of the 16 skill categories

includedinthetaxonomy(Table3.2).

In accordance with a phased iterative approach suggested by Campbell et al. [8], this paper

demonstratesthetheoreticalphase–thefirststep–whendevelopingandevaluatingcomplexresearch-

basedinterventionsto improvehealth.Thus,asetofsixbasicexergamesappearstobeappropriate in

theresearchprocessofdesigninganexergame-basedstrokerehabilitationprogram.Itkeepsthenumber

ofgamesthathavetobedevelopedmanageableand–withthesamegamebeingimplementedacross

adjacentskillcategories–itrenderssystematicprogressionmorestraightforward.

37

Table3.2:ExergamescenarioscorrespondingtoGentile’sskillcategories.

Below,wewillbrieflydescribethecontentofeachofthe16skillcategories.

1A

Thefirstphaseoftherehabilitationprogramfocusesonthebasicphysicalskillofstandingquietly.Inthis

exergame, the patient is represented as a scarecrow avatar and is required to maintain a cursor

indicatingthebody'scenterofpressure(COP)withinapredefinedmarkedcircleonacomputerscreen

[39].Theexergamefocusesonstancesteadiness(sway)thatdemonstratesarelevantaspectrelatedto

an individual's balance ability [39].Due to hemiparesis after stroke, patients often showan increased

amountofposturalsway[39].

38

1B

Whereas the game Scarecrow described for skill category 1A demands a centered and stable COP

position, this game (called Blueberry collector) uses controlled COP displacements for successful

performance. This exergame targets stroke patients' dynamic stability, because subjects with

hemiparesisoftensufferfromreducedlimitsofstability[39].Thevirtualenvironmentrepresentsafield

ofblueberries,whichhavetobecollectedbyavirtualfarmer.Thefarmer'smovingiscontrolledbythe

patient'sweightshiftingtasksand,inthisway,theblueberriescanbegathered.Becausethepositionof

the berries in the field is fixed and unvarying between the different exergame trials, stationary

regulatory conditions are given and no intertrial variability. To meet the requirement of object

manipulation,avirtualbaskedfilledwithblueberriesisplacedonthefarmer'shead.Inordertoprevent

berriesfromfallingdown,thepatientmustadoptanidealuprightbodyposture.

1C

Previous exercise interventions have shown that stepping exercises indicate an effective treatment

method to improve postural stability and balance [9, 29, 40]. Accordingly, this exergame (called Frog

jumping) requires the control of the COP displacements during stepping movements. The virtual

environmentrepresentsapondwithseveralstonesplacedinit.Bydoingstepsinaspecificdirection,the

patientcancontrolafrogjumpingfromonestonetoanother.Avirtualarrowindicateswhichparticular

stonehas tobe targetedby thepatient. In accordancewith the taxonomy conditions, thepositionof

each stone within the pond is fixed (stationary regulatory conditions) and the order of the targeted

stonesunchangeablefromoneexergametrialtothenext(nointertrialvariability).

1D

According to Gentile's taxonomy, the skill category 1D can be seen as a progression of 1C. Thus, the

game Frog jumping described for 1C can be extended by integrating an object manipulation task.

Specifically, in this game, the virtual frog is wearing a crown and it is the patient's task to perform

steppingtaskswithanuprightbodypositioninordertokeepthevirtualcrowncorrectlypositioned.

2A

The gameBlueberry collector described above is not only adequate for skill category 1B, but also for

category2Abymakingsmalladaptations.Ontheonehand,thevirtualbasketonthefarmer'sheadhas

to be removed to get the condition no object manipulation. On the other hand, because intertrial

variabilityisrequired,thepositionoftheberriesvarieswithinexergametrials.

39

2B

Forskillcategory2B,theexergameBlueberrycollector forcategory2Acanbeextendedwithanobject

manipulation task. Thus, thevirtual farmer isbalancingabasketonhishead suchas in theexergame

describedforskillcategory1B.

2C

We use the game Frog jumping described for category 1C with the only modification of providing a

randomorderoftargetedstones–markedbythearrow–torealizeintertrialvariability.Consequently,

each time when the game has been played, a unique step performance pattern is required by the

patient.

2D

Tomeet the taxonomy requirements in skill category 2D, the game Frog jumping of category 2C can

easilybeadapted.Theonlymodificationthathastobedoneconcernstheneedforobjectmanipulation.

Hence,inthisgame,thefrogiswearingacrownforwhichthepatienthastocontrolhisorherposition

whileplayingthegame.

3A

Forskillcategory3A,wecreatedagamecalledTractordriver.Theexergamepresentsamovingtractor

forwhichthedrivingspeedisdefaultedbythevideogame.Thedirectionofdrivingiscontrolledbythe

patient's weight shifting movements. When playing this exergame, the ability to move the COP in a

standing posture without loss of balance (dynamic stability) is being trained [39]. Specifically, the

purposeofthisgameistoforkuphaybalesthroughdirectingthemovingtractorfromonehaybaleto

another.Thehaybalesarewidelyspreadoverthesoil.Consideringthatthespeedofthemovingtractor

is default and cannot bemanipulated by the patient themselves, in-motion regulatory conditions are

given.There isa fixedpositionofeachhaybaleunchangeable fromoneexergametrial to thenext to

ensurenointertrialvariability.

3B

Inthisexergame(calledFruitcatcher),thepatientisrepresentedasanavatarbalancingafruitbasketon

thehead.Virtual apples are fallingdown froma tree (in-motion regulatory conditions) that shouldbe

caught by the basket. The patient has to perform target-oriented COP shifts to get an optimal avatar

positionand theapplesare falling into thebasket. Thisexergame focusesondynamic stabilitydue to

controlled weight shifting movements to selected targets. For presenting no intertrial variability, the

gameparametersarealwaysthesame,evenwhenthegameisrepeatedlyplayed.

40

3C

According to Gentile's taxonomy, this exergame (called Worm hurdler) requires stepping tasks.

Specifically, the patient represented as an avatar has to overstep a crawling worm coming closer

alternately from the right and the left side (in-motion regulatory conditions). The parameters of the

gameareunchangeableand,thus,nointertrialvariabilityisgiven.

3D

TheexergameWormhurdlerdescribedin3Ccaneasilybemodifiedforskillcategory3D.Byintegratinga

virtualwaterjarthathastobebalancedontheavatar'shead,anobjectmanipulationtaskisintegrated.

Toavoidwaterspillage,thepatienthastoadoptanidealuprightbodyposture.

4A

For skill category4A,weadapted thegameTractordriver described for category3Aby implementing

intertrialvariability.Specifically,toprovidevaryingregulatoryconditions,thehaybalepositionschange

fromoneexergametrialtoanother.

4B

The exergame Fruit catcher described for skill category 3B needed a slight modification to meet the

categoryrequirements for4B. In thisgame, therearenotonly fallingappleswhichhavetobecaught,

but various kinds of fruits. On the one hand, the fruits have different sizes and, on the other hand,

differentfallingspeeds.Obviously,intertrialvariabilityisgiven.

4C

WhenplayingthegameWormhurdlerdesignedforcategory3C,butwithchangingregulatoryconditions

betweentheexergametrials, intertrialvariability isensured.Accordingly, in thisgame, thewormsare

crawlingwithvaryingspeedsandarecomingeitherfromtherightortheleftsideinrandomorder.

4D

Forintegratinganobjectmanipulationtask,theexergameWormhurdlerdescribedforskillcategory4C

canbeadvancedbybalancingavirtualwaterjarontheavatar'shead.Consequently,whileoverstepping

the randomly approaching crawling worms, the patient has to adopt an ideal upright body position

ensuringthatnowaterisspillingout(fromthejar).

3.6Practicalapplicationofthetaxonomy-basedrehabilitationprogramusingexergames

When implementing a therapeutic program to improve stroke victims’ motor skills, therapists must

selectexercisesthataretailoredtothedemandsoftheindividualpatient.Toachieveoptimaloutcomes

41

inrehabilitation,theactivitiesshouldbematchedtoapatient'sfunctionalabilitiesandlimitations.Ina

well-elaborated training plan, the (exercise) tasks which have to be performed should maintain an

optimal challenge for the patient [7, 19].Obviously, for providing a perfectly tuned exercise difficulty

levelatanypointintimethroughouttherehabilitationperiod,modifyingthetherapyplanisanessential

need and an ongoing process.When a patient is making progress, more challenging tasks should be

involved into the rehabilitation program. For selecting functionally appropriate activities during

rehabilitation,wehighlightthepracticalvalueofusingGentile'staxonomy.Basedontheconsideration

thatthetaxonomy-basedskillcategoriespresentastructuregoingfromsimpletocomplexmotortasks,

weprovidea formalprocedure forguidingpatients fromthetop leftof the table to thebottomright.

CloserinspectionofTable3.1revealsthatthetaxonomycanbedividedintosevendifficultylevels.More

specifically,startingfrom1ofthe16skillcategories,acategory-basedprogressionintaskdifficultycan

beachievedeitherthroughahorizontalshifttotherightoraverticalshiftdownward.Accordingly,seven

levels of difficulty can be distinguishedwhich define a progressive increase of complexity in diagonal

direction(Table3.3).

Consideringtheallocationoftheskillcategoriestooneofthesevendifficultylevels,Gentile'staxonomy

offers a simple and easy-to-followway for incorporating an ongoing progression into a rehabilitation

process.Specifically,forselectingappropriateactivitiesthatproviderehabilitationattheoptimallevelof

challenge,weproposethefollowingprocedure:Apatientmayonlymoveuponelevelofdifficultywhen

allskillcategorieswithinthecurrentlevelarecompleted.Forclarification,beginningwithskillcategory

1Aindifficultylevel1,thepatientisrequiredtomovetotheskillcategoriesindifficultylevel2(i.e.,1B

and2A)assoonascategory1Aissuccessfullyperformed.Withinlevel2,patientsandtreatingtherapists

arefreetochoosetheorderofexecutionofthebelongingskillcategories.Onceapatientiscapableto

performboth skill categories1Band2A successfully, thenextdifficulty level3has tobe incorporated

into rehabilitation.Thisprocedure canbe continueduntil thepatient finally achieves skill category4D

and, consequently, the highest level of difficulty (i.e., level 7). In this way, challenging situations are

ensuredatanypointintimeduringrehabilitationandthepatientsareencouragedtoexercisetowards

theirfunctionallimits.Followingtheproceduresuggestedtoguidesomeone'stherapyplan,oneensures

that the selectionof skill categories is constrained.Due to this constraint, a variationof both general

dimensions defined by Gentile's taxonomy will be considered during the rehabilitation process.

Accordingly,theprocedurepreventsaskillcategory-basedprogressiononlyinonedirectionandincludes

themodificationofboththeenvironmentalcontextandtheactionfunctioncharacteristics.

42

Apart from these constraints, this approach also enables a certain degree of self-determination by

therapy-involvedactors.Withinaspecificlevelofdifficulty,theperformanceorderoftheskillcategories

can be freely determined. This autonomy in decision-making increases the potential of tailoring the

rehabilitation process to the demands of each individual patient and leaves freedomof choice to the

treatingtherapistsforthemostadequateexercisesthatshouldcurrentlybetrained.

Table3.3:Gentile’staxonomyofmotorskillsdividedintosevenlevelsofdifficulty(ordereddiagonally).

3.7Limitationsandfuturedirections

UsingGentile'staxonomyfordesigningarehabilitationprogramthattargetsbalanceandwalkingdeficits

of stroke patients, an aspect must be considered critically. According to Gentile's framework, a

horizontal shift to the rightor a vertical shift downwardwithin the taxonomyprovides an increaseof

43

taskcomplexity.However,whenwefocusonamotortasksuchasstandingstillononeleg,apotential

inconsistency in Gentile's approach emerges. Standing still on one leg can be categorized by the

taxonomydimensionbodystabilitythatrepresentslesscomplextasksthanmotorskillsthatrequirebody

transport (e.g.,walking). Inour view,maintaining aone-leg stancepositionneeds goodbalance skills.

Therefore, this activitymight beperceivedby some strokepatients as an advancedmotor taskwhich

challenges them more than a body transport activity. Furthermore, where this theoretical approach

focusedonthe‘generalstrokepatientpopulation’,weareawareofthefactthatdifferentaccompanying

diseases and impairments; e.g., dizzinessormuscleweaknessdue to stroke,may causedifferences in

howpatientsperceive tasks asbeingmoreor lessdifficult. It canbehypothesized that somepatients

have more difficulty maintaining a given posture without loss of balance whereas others experience

performingabodytransporttaskasmoredifficult.Wethink,however,thatthesepotentialdifferences

mayberesolvedbycliniciansthattreatandmonitorpatientsanddecide,togetherwiththepatientsand

accordingtheirskilllevels,howandwhentoprogressthroughthetaxonomy.Itiscleartousthatseveral

pilot studies assessing feasibility and usability in several reference and subpopulations are needed as

necessary next step in our program development process. Feasibility studies are comparative

randomized trials designed to provide preliminary evidence on the clinical efficacy of a drug or

intervention [54]. Usability evaluation is away to ensure that interactive systems are adapted to the

usersandshouldbepartofafundamentalstepintheuser-centereddesignprocess[4].

In thispaper,weelucidate the theoreticalbasis fora theory-driven rehabilitationprogramto improve

stroke sufferers' balance skills and walking capability using exergames. According to the framework

proposed by Campbell et al. [8], investigating relevant theory prior to an exploratory trial is of great

importance.Considering the theoretical knowledgegathered,anoptimal study interventiondesign for

pilot studies can be worked out that focus on the relevance and effectiveness of the rehabilitation

programsuggested.Dependingontheusabilityandfeasibilitytestingresultsobtained,refinementsand

extensionsoftheexergamescanbemadeandthepresentsetofsixbasicexergamesmaybeextended

to amaximumof 16 different exergames.Hence, a comprehensive and practical theory-driven stroke

rehabilitationprogrambasedonGentile'staxonomycanbeachieved.

3.8Conclusion

Withstroke,thechangesinthecentralnervoussystemandlifestylemayimpairanindividual'sabilityto

regainand/ormaintaincertainlevelsofmotorfunctioning.Byusingvirtualreality,wemightbeableto

44

offer continued rehabilitation in an attractive andmeaningful way. Specific targeted exergames have

been designed that aim to minimize stroke-induced walking impairments. Considering the aim of

presenting a well-elaborated training concept with a strong theoretical rationale, in this paper we

demonstrate thatGentile's taxonomypresentsa feasible templateprovidingassistance fordeveloping

and implementing a theory-driven rehabilitation program. The motor skill taxonomy suggested by

Gentile defines two general dimensions and structures a table that consists of 16 different skill

categories(Table3.1).Ontheonehand,basedontheseskillcategories,thetaxonomyprovidesvariable

training scenarios. Thus, a therapy programwhichmeets the demand of themotor learning principle

variable practice can be created. On the other hand, the taxonomy allows a systematic progression

during the rehabilitation process. Accordingly, themotor learning principle of progression is explicitly

considered. Due to the advantages of Gentile's two-dimensional approach, the taxonomy suits our

purposes and was used as underlying framework to build up a post-stroke exergame rehabilitation

program for enhancing balance and walking skills. Based on the literature reviewed here, clinical

approachestomaintainingandimprovingphysicalfunctioningoverlongertimeperiodsinpersonswith

strokemaybecombinedwithnovelexergame-basedapproachesthatsustainphysicalfunctioning.

Authors’contributions

SWperformed literature reviewanddesign considerations and contributed towriting themanuscript.

RvdL performed design considerations and contributed to writing the manuscript. EDdB initiated the

study, assisted in both literature review and design considerations and contributed to writing the

manuscript.Allauthorsreadandapprovedthefinalmanuscript.

The authors declare that the submitted paper, the data, and the results have not been published

anywherebefore.

Acknowledgments

This work was partially supported by the REWIRE project (www.rewire-project.eu), funded by the

EuropeanCommissionundertheFP7frameworkwithcontract287713.

Conflictofintereststatement

Seline Wüest, Rolf van de Langenberg, and Eling D. de Bruin declare that they have no conflict of

interest.

45

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4

Usability and effects of an exergame-based balance training program

WüestS1,BorgheseNA2,PirovanoM2,MainettiR2,vandeLangenbergR1,deBruinED1,3,4

1InstituteofHumanMovementSciencesandSport,DepartmentofHealthSciencesandTechnology,ETH

Zurich,Switzerland

2DepartmentofComputerScience,UniversityofMilan,Italy

3DepartmentofEpidemiology,CAPHRISchoolforPublicHealthandPrimaryCareand4Centrefor

EvidenceBasedPhysiotherapy,MaastrichtUniversity,Netherlands

GamesforHealthJournal2014;3(2):106-114

49

Abstract

Background:Post-strokerecoverybenefitsfromstructured,intense,challenging,andrepetitivetherapy.

Exergames have emerged as promising to achieve sustained therapy practice and patientmotivation.

Thisstudyassessedtheusabilityandeffectsofexergamesonbalanceandgait.

SubjectsandMethods:Sixteenelderlyparticipantswereprovidedwiththestudyinterventionbasedon

fivenewlydevelopedexergames.Theparticipantswererequiredtoattend36trainingsessions; lasting

for20minuteseach.Adherence,attritionandacceptancewereassessedtogetherwith(1)BergBalance

Scale,(2)7-mTimedUpandGo,(3)ShortPhysicalPerformanceBattery,(4)forceplatformstancetests,

and(5)gaitanalysis.

Results: Thirteen participants completed the study (18.8 percent attrition), without missing a single

trainingsession(100percentadherence).Participantsshowedhighacceptanceoftheintervention.Only

minoradaptationsintheprogramwereneededbasedontheusers’feedback.Nochangesincenterof

pressure area during quiet stance on both stable and unstable surfaces and no changes of walking

parametersweredetected.ScoresfortheBergBalanceScale(p=0.007;r=0.51),the7-mTimedUpand

Go (p = 0.002; r = 0.56), and the Short Physical Performance Battery (p = 0.013; r = 0.48) increased

significantlywithmoderatetolargeeffectsizes.

Conclusion: Participants evaluated the usability of the virtual reality training intervention positively.

Resultsindicatethattheinterventionimprovesgait-andbalance-relatedphysicalperformancemeasures

inuntrainedelderly. Thepresent resultswarrant a clinical explorative study investigating theusability

andeffectivenessoftheexergame-basedprograminstrokepatients.

50

4.1Introduction

Acute stroke rehabilitation servicesare limited–primarilybecauseof cost constraints [1]–andmany

individuals return home with residual gait impairment [2]. The decision to discharge patients from

furthertherapyisoftenjustifiedwitha‘plateau’inmotorrecovery[3].However,furtherfunctionalgains

afteracuterehabilitationarepossible,eveninthechronicstage[1,4].

Following a stroke, approximately 80 percent of patients experience hemiparesis accompanied by

considerable walking deficits [5]. The typical ‘hemiplegic gait’ post-stroke is associated with several

negativeconsequences(e.g.,gaitasymmetry,reducedwalkingvelocity,cadence,andstridelength)[5-9].

Sixmonthspost-stroke,one-thirdofelderlystrokesurvivorsarenotabletowalkindependently[10].

An intense, structured therapy program offering numerous repetitions of various, challenging tasks

improves motor skills [11]. For best recovery results, a rehabilitation program should be conducted

regularly over an extended period of time.When patients find a treatment program enjoyable, their

willingnesstokeepat it is increased.Ahighlevelofmotivationshouldleadtohighadherenceandlow

attritionandhencepositivelyaffecttreatmentoutcomes[12].

Virtual reality applications in health care have recently received considerable attention. Virtual reality

canbeusedtoprovideengagingscenariosandimproveadherencetotherapy[13-17].Videogamesare

most practical and effective in rehabilitation when they have been specifically designed for therapy

purposes [18-20].Given the importanceof gait recoverypost-stroke, games shouldbeaimed towards

walkingrecovery.Anadditionaladvantageofvideogame-basedprogramsisthattheycanbeperformed

independentlyathomewithminimalequipment[16].

The researchproject ‘RehabilitativeWayout InResponsivehomeEnvironments’ (REWIRE) [21], funded

by FP7, created such a rehabilitation program based on exergames. Exergames are defined as “any

number of types of video games/multimedia interactions that require the game player to physically

moveinordertoplay”[22].FiveexergameshavebeendevelopedinthecontextoftheREWIREproject–

bygamedevelopersincollaborationwithhumanmovementscientistsandrehabilitationspecialists.The

processforgamedevelopmentwithinatheoreticalframeworkhasbeendescribedelsewhere[23].The

underlying exercises – specifically targeting balance and walking recovery – were designed to be

performedindependentlyathomeandremotelymonitoredbyhealthcareprofessionals.Moreover,the

rehabilitationprogramexplicitlyconsideredvariablepracticeandindividuallytailoredprogression,hence

keepingparticipantsengagedandappropriatelychallenged[18,23,24].

51

InaccordancewiththephasediterativeapproachsuggestedbyCampbelletal.[25],thisarticleaimsto

evaluate(1)theusabilityoftherehabilitationprogramintermsofacceptance,adherence,andattrition

and(2)theeffectoftheprogramonmeasuresofbalanceandgaitinuntrainedhealthyelderly.

4.2Subjectsandmethods

Studydesign

Weassessedusabilitybymeansofauser-centeredinteractiondesign.TheETHZurichEthicsCommittee

grantedethicalapproval (protocolnumberEK2013-N-12).Allparticipantswere fully informedprior to

participationandsignedaconsentform.

Participants

Usabilityandeffectswereassessedinanuntrainedelderlyconveniencesample,inwhichsomebalance

andgait impairmentscanbeassumed[26-30].SixteenparticipantswererecruitedinthecityofZurich,

Switzerland, through contact persons of different institutions. Participantswere included if they lived

independently,wereolderthan64yearsofage,wereabletowalk independently for20m,andhada

Mini-MentalStateExaminationscoreofatleast22.Excludedwereindividualswith(1)acuteorunstable

chronic diseases, (2) rapidly progressingor terminal illnesses, (3)Alzheimer’s diseaseor dementia, (4)

otherseverehealthproblems,and/or(5)arecentheadinjury.

Intervention

The intervention program consisted of exergame-based balance training performed while standing

directlyonaforceplatform(TymoplatebyTyromotion,Graz,Austria)[31]oronacompliantfoammat

placedontopofthisplatform.Theinterventionwasperformedthreetimesperweekforaperiodof12

weeks for a total of 36 sessions. Each one-on-one sessionwas partitioned in three parts: 10minutes

training,10minutesbreak,and10minutes training.Allparticipantswereexpected tocompleteall36

sessions while being monitored by an instructor, who systematically observed them throughout the

intervention.Participantswereencouragedto‘thinkaloud’whileoperatingthesoftwareandplayingthe

exergames.Accordingly,anyexpressedcommentsfromtheparticipantsrelatedtotheirdemandswere

documentedbytheinstructorinwritingtoidentifybothproblemareasandwhatpeoplelike.Theaimof

thisprocedurewastoassessstrengthsandweaknessesoftheexergame-basedtrainingprogramonline

52

inarealisticsetting.Consequently,basedonparticipants’feedback,desiredexergameadaptationscould

becarriedout.

Exergames

Asetof fiveexergames– fourof themwithdifferent levelsofdifficulty (Table4.1givesdetails)–was

used for the intervention. In each exergame, a therapist avatar provided real-time feedback. The

exergamesaimedtotrainquietstance (‘Scarecrow’ [Figure4.1]),mediolateralweightshifting (‘Tractor

driver’[Figure4.2]and‘Fruitcatcher’[Figure4.3]),mediolateralweightshiftingcombinedwithsingleleg

stance (‘Wormhurdler’ [Figure 4.4]), andmediolateralweight shifting combinedwith anteroposterior

weightshifting(‘Mixsoup’[Figure4.5]).Adetaileddescriptionofthegamescanbefoundelsewhere[18,

23,24].

Table4.1:Exergamedifficultylevels.

Scarecrow Tractordriver Fruitcatcher Wormhurdler Mixsoup

Nodifficultyleveladaptation

Difficultyleveladaptation:

speedofthemovingtractor

Difficultyleveladaptation:

fruitfallingfrequency&fruitfallingrange

Difficultyleveladaptation:speedofthecrawlingworm

Difficultyleveladaptation:

lifespanofthebubbles

Primaryoutcomes

Acceptance of the training technology. An abridged version [32] of the technology acceptancemodel

(TAM)questionnaireevaluatedparticipants’perceivedacceptanceoftheinterventionpost-training[33-

35](Figure4.6).

Responseswere recorded using a 7-point Likert scale ranging from ‘strongly disagree’ (rated as 1) to

‘stronglyagree’(ratedas7).

Attrition and adherence. For attrition, the number of participants lost during the intervention was

recorded.Foradherence,participants’engagementwiththeinterventionwasassessed.Adherencewas

calculatedasthenumberofcompletedtrainingsessionsasapercentageofthemaximalpossibletraining

sessions(i.e.,36).

53

Figure4.1:Screenshotoftheexergame‘Scarecrow’. Figure4.2:Screenshotoftheexergame‘Tractordriver’.

Figure4.3:Screenshotoftheexergame‘Fruitcatcher’. Figure4.4:Screenshotoftheexergame‘Wormhurdler’.

Figure4.5:Screenshotoftheexergame‘Mixsoup’.

54

Figure4.6:ResearchmodelbyMasrom[32].

Secondaryoutcomes

BergBalanceScale.BalanceabilitywhileperformingfunctionaltaskswasassessedwiththeBergBalance

Scale.Thistestconsistsof14mobilitytasksthatsimulatecommondailylifeactivitiesandisreliableand

valid in geriatrics [36]. By using a 5-point scale, ranging from0 (most impaired balance) to 4 (normal

balance), a person’s functional capability can be defined for each test. The possible cumulative score

rangesfrom0to56points.

TimedUpandGo.TheTimedUpandGo[37,38]requiresparticipantstostandupfromasittingposition,

walkfor3m,turn180°,walkback3m,andturntositdownagain.Weusedanextendedtestversion

witha7-mwalkingdistance[39].Thetestwasrepeatedthreetimeswith30-secondbreaksinbetween,

andthetotaltimetocompleteeachtrialwasmeasured.Theaveragetimewasusedforfurtheranalysis.

Forceplatform.Tomeasureposturalbalancecontrol,participantsstoodquietlyonaKistler(Winterthur,

Switzerland)forceplate(type9286B)undertwodifferenttestconditions:(1)onastablesurfaceand(2)

onanunstablesurface(foammat).Verticalgroundreactionforceswerecollectedatafrequencyof1000

Hz. Inbothconditions,participantswere instructedto focusonaredcrossdisplayedateye levelona

whitewallatadistanceof30cm.Ineachcondition,three20-secondtrialswereperformedwitha30-

secondbreakinbetween.Foreachtrial,centerofpressure(COP)areawasquantifiedastheareaofthe

smallest ellipse containing95%ofCOPdatapoints.MeanCOPareawas computed foreach condition

andusedforstatisticalanalysis.

55

Short Physical Performance Battery. The Short Physical Performance Battery, composed of a balance

test,a3-mwalkingtest,andafive-chair-risestest,resulted inscoresbetween0(notabletocomplete

the task) and 4 (good function) points per test. The sum of these scores represents the total Short

PhysicalPerformanceBatteryscore.Ahigherscoreindicatesbetterlowerextremityfunction[40-42].

Gait analysis. Spatiotemporal gait parameterswere assessedwith theGAITRite® system (CIR Systems,

Havertown,PA)consistingofanelectronicwalkwaywithgaitanalysis software.Theactiveareaof the

walkway(i.e.,theareaequippedwithpressuresensors)measures7.3m.Toeliminateaccelerationand

deceleration effects on calculated gait parameters, the walkway contains an additional 2.5 m at the

beginningandendof theactivearea.Participantswere towalkover theelectronicwalkwayata self-

selected comfortable walking speed. Three successful trials were collected, and the mean values of

velocity (cm/second), cadence (steps/minute), step time (seconds), step length (cm), and swing time

symmetry(ratio)werecalculated.Gaitsymmetrywascalculatedfromthefollowingratio[43]:

Symmetryratio=swingtimerightside/swingtimeleftside

Statisticalanalysis

All statistical analyses were performed using SPSS version 21.0 software (SPSS Inc., Chicago, IL).

Secondaryoutcomeswereonlycalculatedandanalyzedforparticipantswhocompletedtheintervention

as per protocol. AWilcoxon signed-rank testwas used to compare pre- and post-test results. Results

were deemed statistically significant at a p-value of ≤0.05. Effect size (r) was calculated as r = Z/√N,

where Z represents the approximation of the observed difference in terms of the standard normal

distribution and N is the total number of observations. Regarding effect size magnitude, r = 0.1 is

consideredasmall,r=0.3amedium,andr=0.5alargeeffect[44].

4.3Results

Primaryoutcomes

Sixteenparticipantswereenrolledinthestudy,13ofwhomreceivedthefullallocatedtrainingprogram

(Figure4.7). Twoparticipantsdroppedoutbecauseof injuries sustainedoutside the training, andone

discontinued because of self-reported lack of time. All reasons were unrelated to the content of the

training.

56

Figure4.7:Studyflowchart.BBS,BergBalanceScale;MMSE,Mini-MentalStateExamination;n,samplesize;SPPB,ShortPhysicalPerformanceBattery;TAM,technologyacceptancemodel;TUG,TimedUpandGo.

Table 4.2 presents completers’ demographics and clinical characteristics. Adherencewas 100percent.

Noneof the13participantssufferedanyadverseeventsduring the intervention.Theexergameswere

seen as easy to use and useful. The participants expressed a positive attitude toward using the

exergamesaswellasanintentiontocontinueusingthegames(Table4.3).

57

Table4.2:Completers’baselinecharacteristics.

Characteristics Value

Numberofparticipants 13

Age(years) 76.5±5.4(65-85)

Sex(female/male) 10/3

Height(cm) 163.6±8.5(152-177)

Weight(kg) 71.6±9.7(57.4-90.5)

MMSE(points)a 28.9±1.6(25-30)

Education

Collegeeducatedorhigher 2

Inasittingpositionpastprofession 5

Healthstatus

≥2self-reportedchronicdiseases 8

Feelpaindaily 4

Estimatedexcellent/goodhealthstatus 10

Estimatedexcellent/goodbalanceability 7

Dataarenumberofsubjectsormean±standarddeviation(range)valuesasindicated.aTheminimumscorewas0,andthemaximumscorewas30(ahigherscoreindicatesbettercognitivefunctioning).MMSE,Mini-MentalStateExamination.

Table4.3presentstheTAMitemsthatwereevaluatedpost-intervention.

During the intervention, participants reported some minor problems with using the games and

progressing through the exercises. In response, the exergames were adapted online (Table 4.4 gives

details)andsubsequentlyre-assessedforusability.

58

Table4.3:Evaluatedtechnologyacceptancemodelquestionnaireitems.

Item Score

PerceivedEaseofUse 5.9±1.7(1-7)

PerceivedUsefulness 6.4±1.0(4-7)

AttitudeTowardUsing 6.5±1.1(2-7)

BehavioralIntentiontoUse 6.0±1.3(3-7)

Dataaremean±standarddeviation(range)values.

Table4.4:Descriptionoftheonlineexergameadaptationsperformed.

Scarecrow Tractordriver Fruitcatcher Wormhurdler Mixsoup

Addedtwodifficultylevelstooriginalthree

Addedtwodifficultylevelstooriginalthree

Addedtwodifficultylevelstooriginalthree

Addedtwodifficultylevelstooriginalthree

Addedtwodifficultylevelstooriginalthree

Improvedconsistencyofstatementsandscoresprovidedbyvirtualtherapist

Improvedconsistencyofstatementsandscoresprovidedbyvirtualtherapist

Improvedconsistencyofstatementsandscoresprovidedbyvirtualtherapist

Improvedconsistencyofstatementsandscoresprovidedbyvirtualtherapist

Improvedconsistencyofstatementsandscoresprovidedbyvirtualtherapist

Addedpreviouslyabsentobstacles

Increasedwormsizeandhencevisibility

Secondaryoutcomes

The results of the pre-and post-comparisons are presented in Table 4.5. Significant improvements in

BergBalance Scale, TimedUpandGo, and Short Physical PerformanceBattery scoreswereobserved.

Separate analyses of each of the three Short Physical Performance Battery components (standing

balance, repeated chair rises, and gait speed) revealed that only standing balance changed. No

significantchangesweredetectedin(1)COPareaduringquietstanceand(2)anyofthegaitparameters

(allp-values>0.1).

59

Table4.5:Participants’baselineandpost-interventionphysicaloutcomemeasures.

Mean±standarddeviation

Baseline Post-intervention pwithin r Z

BBS(points) 51.7±3.3 54.8±1.4 0.007a 0.51b 2.590

7-mTUG(seconds) 19.8±2.8 17.5±2.4 0.002a 0.56b 2.830

COParea(mm2)

Stablesurface 2.47±1.64 4.43±4.17 0.191 0.27 1.363

Unstablesurface 10.42±7.73 17.69±18.54 0.414 0.17 0.874

SPPB(points)

Total 9.9±1.0 11.2±0.8 0.013a 0.48c 2.436

Balance 3.1±0.9 4.0±0.0 0.008a 0.51b 2.585

Chairrises 3.2±0.8 3.4±0.7 0.375 0.26 1.342

Gaitspeed 3.7±0.5 3.8±0.6 1.000 0.07 0.378

Gaitanalysis

Velocity(cm/second) 122.4±17.3 128.4±21.4 0.497 0.14 0.734

Cadence(steps/minute) 115.2±8.7 119.1±9.3 0.244 0.24 1.223

Steptime(seconds) 0.52±0.04 0.51±0.04 0.273 0.23 1.153

Steplength(cm) 63.6±6.0 64.4±6.9 0.542 0.13 0.664

Swingtimesymmetry(ratio) 0.99±0.03 1.00±0.04 0.127 0.31c 1.572aSignificantwithin-groupdifferencespre-post(pwithin≤0.05)calculatedwithWilcoxonsigned-ranktest.Foreffectsizer,r=0.1indicatesasmalleffect,cr=0.3indicatesamediumeffect,andbr=0.5indicatesalargeeffect.BBS,BergBalanceScale;COP,centerofpressure;pwithin,p-valueforwithin-groupcomparisons;SPPB,ShortPhysicalPerformanceBattery;TUG,TimedUpandGo;Z,approximationoftheobserveddifferenceintermsofthestandardnormaldistribution.

60

4.4Discussion

This study assessed – in untrained elderly – (1) the usability of the program in terms of acceptance,

adherence,andattritionand(2)theeffectoftheprogramonbalanceandgait.Thefindingsrevealeda

high levelofacceptancewithconcomitanthighadherencerates.HighscoresforeachofthefourTAM

itemswerefound.Onaverage,participantsfoundtheexergameseasytouse,clear,andunderstandable

without requiring much mental effort to operate. Perceived Usefulness results showed that the

exergames were perceived as a useful means to increase training effectiveness, productivity, and

performance.Moreover,therewasabroadconsensusintermsofAttitudeTowardUsing:Allparticipants

expressed a positive attitude towards the program. In addition, Behavioral Intention to Use results

showedthatparticipantslikedtheideaofcontinuingtheiruseofexergamesonaregularbasis.Thehigh

acceptancerateobtainedinthecurrentstudyseemsatoddswithapreviousstudybyLaveretal. [45]

thatrevealedskepticismabouttheuseofcommerciallyavailablevideogamesingeriatricrehabilitation.

Alikelyexplanationmaybefoundingamedesign:WhereLaveretal.[45]usedanoff-the-shelfsystem

without patient-specific adaptations, the exergames used in this studywere specifically designed and

developed for rehabilitationandwereadapted to thecognitiveandphysical limitationsof functionally

impaired persons or elderly. This explanation is in line with Cameirão et al. [46], who found high

acceptanceofagamingsystemspecificallydesignedtotreatpost-strokemotordeficits,andwithLewis

etal. [4],whodemonstratedpositive results fornewlydevelopedexergamesaimedto improvestroke

patients’armfunction.Ourfindingsalsocorroboratethehighacceptanceratesofspecificallydesigned

exergamesfoundbyBacklundetal.[47].

Thirteenofthe16participants(81percent)completedthefullallocatedtrainingprogramandattended

theretestingassessments.Consideringthemedianrateforattrition infallspreventioninterventions in

communitysettingsforclinicaltrials[48],a10percentattritionratecanbedeemedacceptable. Inour

study, we achieved a slightly higher rate. It should be noted, however, that the reasons for

discontinuationoftheinterventionwereunrelatedtotheintervention.Incontrasttothesomewhatlow

attrition rate,adherencewas100percentacross the36 training sessions.Thisperfectadherence is in

linewiththehighacceptancerevealedbytheTAMsurvey.Thehighadherenceandacceptanceratesin

thepresentstudymayberelatedtotheonlineadaptationsofthetrainingintervention:Theexergames

weresubjectedtoseveralonlineadaptationsbasedonparticipants’feedbackduringthetrainingperiod,

whichmighthavepositivelyimpactedbothusabilityandeffectiveness.

61

Weexpectedtheexergamesto improveparticipants’balanceandgait.The interventionhadapositive

effectonclinicalmeasuresofbalance.ThisisinlinewithastudybyLaietal.[49]thatreportedsimilar

results through a 6-week interactive videogame-based intervention. Although body sway during quiet

stancedidnotchangesignificantly,bothstandingonastableandunstablesurfaceyieldedlargeraverage

COPareas in thepost-testcomparedwith thepre-test.Given thatbetterbalance isusuallyassociated

withsmallerCOPareas,thistrendissurprising.Althoughspeculative, itmightnonethelessconstitutea

positive interventioneffect:Note that fourof the fiveexergames trainedeffectivecontrol rather than

minimizationofCOPmovement.Giventhat–tobeprecise–posturalstabilitylikewiserequireseffective

controlofCOP(inordertominimizecenterofmassmovement)ratherthanitsminimization,COPmight

notbe thebest indicatorofpostural stability,particularly in thepresent study [50].Measurementsof

center of mass movements (e.g., during walking) would have given a better insight into the actual

participants’dynamicposturalbalancecontrol.

The absence of gait-related effects in this study constitutes a confirmation of results by Szturmet al.

[51],whoalso examinedanexergame-based interventionwith goal-directedweight shifting tasks and

foundnosignificantimprovementinspatiotemporalgaitparameters.Hence,exerciseswithastationary

baseofsupportdonotseemtopresentthemosteffectivewaytoimprovewalkinginuntrainedelderly.

However, the absence of significant effects on gaitmight also be related to the lowpower of testing

togetherwiththeratherhighlevelofwalkingfunctioninoursample.Effectsizesweremediumorclose

tomediumand–withapreferredgaitspeedbetween1.0and1.4m/second–ourparticipantsshouldbe

classified as normal walkers [52]. A logical next step would therefore be to apply the present

intervention to community-dwelling chronic stroke populations that exhibit mildly abnormal (0.6–1.0

m/second)orseriouslyabnormalgaitspeed(below0.6m/second)andre-assessinterventioneffectson

gait in this actual target population [52]. Given that gait speed is an important factor related to

communitywalking in stroke patients,which in turn is strongly determined by balance [53], it seems

likelythatourexergames–whichexplicitlytargetthisskill–willimprovewalkinginchronicpatients.

Futurework

Weperformedan‘aprioripoweranalysis’todeterminetheminimumsamplesizeforsuchafuturetrial

[54].Specifically,weassessedtherequirementsforarandomizedcontrolledstudywithanexperimental

group(receivingexergame-basedtherapyandusualstrokerehabilitation)andacontrolgroup(receiving

usualstrokerehabilitationonly).Assuminganeffectsizeofr=0.30(basedonourobservedvalueforgait

symmetry),acceptabletypeIandIIerrorprobabilities(0.05and0.20,respectively)maybeobtainedwith

62

aminimumsampleof12participantspergroupforatwo-grouppre-andpost-testdesign.Toaccountfor

attrition,initialsamplesizeshouldbeincreasedto15participantspergroup.

Limitations

Some limitations of this study shouldbediscussed. First, this study featured a rather small sampleof

healthy untrained elderly, which resulted in limited statistical power for gait analysis. The validity of

using elderly persons to test the usabilitymay be questioned. However, (1) the primary focus of this

studywasonusability,whereasampleof fiveparticipants issufficient fordetecting80percentofthe

usability problems [55], and (2) untrained elderly normally show both balance and gait impairments,

whichshouldrenderthemanadequatepopulationforassessingeffectivenessaswell.Second,thestudy

may suffer from volunteer bias: It can be hypothesized that our volunteer participants were more

interested in technology than the average elderly, whichmight explain in part their positive attitude

towardtheintervention.Boththeselimitationswouldnotapplyinacontrolledtrialwithstrokepatients,

which–incombinationwiththepromisingresultsofthepresentstudy–highlightstheneedforsucha

trial.Athirdlimitationconcernsthegenderdistributioninoursample,withwomenoutnumberingmen.

However, sexdisparity in strokeprevalencepersists,withwomenbeingmoreaffected thenmen [56].

Thismakesitimportanttoespeciallytestacceptanceandfeasibilityinwomen.

4.5Conclusion

Small-scale interventions focusingonusability representan importantstagewhendevelopingcomplex

theory-based interventions to improve health [25]. Usability studies provide invaluable results for

informationtechnologydevelopersandrehabilitationspecialistsusinginnovativesystemsandmightbe

highlyrelevantforfurtheringthedevelopmentofnewemergingvirtualreality-basedrehabilitation.Our

resultscorroboratepreviousfindingsinshowingthatvirtualtrainingapproachesforperformingbalance

traininghavegreatpotential.Specifically,thisstudydemonstratesthattheexergame-basedintervention

wasperceivedasusableandhadapositiveeffectonbothstandingbalanceanddailylifetasks.

63

Authors’contributions

SWcontributedtotheconceptionofthework,theacquisition,analysisandinterpretationofdata,and

writing the manuscript. NAB, MP, and RM contributed to the development of the software and

exergames.RvdLassistedintheacquisitionofdataandcontributedtotheanalysisandinterpretationof

data and towriting themanuscript. EDdB initiated the study, assisted in the acquisition of data, and

contributedtowritingthemanuscript.Allauthorsreadandapprovedthefinalmanuscript.

Acknowledgments

This work was partially supported by the REWIRE project (www.rewire-project.eu), funded by the

EuropeanCommissionundertheFP7frameworkwithcontract287713.

Conflictofintereststatement

Nocompetingfinancialinterestsexist.

64

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5

Reliability and validity of the inertial sensor-based Timed Up and Go test in post-stroke individuals

WüestS1,MasséF2,AminianK2,GonzenbachR3,deBruinED1

1InstituteofHumanMovementSciencesandSport,DepartmentofHealthSciencesandTechnology,ETH

Zurich,Switzerland

2LaboratoryofMovementAnalysisandMeasurement,EcolePolytechniqueFédéraledeLausanne,

Switzerland

3DepartmentofNeurology,UniversityHospitalZurich,Switzerland

JournalofRehabilitationResearch&Development2015,inpress

68

Abstract

The instrumented Timed Up and Go test (iTUG) has the potential for playing an important role in

providing clinically useful information regarding an individuals’ balance and mobility that cannot be

derivedfromtheoriginalsingle-outcomeTUGprotocol.Thepurposeofthisstudywastodeterminethe

reliabilityandvalidityoftheiTUGusingbody-fixedinertialsensorsinpeopleaffectedbystroke.Fortest-

retest reliability analysis, 14 individualswith stroke and 25 healthy elderlywere assessed. For validity

analysis,anage-matchedcomparisonof12strokepatientsand12healthycontrolswasperformed.Out

ofthe14computediTUGmetrics,themajorityshowedexcellenttest-retestreliabilityexpressedbyhigh

intraclass correlation coefficients (ICCs range 0.431-0.994) together with low standard error of

measurement (SEM and SEM%, respectively) and smallest detectable difference (SDD and SDD%,

respectively) values. Bland and Altman plots demonstrated good agreement between two repeated

measurements.Significantdifferencesbetweenstrokepatientsandhealthycontrolswerefoundinnine

of 14 iTUG parameters analyzed. Consequently, these results warrant the future application of the

inertial sensor-based iTUGtest for theassessmentofphysicaldeficitspost-stroke in longitudinal study

designs.

Keywords:Test-retestreliability,Validity, InstrumentedTimedUpandGotest,Stroke, Inertialsensors,

Motorfunctiontest,Rehabilitation

69

5.1Introduction

After a stroke, many individuals suffer from hemiparesis which often leads to an impaired walking

patternwithalteredgaitcharacteristics[1-7].Specifically,thehemiplegicgaitistypicallyassociatedwith

a reduced gait speed [1-3, 5, 8], cadence [2, 5, 8], stride length [2, 8] and an increased left-right

asymmetryduringwalking[1,3,9]whencomparedtohealthy,age-matchedcontrols.Furthermore,itis

often characterized by an increased stance phase duration [2]. Hemiparesis not only leads to gait

impairments,butmayalsoaffectbalanceandpostural transfers (i.e.,changingposition fromsitting to

standing, and vice versa) further impeding the patients’ mobility and independence [6, 10-12]. It is

thereforea central goalof stroke rehabilitation to improve thepatient’s independenceand functional

capacitybyimprovinghisorhermobility[13].

TheTimedUpandGotest(TUG)isoftenusedtoevaluatebalanceandmobilityinstrokepatients[14],

withgoodreliabilityandvalidity[15-17].TheTUGrequiresapersontorisefromachair,walkadistance

of3metersataself-pacedcomfortablespeed,turnaround,andreturntothechairtositdownagain.

Thetotaltimeforcompletionisrecordedandusedasmeasureofmobility.However,althoughtheTUG

is commonly used to evaluate mobility post-stroke, it has some drawbacks. First, it only uses the

outcomeparameter ‘time’ and fails todetect otherbalance- andmobility-relatedparameters [18-19].

Second, although it consists of a number of consecutive tasks it does not allow analyzing these

separately[18-19].Recently,severalresearchersinstrumentedtheTUGinanefforttoovercomesomeof

thedrawbacks.Forexample,Vernonetal.[20]usedaMicrosoftKinectcamera-basedTUGmethodfor

analyzing the specific subcomponents of the test. Furthermore, Zampieri et al. [19] revealed the

potentialbenefitofaninstrumentedTUG(iTUG)systemusingwearableinertialsensorswhileassessing

individualswithParkinson’sdisease(PD).While10ofthe21gaitandposturaltransitionparametersthat

were identifiablewith the iTUG showed significant differences between PD and healthy controls, the

total test performance time was not diverging. Obviously, the iTUG seemed to exhibit a greater

sensitivitythantheconventionalTUGtestintermsofmobilitydeficitdetectioninPD[18].

Therecentuseofbody-fixedsensorssuggeststhattheycouldserveasatoolforanalyzingmeasuresof

physicalfunctioningofpatients[21-22].Itcouldpotentiallydelivermoredetailedandclinicallyrelevant

informationonastrokepatient’sgaitandmobility than theconventionalTUG,whichonly reports the

time to complete the task. To the best of our knowledge, no study exists applying an inertial sensor-

basediTUGsysteminpeopleaffectedbystroke.Tobeclinicallyuseful,anassessmentproceduremust

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have a small measurement error to detect a real change and must be able to distinguish between

subpopulations;e.g.,strokepatientsinvariousstagesandhealthycontrols.Atest-retestdifferenceina

patientwithavaluesmallerthanthestandarderrorofthemeasurement(SEM)islikelytobetheresult

of‘measurementnoise’andisunlikelytobedetectedreliablyinpractice;adifferencegreaterthanthe

smallest real difference is highly likely (with 95% confidence) to be a real difference [23-25]. Another

exampleof these statistics is the smallestdetectabledifference (SDD) [24,26].Thepresent studywas

conducted toassess the reliabilityandvalidityof inertial sensor-based iTUGmetrics in strokepatients

andage-matchedhealthycontrolelderly.

5.2Methods

Studydesign

The study was designed as an observational study where all participants were tested by the same

observer.EthicalapprovalforthisstudywasgrantedbythelocalETHZurichEthicsCommittee(protocol

numberEK2012-N-32)andthecantonalEthicsCommitteeoftheCantonofSt.Gallen(protocolnumber

EKSG12/002/1B).Priortoparticipation,allparticipantswerefullyinformedaboutthecompleteresearch

protocolandrequestedtosignaconsentform.

Participants

Participants were recruited on a voluntary basis through researchers from the Institute of Human

MovementSciencesandSportatETHZurich, Switzerland, andby contactingphysiciansand therapists

fromtheRehabilitationCenterValens,Switzerland.Thereweretwogroupsofparticipants:1)fourteen

patients at any stage after ischemic or hemorrhagic stroke aged over 18 years. Participants were

excluded from the study if any known comorbid disabilities other than stroke were present (e.g.,

musculoskeletal illness,cardiovasculardisordersorotherneurologicdiseases)thatmighthaveaffected

performanceinthetestprocedures;2)twenty-fivehealthybyself-reportcontrolparticipantsagedover

65 years who had no history of neurological, cardiovascular or musculoskeletal pathologies. To be

eligibleforthestudy,individualshadtobeabletowalkunassistedforatleast15meters.Theuseofone

crutchforwalkingwasacceptedfor inclusion. Individualswhowerenotabletogive informedconsent

wereexcluded.

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Apparatus

Intotal,eightbody-fixeddevices(Physilog®,GaitUp,CH)wereplacedonparticipants’body:thesensor

configurationdescribed inthe iTUGprocedurebySalarianetal. [18]–oneoneachwrist,oneoneach

shank,andoneonthetrunk–wascomplementedwithonedeviceoneachfootandoneontheback(L3)

for further analysis. The sensor located on patient’s back was taped using hypoallergenic breathable

straps to ensure firm attachment to the skin. Every other sensor devices were firmly affixed to the

patientusingelasticstraps.

The devices recorded to an on-boardmemory card the signals from a calibrated inertial sensor (3D-

accelerometer and 3D-gyroscope) at 500 Hz [27]. Before any processing, the inertial signals, sampled

synchronouslyacrossdevices,wereresampledbysoftware(Matlab2014a,Mathworks,USA)at200Hz

asdescribedintheoriginaliTUGstudy[18].

Measurementprotocol

Eachpatientwas firstequippedwith thewearable sensor set.Then, inaccordancewithSalarianetal.

[18],weusedanextendediTUGtestversionwitha7-meterwalkingdistance.Thereby,moregaitcycles

were recorded thanwhenusing the original TUG test protocol. All participants completed the testing

sessioneitherinagaitlaboratoryoftheInstituteofHumanMovementSciencesandSportatETHZurich,

Switzerland,orinsuitablelocationsattheRehabilitationCenterValens,Switzerland.

Thetestingsessionincludedthefollowingprocedure:Initially,eachparticipantwasequippedwithaset

of sensors.Once the sensorshadbeenattachedon theappropriateparticipants’ bodypositions, they

performedthe first iTUGmeasurementsessioncomposedof threerepeated iTUGtrials (measurement

session 1). Between each trial, a 30-second rest periodwas applied. After completing the three iTUG

trials, the participantswere instructed to relax for 15minuteswhile removing the sensors from their

body. Then, the sensors were reattached to participants’ body and the same protocol repeated

(measurementsession2).Eachtestingsessionwasrecordedwithavideocameraallowingresearchers

laterinspectionifnecessary.

Inordertogetsufficientinformationabouttheassessmenttool’sreliabilityandvaliditycharacteristics,

weidentified1)therelativereliabilitybyusingtheintraclasscorrelationcoefficient(ICC),2)theabsolute

reliabilitytoidentifyarealimprovementbycalculatinga)thestandarderrorofmeasurement(SEM)for

groups of subjects, b) the limits of agreement (LOA) for a single person and c) the smallest clinical

detectabledifference(SDD)whichalsorevealsthe limitsfortherealchangeforasinglepersonand3)

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thediscriminatorycapabilitiesontheiTUGmetricsbycomparingstrokepatientstohealthyage-matched

controls.

Dataanalysis

Based on algorithms described elsewhere [18-19, 28-29], different parameters of gait and postural

transitionduringiTUGperformanceweremeasured:

• iTUGtotalduration(sec):TotaldurationoftheiTUGtrialinseconds

Sit-to-walkmetrics

• Sit-to-walkduration(sec):Durationofthesit-to-walktransitioninseconds

• Peak sit-to-walk velocity (deg/sec): Maximum angular trunk velocity in degrees per secondduringthesit-to-walktransition

Gaitmetrics

• Gait cadence (steps/min): Walking cadence in number of steps per minute; normalized toparticipants’height

• Gaitstancephase(%):Stancephaseasapercentageofgaitcycletime

• Gait limp phase (%): Difference between initial and terminal double support phase as apercentageofgaitcycletime

• Gaitvelocity(m/sec):Walkingspeedinmeterspersecond;normalizedtoparticipants’height

• Gaitstridelength(m):Distanceinmetersbetweentwoconsecutivefootfallsatthemomentsofinitialcontact;normalizedtoparticipants’height

• Gait peak swing velocity (deg/sec): Maximum angular shank velocity in degrees per secondduringonestride

• Gaitasymmetry:Symmetryratio relatedto theswingphaseperformedbyeach leg;calculatedwiththeformula=|1-((limbwithlowervalue)/(limbwithhighervalue))|

Turningmetrics

• Turningduration(sec):Durationof180°turninseconds

• Peak turning velocity (deg/sec):Maximum angular trunk velocity in degrees per secondwhileturning

Turn-to-sitmetrics

• Turn-to-sitduration(sec):Durationoftheturn-to-sittransitioninseconds

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• Peakturn-to-sitvelocity(deg/sec):Maximumangulartrunkvelocityindegreespersecondduringtheturn-to-sittransition

ThereliabilityandvalidityassessmentsapplytotheiTUGmeasuredforthreetimesandaveragedvalues

asopposedtotheoriginalTUGwhereasinglemeasureafterapracticetrialistakenastheoutcome.For

data analysis, the mean value of the iTUG total duration across the three iTUG trials performed in

measurementsession1andmeasurementsession2,respectively,wasused.Themedianofthemetrics

of the straight walking gait, the transitions and turns across the three iTUG trials performed in

measurement session 1 and measurement session 2, respectively, was used to eliminate possible

outliers.Exceptoftheparameter‘gaitasymmetry’whichisbasedontheswingphaseperformedbyeach

leg,theaveragevalueofbothlegswasused.

Statisticalanalysis

Descriptive statistical analysis was carried out to describe the study population. The one-sample

Kolmogorov-Smirnovtest, skewnessandkurtosiswereusedtotestnormalityof thedata.Theprimary

test-retestreliabilitycalculationswerebasedontheentirestudypopulation.Areliabilitysubanalysisonly

includingthestrokepatientswasperformedseparately.Thereliabilitysubanalysisincorporatedthefive

gait iTUG metrics ‘cadence’, ‘stance phase’, ‘velocity’, ‘stride length’ and ‘asymmetry’. For assessing

differencesbetweenstrokepatientsandhealthyelderly(age-matched),twogroupswerecreated(stroke

& healthy control) and compared with the paired t-test or the non-parametric equivalent where

appropriate.AllstatisticalanalyseswereperformedusingSPSSversion21.0software(SPSSInc.,Chicago,

IL).Thecriticalα-levelwassetatp≤0.05.

Reliability

Several statistical methods of assessing test-retest reliability were performed. Heteroscedasticity was

tested by calculating the square value of Pearson’s correlation coefficient (r2) between the absolute

differenceandthemeanofeachpairofmeasurements.Ifvaluesofr2aregreaterthan0.1,thenthedata

are heteroscedastic [30]. The ICC with the 95% confidence interval (CI) was used as an estimate of

relative reliability [30]. The ICC is commonly used to determine the consistency or reproducibility

betweenrepeatedmeasurementsandtoassesstheSEM[31].Inthisarticle,theICC1,kone-wayanalysis

ofvariance(ANOVA)wasconsideredforthefollowingreasons:Thesamedeviceandsameparticipants

tested by the sole rater were used for assessing test-retest reliability. Furthermore, the two

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measurementsessionsperformedduringthestudywereseparatedbyatimeperiodofonly15minutes.

Therefore,weassumedthatparticipants’gaitpatternwouldnothavechangedoverthistime.

The interpretation of the ICC valueswas according to Shrout and Fleiss [32] inwhich values of >0.75

indicate excellent reliability, 0.75-0.40 fair to good reliability and <0.40 poor reliability. Since the ICC

score depends greatly on the range of values in the analyzed sample [30] and is not able to provide

informationabouttheaccuracyforaspecificindividual,theSEMandtheSDDforeachparameterwere

calculated. TheSEM indicatesa real improvement in thegroupof individuals andwasassessedusing:

SEM=SD√(1-ICC),inwhichSDrepresentsthesamplestandarddeviation[30].TheSDDcanbeusedasan

indicatorforassessingrealchangebeyondmeasurementerrorinasingleperson.Itwasderivedfromthe

SEM through: 1.96 x √2 x SEM [26]. The SEM and SDD can be expressed as a percentage which are

independentof theunitsofmeasurementand, therefore, suitable tocompare theamountof random

error between measurement parameters: SEM% = ((SEM/mean of the two measurements)*100) and

SDD%= ((SDD/meanof the twomeasurements)*100).Discrepanciesbetween themeasurementswere

also investigatedbyperformingBlandandAltman’s95%LOAanalysis. Itexpressesthedegreeoferror

proportional tothemean.TheBlandandAltmanmethod includesascatterplotproviding information

about the degree of error (measurement 1 – measurement 2) proportional to the mean of the two

measurementswith95%LOA(meandifference±1.96xSDofthedifference)[24,33-34].

Validity

Thepaired t-test and theWilcoxon signed-rank testwere performed to examinedifferences between

stroke patients and the age-matched healthy controls, depending on normality of data. Groupmean

values of the iTUG metrics are expressed as mean ± SD. Effect sizes are presented as Pearson’s

correlationcoefficient(r)whichcanbecalculatedfromthet-statisticsconvertedintor-statisticsbythe

formular=t2/(t2+df)orfromtheZvalueusingtheequationr=Z/√N[35].dfrepresentsthedegreesof

freedom,Z theapproximationof theobserveddifference in termsof thestandardnormaldistribution

andNthetotalnumberofobservations.Theeffectsizemagnitudeofr=0.1indicatesasmall,r=0.3a

medium and r = 0.5 a large effect [35]. The results of the first measurement session were used for

analysis.Since thegaitparameterswalkingspeed,stride lengthandcadencearerelatedtosomeone’s

bodyheight,theseparameterswerenormalizedtoheight(actualparametervalue/height)[36].

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5.3Results

Atotalof39participantswereenrolledinthestudy,whereof25werehealthyelderly.Thecharacteristics

ofthisstudypopulationaredescribedinTable5.1.Sincethetwogroupsdifferedinmeanage,anage-

matched comparison of 12 stroke patients and 12 age-matched healthy controls was performed for

validityanalysis.ThecharacteristicsofthoseparticipantsarepresentedinTable5.2.

Reliability

Out of the 14 analyzed iTUGmetrics, the ICCs of 12 variables showed excellent test-retest reliability

(ICC1,k = 0.855-0.994). Only the two sit-to-walk parameters ‘duration’ and ‘peak sit-to-walk velocity’

reported a lower relative reliability coefficient (ICC1,k = 0.431 and ICC1,k = 0.674). The ICC values with

corresponding95%CIarereportedtogetherwiththeSEMandSEM%,theSDDandSDD%,andthe95%

LOA inTable5.3.Valuesof r2basedon theabsolutedifferencesbetweenmeasurementsession1and

measurementsession2andthemeanvalueofbothmeasurementsessionswereforalliTUGparameters

below 0.1 indicating no evidence of heteroscedasticity. Bland and Altman plots graphically support

homoscedasticity in all iTUG variables analyzed (Figures 5.1-5.14). Eleven of the 14 analyzed iTUG

parameters showed lowSEMandSEM%values (ranging fromSEM%=0.220 to7.109%),and lowSDD

andSDD%values (ranging fromSDD%=0.659 to19.706%).HighSEMandSEM%values (ranging from

SEM%=15.819to20.600%),andhighSDDandSDD%values(rangingfromSDD%=43.848to57.134%)

werefoundforbothsit-to-walkparametersandforthegaitparameterrelatedtothelimpphase.

ThereliabilitysubanalysisofthegaitiTUGmetrics‘cadence’,‘stancephase’,‘velocity’,‘stridelength’and

‘asymmetry’ revealed similar results to thosebasedon theentire studypopulation (Table5.4): Forall

five iTUGmetricsmeasured,excellent test-retest reliability (ICC1,k=0.958-0.991)withconcomitant low

SEMandSEM%(rangingfromSEM%=0.431to2.701%),and lowSDDandSDD%values(rangingfrom

SDD%=1.292to7.481%)werefound.

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Table5.1:Demographicdataoftheentirestudypopulation.

Characteristics Strokepatients Healthyelderly Total p-value r-value

Numberofparticipants 14 25 39

Age(years),mean±SD(range) 64.7±9.2(47-76) 76.0±5.7(66-86) 72.0±9.0(47-86) <0.001a 0.381c

Sex(female/male) 2/12 17/8 19/20

Height(cm),mean±SD(range) 175.4±6.0(166-186) 167.7±9.2(152-189) 170.4±8.9(152-189) 0.008a 0.174

Weight(kg),mean±SD(range) 82.0±15.1(62.5-114.0) 73.4±12.4(50.4-101.10) 76.5±13.9(50.4-114.0) 0.061 0.092

BMI(kg/m2),mean±SD(range) 26.6±4.1(21.1-35.2) 26.0±3.1(19.0-30.4) 26.2±3.5(19.0-35.2) 0.907 0.019

Walkingassistance,n(%) 5(35.7%) 0(0.0%) 5(12.8%)

Affectedside(right/left) 8/6 - -

p-valueforbetween-groupscomparison,aSignificantbetween-groupdifferences(pbetween≤0.05)calculatedwithindependentt-testandMann-WhitneyU-test.r-value,effectsize,calculatedaccordingtor=Z/√Nandr=t2/(t2+df),r=0.1:smalleffect,cr=0.3:mediumeffect,br=0.5:largeeffect.BMI,Bodymassindex;SD,standarddeviation.

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Table5.2:Demographicdataoftheage-matchedstudypopulation.

Characteristics Strokepatients Healthyelderly Total p-value r-value

Numberofparticipants 12 12 24

Age(years),mean±SD(range) 67.5±6.2(57-76) 71.2±3.0(66-76) 69.3±5.1(57-76) 0.078 0.134

Sex(female/male) 0/12 9/3 9/15

Height(cm),mean±SD(range) 176.4±5.7(168-186) 168.9±9.5(157-189) 172.7±8.6(157-189) 0.029a 0.200

Weight(kg),mean±SD(range) 85.2±14.0(70.0-114.0) 75.3±12.4(60.2-101.10) 80.3±13.9(60.2-114.0) 0.082 0.131

BMI(kg/m2),mean±SD(range) 27.3±4.0(22.6-35.2) 26.3±2.6(21.7-30.4) 26.8±3.3(21.6-35.2) 0.452 0.026

Walkingassistance,n(%) 5(41.7%) 0(0.0%) 5(20.8%)

Affectedside(right/left) 7/5 - -

p-valueforbetween-groupscomparison,aSignificantbetween-groupdifferences(pbetween≤0.05)calculatedwithindependentt-testandMann-WhitneyU-test.r-value,effectsize,calculatedaccordingtor=Z/√Nandr=t2/(t2+df),r=0.1:smalleffect,cr=0.3:mediumeffect,br=0.5:largeeffect.BMI,Bodymassindex;SD,standarddeviation.

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Table5.3:ReliabilityoftheiTUGmetricsbasedontheentirestudypopulation(strokepatientsandhealthyelderly).

iTUGmetrics ICC1,k CI95%forICC1,k SEM CI95%forSEM SDD SEM% SDD% LALB LAUB

iTUGtotalduration(sec) 0.935 0.876-0.966 1.487 ±2.914 4.122 6.435 17.838 -12.865 9.997

Sit-to-walkmetrics

Sit-to-walkduration(sec) 0.431 -0.079-0.701 0.346 ±0.679 0.960 15.908 44.138 -0.900 0.858

Peaksit-to-walkvelocity(deg/sec) 0.674 0.382-0.828 12.923 ±25.330 35.821 15.819 43.848 -38.700 50.025

Gaitmetrics

Gaitcadence(steps/min) 0.985 0.971-0.992 0.487 ±0.955 1.350 0.453 1.257 -7.142 8.432

Gaitstancephase(%) 0.947 0.900-0.972 0.317 ±0.622 0.880 0.516 1.434 -3.003 2.400

Gaitlimpphase(%) 0.855 0.725-0.924 0.680 ±1.334 1.886 20.600 57.134 -4.007 2.997

Gaitvelocity(m/sec) 0.991 0.982-0.995 0.006 ±0.011 0.016 0.470 1.302 -0.114 0.126

Gaitstridelength(m) 0.994 0.989-0.997 0.003 ±0.006 0.009 0.220 0.659 -0.077 0.083

Gaitpeakswingvelocity(deg/sec) 0.988 0.977-0.993 1.618 ±3.172 4.486 0.466 1.293 -28.105 29.807

Gaitasymmetry 0.963 0.930-0.981 0.666 ±1.305 1.846 6.777 18.783 -7.617 5.951

Turningmetrics

Turningduration(sec) 0.985 0.972-0.992 0.064 ±0.126 0.178 1.914 5.323 -1.209 0.845

Peakturningvelocity(deg/sec) 0.905 0.820-0.950 8.057 ±15.791 22.332 5.502 15.251 -48.866 53.599

Turn-to-sitmetrics

Turn-to-sitduration(sec) 0.951 0.908-0.974 0.242 ±0.474 0.670 5.549 15.363 -2.200 2.079

Peakturn-to-sitvelocity(deg/sec) 0.862 0.739-0.928 6.461 ±12.664 17.909 7.109 19.706 -29.150 39.030

ICC1,k,intraclasscorrelationcoefficient(one-wayanalysis);CI95%,confidenceinterval95%;SEM,standarderrorofmeasurement;SDD,smallestdetectabledifference;LALB,limitsofagreementlowerboundary;LAUB,limitsofagreementupperboundary.

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Figure5.1:BlandandAltmanplotofiTUGtotalduration.Closedcircles=strokepatients,opencircles=healthyelderly.

Figure5.2:BlandandAltmanplotofsit-to-walkduration.Closedcircles=strokepatients,opencircles=healthyelderly.

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Figure5.3:BlandandAltmanplotofsit-to-walkvelocity.Closedcircles=strokepatients,opencircles=healthyelderly.

Figure5.4:BlandandAltmanplotofgaitcadence(notnormalizeddata).Closedcircles=strokepatients,opencircles=healthy

elderly.

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Figure5.5:BlandandAltmanplotofgaitstancephase.Closedcircles=strokepatients,opencircles=healthyelderly.

Figure5.6:BlandandAltmanplotofgaitlimpphase.Closedcircles=strokepatients,opencircles=healthyelderly.

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Figure5.7:BlandandAltmanplotofgaitvelocity(notnormalizeddata).Closedcircles=strokepatients,opencircles=healthy

elderly.

Figure5.8: BlandandAltmanplotof gait stride length (notnormalizeddata). Closed circles = strokepatients, open circles =

healthyelderly.

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Figure5.9:BlandandAltmanplotofgaitpeakswingvelocity.Closedcircles=strokepatients,opencircles=healthyelderly.

Figure5.10:BlandandAltmanplotofgaitasymmetry.Closedcircles=strokepatients,opencircles=healthyelderly.

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Figure5.11:BlandandAltmanplotofturningduration.Closedcircles=strokepatients,opencircles=healthyelderly.

Figure5.12:BlandandAltmanplotofpeakturningvelocity.Closedcircles=strokepatients,opencircles=healthyelderly.

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Figure5.13:BlandandAltmanplotofturn-to-sitduration.Closedcircles=strokepatients,opencircles=healthyelderly.

Figure5.14:BlandandAltmanplotofpeakturn-to-sitvelocity.Closedcircles=strokepatients,opencircles=healthyelderly.

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Table5.4:ReliabilityoftheiTUGmetricsbasedonthestrokepatients.

iTUGmetrics ICC1,k CI95%forICC1,k SEM CI95%forSEM SDD SEM% SDD% LALB LAUB

Gaitmetrics

Gaitcadence(steps/min) 0.983 0.948-0.994 0.488 ±0.957 1.354 0.512 1.421 -3.603 11.081

Gaitstancephase(%) 0.958 0.873-0.986 0.327 ±0.641 0.907 0.522 1.448 -4.198 2.059

Gaitvelocity(m/sec) 0.985 0.955-0.995 0.007 ±0.014 0.020 0.746 2.131 -0.057 0.173

Gaitstridelength(m) 0.991 0.973-0.997 0.005 ±0.011 0.015 0.431 1.292 -0.087 0.136

Gaitasymmetry 0.981 0.942-0.994 0.464 ±0.910 1.285 2.701 7.481 -6.810 6.078

ICC1,k,intraclasscorrelationcoefficient(one-wayanalysis);CI95%,confidenceinterval95%;SEM,standarderrorofmeasurement;SDD,smallestdetectabledifference;LALB,limitsofagreementlowerboundary;LAUB,limitsofagreementupperboundary.

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Validity

TheresultsofthevalidityanalysisarepresentedinTable5.5.Consideringthetotaltimedurationneeded

foriTUGcompletion,therewasastatisticallysignificantdifferencebetweenthetwogroups.Thestroke

patientsrequiredmoretimetocompetetheiTUGtestcomparedtotheage-matchedhealthycontrols.

Among the 13 computed iTUG subcomponent parameters, eight showed significant between-group

differences.

5.4Discussion

Thisstudywasperformedtoanalyzeinertialsensor-basediTUGmetricsregarding1)test-retestreliability

inagroupcomposedof strokepatientsandhealthyelderlyand2) theability todiscriminatebetween

individualswithstrokeandage-matchedhealthycontrols.Thepresentstudyrevealedthatallbuttwoof

thecomputediTUGmetricsreachedICCsabove0.75,whichindicatesexcellentrelativereliability.Both

variablesthatdidnotachieveexcellentrelativereliabilityvalueswererelatedtotheiTUGsubcomponent

‘sit-to-walk’.ComparableresultsfoundinthisstudywerereportedbySalarianetal.[18],whoperformed

the inertialsensor-based iTUG inpatientssufferingPDandhealthyparticipants.Three,outof the four

major iTUGsubcomponents ‘sit-to-stand’, ‘steady-stategait’, ‘turning’and‘turn-to-sit’showedgoodto

excellentreliabilityformostoftheircontributingmetrics[18].Inlinewithourfindings,theparameters

‘cadence’ and ‘stance phase’ have pointed out as one of the most reliable iTUG variables with ICCs

greaterthan0.90.Regardingthesubcomponents‘turning’and‘turn-to-sit’,therewasconsensusthatthe

parameter‘duration’seemstobethemostreliable.Moreover,inaccordancetoourstudy,Salarianetal.

[18]revealedthesit-to-standsubcomponentasleastreliablepartoftheiTUGtest.

BesidehighICCs,ameasurementtoolshouldexhibitsmallmeasurementerrorsandbeabletoidentify

realchangesinthegroupandinsingleindividuals[37].Theabsolutereliabilityanalysisperformedinthis

study corroborates the good relative reliability of the inertial sensor-based iTUGmetrics. Specifically,

small SEMand SEM%values togetherwith small SDDand SDD%valueswere found in 11of the total

computed14iTUGparameters.Thoselowvaluesindicategoodprecisionofthemeasurementtool.

Exceptforafewoutliers,mostofthedifferencevaluesbetweenthetworepeatedmeasurementswere

lyingwithinthe95%LOAintheBlandandAltmanplotsandwerewelldistributedaroundzero(dashed

zero line in Figures 5.1-5.14) demonstrating good agreement between the data of repeated

measurements(Figures5.1-5.14).

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Table5.5:DifferencesbetweenthegroupsfortheiTUGmetrics.

iTUGmetrics Strokepatients Healthyelderly Meandiff±SD CI95%formeandiff p-value r-value

iTUGtotalduration(sec) 27.66±12.73 18.19±1.84 9.477±11.860 1.941-17.013 0.002a 0.577b

Sit-to-walkmetrics

Sit-to-walkduration(sec) 2.17±0.47 2.10±0.29 0.073±0.570 -0.289-0.435 0.945 0.021

Peaksit-to-walkvelocity(deg/sec) 69.77±26.48 97.81±20.33 28.043±34.812 5.925-50.162 0.018a 0.414c

Gaitmetrics

Gaitcadence(steps/min) 54.6±10.9 68.9±7.4 14.278±12.801 6.144-22.411 0.005a 0.544b

Gaitstancephase(%) 62.20±4.19 61.01±1.39 1.187±4.809 -1.868-4.243 0.850 0.048

Gaitlimpphase(%) 3.64±2.87 2.80±1.86 0.841±3.981 -1.689-3.370 0.850 0.048

Gaitvelocity(m/sec) 0.57±0.17 0.85±0.06 0.282±0.192 0.160-0.404 0.001a 0.609b

Gaitstridelength(m) 0.69±0.16 0.88±0.05 0.187±0.184 0.070-0.303 0.002a 0.577b

Gaitpeakswingvelocity(deg/sec) 297.56±59.24 391.38±34.43 93.824±80.058 42.957-144.690 0.001a 0.609b

Gaitasymmetry 15.60±11.28 6.42±3.39 9.179±13.655 0.503-17.854 0.092 0.352c

Turningmetrics

Turningduration(sec) 5.15±2.83 2.16±0.35 2.994±2.776 1.230-4.757 <0.001a 0.624b

Peakturningvelocity(deg/sec) 95.34±24.47 180.13±28.44 84.788±36.971 61.297-108.278 <0.001a 0.852b

Turn-to-sitmetrics

Turn-to-sitduration(sec) 5.98±3.63 3.17±1.19 2.812±2.758 1.060-4.564 <0.001a 0.625b

Peakturn-to-sitvelocity(deg/sec) 97.51±36.81 88.71±19.42 8.804±37.729 -15.168-32.776 0.733 0.080

p-valueforbetween-groupscomparison,aSignificantbetween-groupdifferences(pbetween≤0.05)calculatedwithpairedt-testandWilcoxonsigned-ranktest.

r-value,effectsize,calculatedaccordingtor=Z/√Nandr=t2/(t2+df),r=0.1:smalleffect,cr=0.3:mediumeffect,br=0.5:largeeffect.Meandiff,meandifference=(meanofthegroupwiththehighervalue)-(meanofthegroupwiththelowervalue);SD,standarddeviationofthedifference;CI95%,confidence

interval95%.

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Onaverage thepatients improvedbetween the firstand the secondmeasurement (BlandandAltman

plots in Figures 5.1-5.14). This is likely a learning effect between the first and secondmeasurement.

Performinganinitialtesttrialpriortotheactualmeasurementmayhavepreventedthislearningeffect.

Several studies described the typical ‘hemiplegic gait’ post-stroke with a decreased walking velocity,

cadence and stride length [1-3, 5, 8]. Moreover, an increase in stance phase duration and left-right

asymmetryseemstobeacharacteristicfeatureofstrokepatients’gait[1-3,9].Accordingly,inthisstudy,

those five iTUG metrics were highlighted by a separate reliability analysis where the group ‘stroke

patients’wereseparated fromthehealthyelderlycontrols (Table5.4).Thesubanalysis showedsimilar

relative test-retest reliabilityvaluesas found in theentirestudypopulation.Specifically,excellent ICCs

above 0.75 were achieved. Furthermore, all five iTUGmetrics in the subanalysis demonstrated good

absolute test-retest reliability expressedby small SEMand SEM%values togetherwith small SDDand

SDD% values. These findings warrant further investigations of the iTUG in larger samples of stroke

survivorsand,thus,furtherexploringtheclinicalrelevanceofthesystem.

In clinical settings, theassessmentofmobility andbalance in stroke survivors is important for several

reasons; e.g., to accurately perform a diagnosis, to plan the treatment method for each individual

patientandtoadequatelyevaluatetherehabilitationeffectiveness.The iTUGsystemhasthepotential

forplayingan importantrole inprovidingclinicallyuseful informationbyobjectivelyassessingastroke

patient’sbalanceandmobility.Thishighlightsitspotentialrelevanceforapplicationinclinicalpractice.

Outofthe14analyzediTUGmetrics,nineshowedasignificantdifferencebetweenstrokepatientsand

healthy controls (Table 5.5). Among the variableswhichwere significantly different between the two

groups,alldemonstratedhigheffectsizevaluescloseto0.50andlarger.Incontrast,smallereffectsizes

rangingfrom0.021to0.352weremeasuredforthosefiveparameterswhichdidnotdifferbetweenthe

twogroups.Specifically,therewerenosignificantdifferencesinthedurationrequiredforcompletingthe

iTUGsubcomponent‘sit-to-walk’,inthepercentagevaluesrelatedto‘stancephase’and‘limpphase’of

gait cycle timeduring steady-state gait, in the left-right gait asymmetry, and in themaximumangular

trunkvelocityduringturn-to-sittransition.

Frompreviousstudieswehave indicationthatstroke leads towalking-andbalance-related limitations

and negatively affects patients’ functional mobility. Research by Ng and Hui-Chan [15] indicates that

therewasasignificantdifferencebetweenchronicstrokepatientsandhealthyelderlyofthedurationit

tookforTUGtestperformance.Inlinewithourstudy,thestrokepatientsneededmoretimetofinishthe

90

TUG procedure. Furthermore, significant higher values forwalking speed, cadence and step length in

favorofthehealthyindividualswerefound.Regardingthevariable‘stancetime’,NgandHui-Chan[15]

revealedadiscrepancybetweenthetwogroups,butonlywhentheoutcomebasedonstrokepatients’

unaffected side was considered. In our study, no separate body-side related analysis was done and,

therefore, no specific information regarding the paretic and non-paretic side available. Hence, we

recommendthatthisshouldbepartoffuturestudies.OlneyandRichards[38]statedanincreaseofthe

stance phase proportion within the gait cycle in stroke patients. In the present study, however, no

significant difference was found between stroke patients and age-matched healthy controls. The

inconsistencybetweenthestudiesmayberelatedtodifferencesinstrokecharacteristicsandseverity.

Gait symmetry represents an indicator of normalwalking [39]. Since stroke often results in unilateral

symptomscontralateraltotheinfarct,normalizationofgaitsymmetrymaybeanindicatorforrecovery

of gait. For gait symmetry evaluation, variousmetrics can be considered. According to literature, the

most common symmetrymetrics used for gait assessment are swing time, single support time, pelvic

and/or trunkmovement, and ground reaction forces [39-40]. Patterson et al. [40] concluded that the

parameter ‘swing time’ is suitable to analyze gait symmetry post-stroke and, therefore, highly

recommended.Hence,thisstudyfocusedonthegaitvariable‘swingphase’forsymmetrymeasure.Our

resultsofthegaitsymmetryevaluationare,however,atoddswiththefindingsrevealedbyPattersonet

al.[40].Pattersonetal.[40]reportedamoreasymmetricgaitpatterninstrokepatientswhencompared

with healthy individuals. In the current study, no significant asymmetry difference was found.

Nonetheless, the effect size for gait asymmetry exceeded the 0.30 level and showed, consequently, a

mediumeffect.Onepossible reason for thismightbetherathersmall sampleofstrokesurvivorswith

insufficient between-subjects variance. Future studies should, therefore, repeat our study design in

largersamplesofstrokepatientsindifferentpost-strokerecoveryphases.

Another interesting parameter to be considered for gait analysis of stroke patients is arm swing.

Indicationexiststhattheasymmetriesfrequentlyseen ingaitparameterspost-strokealsoaffectupper

body movements resulting in asymmetric arm swing patterns [41]. The hemiparetic gait of stroke

patientsisoftenassociatedwithanadductedarmwithnoorlimitedarmswingontheaffectedside.A

normalizationofthearmswingontheaffectedsidemightbeaparameterforrecoveryofnormalgait.

Zampierietal.[19]identifiedtheiTUGparameter‘peakarmswingvelocity’asoneofthemostsensitive

91

deficits inearlyPD. Itmightbethattheparameter ‘armswing’ isalsoofclinicalrelevancepost-stroke.

Futureresearchiswarrantedthatincludesarmswingparametersasoutcomevariable.

5.5Limitations

Somelimitationsofthisstudyshouldbeconsidered.Afirstlimitationisthelackofdetailedinformation

regardingtheseverity,typeandanatomical lesionlocation(s)ofthestroke.Furtherstudiesareneeded

thatfocusonspecificsubgroupsinthestrokepopulation(e.g.,sub-acuteorchronicpatients,first-everor

recurrent stroke) to substantiate our findings of the inertial sensor-based iTUG application in clinical

settings. Moreover, the pertinence of using elderly to test the iTUG may be questioned. However,

untrainedelderlynormallyshowbothbalanceandgaitimpairments[42-46],whichshouldrenderthem

anadequatepopulation forassessing reliabilityaswell. Thegenderdistribution inour samplemaybe

anotherlimitationwithadifferencebetweenthestrokepatientsandtheage-matchedhealthycontrols

withrespecttosex:Allthestrokepatientsweremaleswhereasonlythreeof12healthycontrolswere

males. This may be a source of bias confounding the results. Furthermore, sex disparity in stroke

prevalencepersistswithwomenbeingmoreaffected thenmen [47]making it important toespecially

test reliability inwomen in futurestudies.A further limitationof this study is thesmall sample size in

relationtoreliabilitystudies.Anadequatesamplesizefortheassessmentoftheagreementparameter,

basedonageneral guidelinebyAltman [48], is lyingaroundat least50. The sample sizeof14 stroke

survivors and 25 healthy elderly individuals we used is, however, a realistic group size to find first

estimates for theassumedrelationbetweenstrokeandfunctionally importanttasksasmeasuredwith

the iTUG and results in preliminary data as a basis for further examinations including larger samples.

Furthermore,thereliabilitysubanalysishastobeinterpretedwithcaution:Otherthanthedatausedfor

the primary reliability analysis based on the entire study population, the subanalysis data were not

checkedforheteroscedasticity.

5.6Conclusion

Excellenttest-retestreliabilitywasfoundformostoftheiTUGmetricsmeasuredandtheinertialsensor-

basediTUGisabletodistinguishstrokepatientsfromhealthycontrols.Thesefindingssuggestthatthe

inertialsensor-basediTUGmeasuresareusefultoassessfunctionalmobilityinstrokepatients.However,

thestudyshouldberepeatedwithalargergroupofpatientstoinvestigateitsdiscriminatorycapabilities

betweendifferentsubgroupsofstrokepatients.

92

Authors’contributions

SWcontributed to the conceptionof thework, to theacquisition, analysis and interpretationofdata,

andtowritingthemanuscript.FMcontributedtothedevelopmentoftheiTUGsoftware,assistedinthe

acquisitionandanalysisofdata.KAcontributedtotheconceptionoftheworkandthedevelopmentof

theiTUGsoftware.RGassistedintheacquisitionandanalysisofdataintheclinicalsettingandcritically

revisedthemanuscript.EDdBinitiatedthestudy,assistedintheacquisitionofdata,andcontributedto

writingandcriticallyrevisingthemanuscript.Allauthorsreadandapprovedthefinalmanuscript.

Acknowledgments

This work was partially supported by the REWIRE project (www.rewire-project.eu), funded by the

European Commission under the FP7 frameworkwith contract 287713.We thank Prof. Dr.med. Jürg

Kesselring,GabrielaWyttenbachandSusanneMüller,ClinicsofValens,forsupportwithorganizationand

recruitingofpatients.

Conflictofintereststatement

Theauthorsdeclarethattheyhavenocompetingfinancialinterests.

93

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6

Epilogue

97

Thenumberofstrokepatientsincreasesyearafteryear[1].Moreover,thereisanincreasedawareness

that stroke patients benefit strongly from a rehabilitation program that well exceeds the critical first

threemonthsafterstroke[2].Clearly,theneedforalong-termapproachtostrokerehabilitationforan

ever larger number of stroke patients cannot be realized by cost-intensive inpatient care alone.

Autonomous home-based rehabilitation programs are required. Interactive rehabilitation games

representapromisingtooltosupportintensiveandprolongedhome-basedstrokerehabilitation.

Accordingly, the overarching theme of this doctoral thesis was home-based long-term stroke

rehabilitationusingrehabilitationgamesspecificallydesignedforthispurpose.First,thisthesisdescribed

the Intelligent Game Engine for Rehabilitation (IGER) – a game engine designed for building

rehabilitation games that are functional, accessible and entertaining. Second, it discussed the two-

dimensional taxonomy framework suggested by Gentile as a template for providing beneficial virtual

reality(VR)-basedrehabilitationcircumstancesinaccordancewithestablishedmotorlearningprinciples.

Third,itpresentedaninterventionstudyfollowingauser-centeredinteractiondesignmethodology.This

study assessed the usability and effects of a 12-week rehabilitation program based on the newly

developedrehabilitationgamesandorganizedaccordingGentile’staxonomy.

In order to quantify intervention effects, a reliable method for measuring stroke victims’ physical

functioningisneeded.Tothisend,thisthesisevaluatedaninstrumentedversionoftheTimedUpandGo

test(TUG)abbreviatedas iTUG.Specifically, itwasevaluatedwhetherthe iTUGusingwearable inertial

sensorsrepresentsareliableandvalidassessmenttoolformobilitydeficitdetectionpost-stroke.

Inthisepilogue,Iwill(1)detailthemainfindingsofthethesis(2)outlinemethodologicalissuesand(3)

providedirectionsforfutureresearch.

6.1.Computational intelligenceandgamedesign foreffectiveat-homestroke rehabilitation

(Chapter2)

VR technique was hypothesized to offer a broad spectrum of advantages for providing beneficial

treatment conditions in clinical practice. It is not surprising, therefore, that interactive videogames

availablefortheentertainmentmarketfoundtheirwayintothefieldofhealthcareandinfluencedthe

directionofresearchinthisarea.However,todate,themajorityofgamesappliedinhealthcarelacked

the features needed to support rehabilitation at home. In our view, the following features must be

ensured:First,a flexibleadaptationof thegamechallenge levelaccording topatient’sactual statusof

functional abilities is required. A proper level of exercise difficulty ensures that the rehabilitation

98

exerciseisneitherperceivedastooeasyandboringnorastoodifficultandfrustrating.Thishelpstokeep

individuals’trainingmotivationhigh.Second,continuousmonitoringofthepatientisneededtobeable

tocorrectharmfulpostureandbadmovements.Third,andrelated,giventheabsenceofcliniciansand

therapistsinpatients’homeenvironments,automaticreal-timepatientfeedbackisofgreatimportance.

The patient can then be warned upon incorrectmovement execution or gameplay, thereby ensuring

patientsafety.Moreover,thefeedbackfeaturecanalsoserveasamotivationaltool.

Inordertoachievepleasurablegameplayexperiences,itisimportanttoexplicitlyconsidergamedesign

principles widely applied in games developed for the leisure industry. Three such principles are

meaningfulplay, flowtheoryandsenseofpresence.Theprincipleofmeaningfulplayreferstothe link

betweenaplayer’sparticularactionanditsconsequenceswithinthegame.Byprovidingdirectandclear

feedback,thislinkisensuredandtheplayerunderstandsthegame’sinternallogicandfeelsincontrolof

gameevents[3].Furthermore,accordingtothetheoryofflow,ithasbeenfoundthatbyappropriately

adaptingthechallengeandcomplexityofavideogametoapatient’scognitiveandphysicalcapabilities,

theplayerwillachieveahigh levelof focusandfeel trulypresent inthevirtualworld.Thiscouldeven

reach a stage in which patients forget that they are performing therapeutic exercises [4].Moreover,

thereisevidencethattheplayer’srealbodymovementsshouldbetrackedandintegratedinthegamein

real time; i.e., well-synchronized with the game’s virtual environment. Thereby, the player gets an

enhanced sense of autonomy and regards him- or herself as being the actor [5]. We assume that

rehabilitation games that meet these requirements are more successful at motivating patients for

treatmentpracticethanthosewhodonot.

In order to optimize home-based rehabilitation, games should not be treated as stand-alone

components. There is a need for overarching system architecture to connect relevant parties

contributing to successful rehabilitation outcomes. Specifically, the rehabilitation games must be

integratedintoabroaderstructurecomprisedofpatients,rehabilitationspecialists,hospitalsandhealth

providers.WithintheREWIREproject,threemaincomponentsmakeupamulti-layeredstructure:(1)the

patientstation(PS),(2)thehospitalstation(HS)and(3)thenetworkingstation(NS).ThePS–installedin

thepatient’shome–includesfourmodulesthatenablethefollowingtasks:hospitalcommunicationfor

downloadinggameconfigurations,datacollectionofpatients’dailylifeactivities,patientcommunityfor

interactingwithpeersandguidanceof the rehabilitationprocessbasedon the IGER.The IGER system

represents the core component of the PS allowing game configurability and flexibility, feedback

realization, real-time adaptation andmonitoring [4]. Its functioning is based on a game engine and a

game control unit. TheHS – conceived as aweb application – is a therapymanagement tool used at

99

hospital. Itgeneratesavirtualcommunitybetweenpersonsinvolvedintherehabilitationprocess(e.g.,

patients,therapists,clinicians)tosupportpatients’therapypractice.Additionally,theHSenablesinsight

intopatients’rehabilitationoutcomesaswellasthespecificationandmonitoringoftreatmentsessions.

TheNS– installed at a regional level at thehealthprovider site – is responsible for datamining. This

stationrevealsfeaturesandtrendsofrehabilitationtreatmentandallowsacomparisonof,e.g.,different

hospitals,geographicregionsandsocio-economicgroupings.

The structure and characteristics described here are likely to ensure a motivating, safe and well-

supervisedrehabilitationenvironmentandhencerender long-termhome-basedrehabilitationfeasible.

However, a set of targeted videogames embedded in overarching system architecture – although

necessary – is not yet sufficient for providing a comprehensive approach to rehabilitation. The

videogames must be embedded in a structured, theory-based therapy program so that continuous

progressacrossallrelevantdimensionsofmotorfunctionisensured.

6.2. Design considerations for a theory-driven exergame-based rehabilitation program to

improvewalkingofpersonswithstroke(Chapter3)

Inthecontextofthisdoctoralthesis,Gentile’staxonomywasconsideredasatherapyprogramtemplate.

Chapter 3 explained how Gentile’s taxonomy constitutes a practical template, which allows the

development of a therapy program according to the motor learning principles variable practice and

progression. Concretely, based on a 4x4-table (see Table 3.1, Chapter 3), 16 different categories to

classify motor skills are characterized. Each skill category is defined by unique features through two

general dimensions (i.e.,environmental contextandaction function).Due to thepositioningof the16

skillcategorieswithinthetaxonomy,asystematicprogressionintaskdifficultycouldbeperformedina

structured and simplemanner. Gentile’s taxonomy allows VR rehabilitation scenarios to be efficiently

created.Sincethebeginningofthe1990s,evidencehasaccumulatedthatvirtualenvironmentsareable

tofacilitatetheacquisitionofmotorskills[6].Consequently,VRhasbeguntobeappliedasapotential

tool for motor rehabilitation. A key advantage of this technology is the possibility of tailoring the

environmental conditions for therapy purposes. Furthermore, numerous studies emphasize that VR

provides engaging treatment situations and, thereby, enhances patients’motivation for rehabilitation

practice. This, in turn, might lead to better clinical outcomes [7]. Accordingly, we developed six

exergames and used them to create 16 virtual rehabilitation scenarios organized in accordance with

Gentile’staxonomy.

100

The16 scenariosorganized thusaccommodate thedescriptionof seven levelsof taskdifficulty,which

areorderedalongthediagonalofthe4x4-taxonomy(seeTable3.3,Chapter3).Basedonthisstructure,

wepresentedaformalprocedurefordefiningmeaningfultherapyplans.Concretely,rehabilitationstarts

with skill category 1A in the upper left corner of the taxonomy, which represents difficulty level 1.

Difficulty may be increased either by a vertical shift to the adjacent row (skill category 1B), or a

horizontal shift to the adjacent column (skill category 2A). Hence, skill categories 1B and 2A together

formdifficultylevel2.Fromeitherofthetwoskillcategoriesindifficultylevel2,wecanobtaindifficulty

level3byagainshiftingeitherhorizontallyorvertically.Whencontinuingthisprocess,weendupinskill

category 4D,which represents the seventh and final difficulty level in the taxonomy. Importantly, the

procedureproposed isnot limitedtoskillcategory-basedshifts inonlyonedirectionyet involvesboth

horizontal and vertical shifts and hence a modification of both environmental context and action

function. Additionally, persons involved in the therapy may freely choose the order in which skill

categoriesinthesamedifficultylevelaretraversed,thusallowingthetherapyprogramtobetweakedto

each patient’s individual rehabilitation requirements. Due to these advantages, Gentile’s taxonomy

constitutes a valuable template for the systematic development of coherent VR-based rehabilitation

programs to improvepost-strokemotor deficits. Future exploratory studies are neededwith focus on

usabilityandfeasibilityofrehabilitationinterventionsbasedonGentile’staxonomyusingVR.

6.3.Usabilityandeffectsofanexergame-basedbalancetrainingprogram(Chapter4)

Hemiparesis isregardedasamajor impairmentofstrokepatientswhichresults inanimpairedwalking

patternanddiminishedbalanceskills.Intactwalkingabilitiesare,however,centralforthepreservation

of autonomousmobility and the achievement of a high quality of life [8]. Intensive therapy sessions

performedrepeatedlyoveraprolongedperiodoftimehavebeenproventoguaranteeagood levelof

motor recovery post-stroke [9]. Previous studies were able to demonstrate that one of the best

predictors of successful rehabilitation outcome was a high level of motivation. High motivation

corresponds to high adherence and low attrition and contributes to optimal functional recovery from

stroke[10].Unfortunately,however,strokepatientsoftenperceivetherapeutic interventionsbasedon

usualrehabilitationexercisesasmonotonousandboringandtheirmotivationforrehabilitationpractice

is correspondingly low. Because VR represents a promising tool for turning boring rehabilitation

exercises intoentertainingones,videogamescouldbeagoodtooltopromote long-termrehabilitation

viaincreasedmotivation.

101

With this in mind, we designed an intervention program based on a set of five rehabilitation games

designedwithintheREWIREproject.Theprogramaimedtoreducestroke-inducedwalkingandbalance

impairments.Chapter4reportsapilotprojectinwhichtheprogramisappliedinhealthyelderly.Inline

with the phased iterative approach proposed by Campbell et al. [11], the pilot project represents a

discrete exploratory phase, which is to be followed by a prospective study with stroke patients.

Specifically,thepilotprojectfocusedonusabilityandeffectivenessoftheexergame-basedprogram.The

trainingsessionswereperformedthreesessionsperweekfor12weeksforagrandtotalof36sessions.

Thirteenofthe16enrolledparticipantscompletedthestudyintervention(18.8percentattrition)witha

remarkableadherencerateof100percent.Furthermore,basedonparticipants’feedback,ahighlevelof

trainingtechnologyacceptancewasexpressedand fewmodificationsof therehabilitationgameswere

suggested.After the intervention, no significant changeswere found in center of pressure (COP) area

duringquitestanceandinwalkingparameters.However,theBergBalanceScale(p=0.007;r=0.51),the

7-mTimedUpandGotest(p=0.002;r=0.56)andtheShortPhysicalPerformanceBattery(p=0.013;r=

0.48)showedsignificant improvementwithmoderateto largeeffectsizes.Obviously,thestudyresults

suggest that theexergame-based interventionwasperceivedasusableandable to influencegait-and

balance-relatedphysicalperformancemeasurespositively.Innextresearchsteps,itwouldbeinteresting

toevaluatetheinterventionpresentedhereonstrokesurvivors,firstperformedinclinicalsettingsand

thereafterinpatients’homes.

6.4.Reliabilityandvalidityofthe inertialsensor-basedTimedUpandGotest inpost-stroke

individuals(Chapter5)

For evaluating and tailoring a stroke treatment program to the patients’ specific requirements, an

accurateassessmentofphysicalfunctioningisofgreatrelevance.TheinstrumentedversionoftheTUG

based on wearable inertial sensors resulted in improved discriminative capabilities for balance and

mobility evaluation compared to the original test protocol [12]. Yet the iTUG has only been used –

invariablywith positive results – in healthy elderly andpatientswith Parkinson’s disease (PD).Hence,

althoughvalidityandreliabilityhaveneverbeentestedinstrokepatients,itcanbehypothesizedthatthe

iTUGmightalsobeausefultoolfortestingbalanceandmobilitylimitationsinthispopulation.

ThestudypresentedinChapter5analyzediTUG-basedgaitandtransitionmetricsintermsoftest-retest

reliabilityanditsabilitytodiscriminatebetweenindividualswithstrokeandage-matchedhealthyelderly

controls. To investigate test-retest reliability, a repeated-measures designwas used composedof two

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measurementsessionswitha15-minutebreakinbetween.Withineachmeasurementsession,theiTUG

was repeated three times with a 30-second break in between. One observer tested a mixed study

population including both stroke patients (n = 14) and healthy elderly (n = 25). To examine the

discriminatory capabilities of the iTUGmetrics, an age-matched group of 12 patients and 12 healthy

individualswascreatedbyrandomselection.

Thefollowing14iTUGmetricswereanalyzed:iTUGtotalduration,sit-to-walkduration,peaksit-to-walk

velocity,gaitcadence,gaitstancephase,gaitlimpphase,gaitvelocity,gaitstridelength,gaitpeakswing

velocity,gaitasymmetry,turningduration,peakturningvelocity,turn-to-sitdurationandpeakturn-to-sit

velocity. The sit-to-walkmetrics ‘duration’ and ‘peak sit-to-walk velocity’ showed fair to good relative

test-retest reliability; all othermetrics showedexcellent relative reliability. Thehigh relative reliability

wascorroboratedbysmall‘standarderrorofmeasurement’and‘smallestdetectabledifference’values

found in11outof 14 iTUGmetrics.Additionally, the iTUGparameterswere revealed tobe in a good

agreement inBlandandAltmanplots,withmostof thedata lyingcloseto themeandifferencewithin

narrow limits of agreement. The analysis of validity indicates that the inertial sensor-based iTUG

represents a valid assessment method allowing a distinction between stroke patients and healthy

elderly.Concretely,outofthe14analyzed iTUGmetrics,nineshowedasignificantdifferencebetween

the two groups with large effect sizes. A future study could use a pre- and post-design to explore

whether the iTUG represents a valuable tool for efficacy assessment of home-based stroke

rehabilitation.

6.5.Methodologicalissues

Theresultsofthestudiesreportedinthisdoctoralthesis(Chapters2-5)shouldbeinterpretedwithinthe

contextofthemethodologicallimitationsoutlinedbelow.

Thisthesisshowsastrongfocusonbalanceandlargelydisregardstheimportanceofmuscularstrength.

Previous stroke studies have shown that – besides balancedeficits –muscleweakness seems to be a

relevantcontributing factor for impairedwalking function[13-14].Muscleweakness is recognizedasa

frequent negative consequence of stroke and as a limiting factor of gait performance [13, 15-16].

Therefore, the ideal stroke rehabilitation intervention should include strength training in addition to

balancetraining.

Inadditiontothemotordeficitsthatarethemainfocusofthisthesis,cognitivedeficits,whichnegatively

affect both independence and quality of life [17-18], are also common after stroke. Although no

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generalizedandunitaryprofileofcognitiveproblemsafterstrokecurrentlyexists,itisnowthoughtthat

stroke often has a great negative impact on patients’ executive functioning [17-19]. Executive

functioningstandsforcognitiveabilitiesassociatedwithgoal-directedself-regulatorybehaviorincluding

response inhibition, planning,workingmemory, task switching, and attention. Earlier studies highlight

that executive functioning is related towalking performance in bothhealthy and cognitively impaired

older adults and in patients suffering from neurological diseases (e.g., stroke) [20-21]. A substantial

literaturedemonstratespositiveeffectsoncognitive functioningpost-strokecausedbyan intervention

program that emphasized various aspects of executive functions (e.g., planning, strategy, decision-

making, and learning) besides physical and social activities [19]. Obviously, a rehabilitation program

includinganenrichedenvironmentandafocusonbothphysicalactivitiesandexecutivefunctioningmay

effectively promote bothmotor performance and brain function [22]. Based onmy own experiences

withVRgatheredduring theREWIREproject,VRhasgreatpotential to theseconditionsandhence to

effectively promote both cognitive andmotor functioning. However, inmy view, the current REWIRE

rehabilitation games, with their strong focus on balance, should be developed further in order to

become more cognitively challenging. Specifically, structured cognitive stimuli such as response

inhibition, attention,dual tasksanddecision-makingopportunities shouldbe included in the future to

moreeffectivelytrainexecutivefunctioningand,hence,moreeffectivelyimprovewalkingperformance.

The study presented in Chapter 4 aimed at the improvement of individuals’ balance and walking

competency. The intervention was based on a set of five rehabilitation games which required, for

successfulgame-playing,postural controlandstabilitywhile standingonaCOPsensing forceplatform

(i.e., Tymo plate by Tyromotion, Graz, Austria [23]). Interestingly, the intervention did not result in

significant changesofwalkingparameters.As I alreadynotedpreviously, it iswell established that, in

ordertosuccessfullymasteramotorskill(e.g.,walking),task-specificpracticeisparamount[24].Hence,

steppingexercisesmighthavebeenmoreeffectiveforimprovingwalkingfunctionthanexerciseswitha

stationary base of support. Unfortunately, stepping movements cannot be performed safely in the

existingsetup,sincetheTymoplatformistoosmall(32x51cm).Anotherinteractingdeviceisrequiredif

steppingistobeincludedingameplay.TheMicrosoftKinect(Microsoft,Redmond,WA)motionsensing

camera[25]–acommerciallyavailablebodymotiontrackingdevice–maybesuchadevice.Inmyview,

stroke rehabilitation guided by Gentile’s taxonomy should harness the advantages of both the Tymo

plateandadeviceliketheMicrosoftKinect:When,accordingtothetaxonomy,anexerciserequiresbody

stability,usingtheTymoplate ispreferableas itprovides informationaboutpatients’COPmovements

(andhence their stability),even ifboth feetare stationary.Whenbody transport is required,walking-

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related stepping movements should be performed and tracked by using a device like the Microsoft

Kinect.

6.6.Clinicalimplicationsandfuturedirections

The fundamental idea of the REWIRE project and likewise of this doctoral thesis is to develop an

innovative VR-based rehabilitation platform, which allows patients to continue intensive home

rehabilitation under remote monitoring after being discharged from hospital. Such a home-based

rehabilitationapproachisrequiredbecause,asthenumberofstrokevictimscontinuestoincrease,the

cost-intensiverehabilitationservicesinspecializedstrokeunitsorhospitalswillposeaneverincreasing

burdentotheNationalHealthService.Therefore,there isapressuretoshortenthedurationofstroke

rehabilitationinspecializedcentersandreplaceitbymorecost-extensive–yeteffective–home-based

rehabilitation. The recently launched Tymo force plate and Microsoft Kinect camera open new

possibilities for providing this important service.Given the low cost and small footprint of suchnovel

typesofhardware,theyhavethepotentialtoofferstrokepatientsahighlymotivatingandcustomizable

VR-basedrehabilitationprogramwithinthecomfortsoftheirownhomes.Withthesystemarchitecture

developed in theREWIREproject (i.e., thePS, theHSandtheNS;seeChapter2) thepatient isalways

undersupervisionbycliniciansandconnectedwithotherpatients.Hence,professionalsupervisionand

customizationoftherehabilitationprocess,positivepeerpressureandasenseofcommunitycombineto

createanoptimalrehabilitationenvironment.ParticularlythepositiveeffectsofbothVRandthesense

of community on motivation might be crucial. After all, for best recovery results, discharged stroke

patients should practice rehabilitation exercises on a regular basis formanymonths on end,which is

well-nighimpossiblewithoutmotivatingexercisesandthepresenceofacommunityofpeers.Thehigh

acceptance towards the REWIRE rehabilitation games presented in Chapter 4 shows that the newly

developedgamesare indeedmotivating.Thispositiveresultwarrantsasubsequentclinicalexplorative

studyusingthisinterventionapproachwithactualstrokepatients.

Inourstudyonlyfivebalancegameswereused.Thissetofexercisesshouldbeexpandedtoincludethe

aforementioned strength and cognitive elements. It might even be a good idea to generate a set of

gamesthatallowsthedevelopmentof twoparallel taxonomies:one focusingonbalance,andanother

focusing on muscular strength. All exercises – and hence both taxonomies – should include a

pronouncedcognitiveelementtoprovideamultifacetedcomplexchallengethatwillnotonlychallenge

balanceorstrength,butalsopatients’executivefunctioning.

105

In further clinical trials, I also recommend using the iTUG to replace the traditional TUG test for the

objective assessment of motor functions. The iTUG provides a more comprehensive insight into the

effectsofatraininginterventiontoimprovegaitandmobility.ThestudyofferedinChapter5usedagait

analysis system for iTUG metrics assessment based on eight inertial sensors. However, for clinical

practice, a smaller number of sensors is preferable, if this does not significantly affectsmeasurement

accuracy.Asmallernumberofsensorswouldreducethetimeneededtoattachthesensorsandreduce

thesystem’sweighttherebyenhancingwearingcomfort.Basedonpreviousstudies[26-31],Iproposesix

inertial sensors located as follows: One sensor on each wrist (to assess upper limbmovement), one

sensoroneachtibiaplatemid-shank(toassessgaitpattern),onesensoronthemid-thoracicspine(to

assessbodyposture)andonesensoronthesacrum(i.e.,nearthecenterofmass,toaccuratelyassess

balance). This proposal for a reduced number of sensors for the iTUG should be tested in future

experiments.Aiming thedevelopmentof instrumentedassessmentprocedures that canbeperformed

independentlyatpatients’homes,reducingthenumberofsensorsmightbeofgreatrelevance.Onecan

assumethatonlyasystemdesignedforeasyself-applicationavoidsfrustrationinducedbytheinability

touse it.Furthereffort shouldbedirectedtowardsusabilityevaluationof the independentuseof the

iTUGbypatients.

Inanextresearchstep,theeffectoftheexergame-basedinterventiononpatients’physicalfunctioning

shouldbeanalyzed.Beforeconcludingthattheinterventiontrulyrepresentsatherapeuticadvance,an

RCT including stroke patients should ideally be performed. The proposed study would compare two

groups: one experimental group, which performs the game intervention in addition to conventional

physicaltherapyandonecontrolgroup,whichonlyperformsconventionalphysicaltherapyforatotalof

36 training sessions. The main outcome measures would be pre- and post-test results of relevant

walking-relatedparameters.

106

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Summary / Zusammenfassung

109

Summary

Stroke is considered as one of themain causes of acquired adult disability. In themajority of cases,

stroke causes hemiparesis and, hence, diminished balance and walking ability. Locomotor function

deficits are often considered by stroke patients as a primary reason for decreased quality of life.

Therefore, recovery of walking is a major focus in almost all rehabilitation efforts for stroke victims.

Strokerehabilitationinhospitalsorspecializedrehabilitationunitsisexpensive.Asthenumberofstroke

patientscontinuestoincrease,thereisapressuretoreducethetreatmentdurationinspecializedstroke

facilities.Home-basedstrokerehabilitationrepresentsalesscostlyapproachand,therefore,apromising

tooltosupportrehabilitationonalong-termbasis.

Indications exist that virtual reality technology has the potential to promote motor recovery in

rehabilitation.However,videogamesthathavebeenoriginallydevelopedfortheleisureindustryarenot

optimally suited for therapeutic purposes. Specific gaming functionalities (i.e., game difficulty level

adaptation, continuousmonitoring of the patient, real-time feedback) needed for providing beneficial

rehabilitation situations for intensive home-based therapy rehabilitation are lacking. Moreover, for

creatingmotivating rehabilitationgames, it is crucial toexplicitly considergamedesignprinciples (i.e.,

meaningful play, flow theory and sense of presence). These game design principles might be largely

responsible for eliciting attractive gameplay scenarioswhich, in turn, arepresumably fundamental for

prolongedrehabilitationadherence.Allthosegamingcharacteristics,describedinmoredetailinChapter

2, are considered toprovidebeneficial andengaging rehabilitation conditions ina safeand controlled

environment.

Rehabilitationgamesmustbeembeddedinawell-elaboratedtherapyprogramsothatcontinuousmotor

functionprogressbecomespossible.However,todate,nosimpleandfeasibleconceptisavailablethat

facilitates the development of a therapy program consistent with widely accepted motor learning

principles and theories. Specifically, there is a need for an adequate template which allows the

developmentofagraduallyprogressingtherapyprogramincludingtask-specificandvariableexercises.In

thisdoctoralthesis,Gentile’staxonomy,describedinmoredetailinChapter3,wasconsideredassucha

template. It demonstrates a classification system that categorizes motor skills based on a 4x4-table

according to two basic dimensions (i.e., environmental context and action function). Concretely, 16

categories toclassifymotorskillsaredefined;eachof thosedescribedbyunique features.The16skill

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categoriesarepositionedinsuchawaythatsevenlevelsofdifficultyaredistinguishable.Thisstructure

allows a skill category-basedprogression and challenging rehabilitation situations at anypoint in time

duringrehabilitation.

Virtual reality has been shown to be a valuable and flexible technology for tailoring rehabilitation

exercisesbasedonGentile’staxonomy.

Giventheimportanceofwalkingrecoverypost-stroke,theresearchquestiondealtwithinChapter4was

whetherthevirtualreality-basedapproachwouldbeusableandeffective in improving individuals’gait

andbalance.Inordertoprovidepreliminaryresults,apilotprojectwasappliedinhealthyelderlyandthe

usabilitytested.Thestudyincludedatri-weeklybalancetrainingprogramperformedfor12weeks.The

firstobjectiveofthestudywastodeterminetheusabilityoftheinterventionbasedonnewlydeveloped

interactiverehabilitationgames.Thefindingsrevealedahighlevelofacceptanceandagoodadherence

rate and, furthermore, that theparticipants’ perceived the virtual reality-based treatmentprogramas

usableandmotivating.Thesecondobjectivewastoevaluatetheeffectivenessoftheintervention.The

results of the pre- and post-comparisons revealed statistically significant changes in the Berg Balance

Scale, the 7-m Timed Up and Go test and the Short Physical Performance Battery. It is therefore

concluded that the virtual reality-based intervention positively influenced gait- and balance-related

physicalperformancemeasures.

For adequately evaluating the effectiveness of a rehabilitation program and tailoring the treatment

method to the patients’ individual requirements, an accurate assessment of physical functioning is of

greatimportance.ThestudypresentedinChapter5evaluatedaninstrumentedmethodoftheTimedUp

and Go test (iTUG) using inertial sensors. The purpose of this study was to estimate the test-retest

reliability andvalidityof iTUG-basedgait and transitionmetrics in strokepatientsandhealthyelderly.

The results revealed that the majority of the iTUG metrics measured showed excellent test-retest

reliability.Moreover, the iTUG has shown to be able to distinguish stroke patients from healthy age-

matchedelderlycontrols.

The present doctoral thesis emphasizes that virtual reality technology has great potential to provide

beneficial conditions for home rehabilitation. However, it is not entirely settled whether the virtual

reality-based rehabilitation approach can be practically implemented in patients’ home environments

andeasilybeusedindependentlybystroke-affectedindividuals.Furthermore,itsactualclinicaleffecton

111

motorperformance(e.g.,walking)amongstrokevictimsisstilluncertain.Theseopenquestionsprovide

anincentiveforfurtherresearchtofosterthedevelopmentofeffectiveat-homerehabilitationfollowing

stroke.

112

Zusammenfassung

Der Schlaganfall gilt als eine derHauptursachen einer erworbenenBehinderung im Erwachsenenalter.

Nach einem Schlaganfall kommt es in denmeisten Fällen zu einer Hemiparese und einhergehend zu

einer verminderten Gleichgewichts- und Gehfähigkeit. Eine beeinträchtigte Fortbewegungsfunktion

nehmen die betroffenen Menschen häufig als eine der wichtigsten Gründe für eine Einbusse an

Lebensqualität wahr. DieWiederherstellung und Verbesserung der Gehfähigkeit hat deswegen in der

SchlaganfallrehabilitationeinehohePriorität.DieRehabilitationinspezialisiertenZentrenistjedochmit

hohenBehandlungskostenverbunden.DadieZahlanSchlaganfallpatientenstetigansteigt,erhöhtsich

der Druck nach einer Einschränkung der Behandlungsdauer in spezialisierten Einrichtungen. Ein

Rehabilitationsprogramm für zu Hause stellt eine kostensparende Möglichkeit für eine Therapie auf

langfristigerBasisdar.SiegewinntdeshalbzunehmendanBedeutung.

Hinweise existieren, dass durch die Verwendung von virtueller Realität die motorische Rehabilitation

begünstigtwerdenkann.Zuanerkennen istaber,dass sichVideogamesausderUnterhaltungsbranche

für den therapeutischen Einsatz nicht optimal eignen. Es fehlt ihnen an spezifischen Eigenschaften

(Anpassung der Schwierigkeitsstufe, Monitoring des Patienten, Feedback-Funktion), um optimale

Rehabilitationsbedingungen für zu Hause zu gewährleisten. Des Weiteren ist entscheidend, dass die

Videogames nach bewährten Game-Design-Richtlinien (‚meaningful play‘, ‚flow theory‘, ‚sense of

presence‘) konzipiert sind. Es wird angenommen, dass durch die Berücksichtigung der Game-Design-

Richtlinien faszinierende Szenarien geschaffen werden, was eine langfristige Aufrechterhaltung der

Rehabilitation unterstützt. All diese Charakteristiken (beschrieben in Kapitel 2) werden als wichtig

erachtet,umförderlicheundspannendeRehabilitationsbedingungenineinersicherenundkontrollierten

Umgebungzuermöglichen.

Videogames sollen für den therapeutischen Gebrauch in ein gut ausgearbeitetes Therapieprogramm

eingebettet sein, um möglichst optimale Fortschritte zu erreichen. Bis heute konnte sich noch kein

Konzept etablieren, welches die Ausarbeitung eines Therapieprogramms – übereinstimmend mit

motorischenLernprinzipienundTheorien–unterstützt.EntsprechendisteinKonzepterwünscht,umein

progressives Rehabilitationsprogramm zu definieren, das sich durch aufgabenspezifische und variable

Übungen auszeichnet. In der vorliegenden Doktorarbeit wird Gentile’s Taxonomie (beschrieben in

Kapitel 3) als ein dafür sich eignendes Konzept beurteilt. Gentile’s Taxonomie beschreibt ein

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Klassifikationssystem,basierendaufeiner4x4-Tabelle,ummotorischeFertigkeitenzukategorisieren.Es

werden zwei grundlegende Dimensionen berücksichtigt:Anforderungen der Umwelt und Funktion der

Aktion. Die beiden Dimensionen sind jeweils in zwei Komponenten unterteilt, so dass sich eine

Taxonomiemit 16 Kategorien ergibt. Jede dieser 16 Kategorienweist einen spezifischenmotorischen

Fertigkeitscharakter aufundgrenzt sichdadurch vondenanderenab.Die Taxonomie vermagdeshalb

variableÜbungenzubieten.DieAnordnungder16KategorienermöglichteineEinteilunggemässderer

Komplexität, woraus sieben Schwierigkeitsstufen resultieren. Es bietet sich ein strukturierter

RehabilitationsverlaufvoneinfachenzuschwierigenÜbungen.

Durch die Verwendung von virtueller Realität lassen sich Rehabilitationsübungen entsprechend der

TaxonomievonGentiledefinieren.

AngesichtsderBedeutung,dieGehfunktionvonSchlaganfallpatientenzuoptimieren,wurdeinKapitel4

die Benutzbarkeit und der Effekt eines virtuell-realitätsbasierten Rehabilitationsprogramms zur

Förderung derGleichgewichts- undGehfähigkeit untersucht. In einer Pilotstudie absolvierten gesunde

Senioren dreimal pro Woche ein Gleichgewichtstraining über eine Zeitspanne von 12 Wochen. Das

primäreZielder Studiewar,dieBenutzbarkeitder virtuell-realitätsbasierten Intervention zuermitteln,

welchedenEinsatzvonneuentwickelteninteraktivenVideogamesgewährte.DieResultatezeigteneine

hoheAkzeptanzundAdhärenz.Zudemwurdeerkannt,dassdieProbandendievirtuell-realitätsbasierte

Interventionalsbenutzbarundmotivierendbeurteilten.DesWeiterenverfolgtedieStudiedasZiel,die

Effektivitätder Interventionzuerfassen.EinPrä-undPost-VergleichergabsignifikanteVeränderungen

hinsichtlich folgenden Tests: ‚Berg Balance Scale‘, ‚7-m Timed Up and Go‘ und ‚Short Physical

Performance Battery‘. Diese Ergebnisse lassen den Schluss zu, dass die virtuell-realitätsbasierte

Intervention einen positiven Effekt auf Gleichgewichts- und Gehfähigkeits-bestimmende Parameter

bewirkt.

Die Effektivitätsbestimmung und Anpassung eines Rehabilitationsprogramms an individuelle

Erfordernisse bedarf präzise Messmethoden. In der Studie (präsentiert in Kapitel 5) wurde eine

instrumentalisierte Methode des ‚Timed Up and Go‘-Tests (iTUG) unter Verwendung von

Inertialsensoren evaluiert. Das Ziel der Studie war, die Zuverlässigkeit und die Validität von iTUG-

Parametern bei Schlaganfallpatienten und gesunden Senioren zu untersuchen. Die Ergebnisse dieser

StudieverdeutlicheneinehoheZuverlässigkeitfürdieMehrheitdererhobeneniTUG-Parameter.Zudem

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zeigtesichderiTUGalsfähigeMethode,umSchlaganfallpatientenvongesunden,gleichaltrigenSenioren

zuunterscheiden.

DievorliegendeDoktorarbeitunterstreichtdasgrossePotential,welchesdieVerwendungvonvirtueller

RealitäthinsichtlichförderlicherMassnahmeneinerRehabilitationfürzuHauseaufweist.Esistallerdings

nochunklar,obsichdievirtuell-realitätsbasierteMethodepraktischzuHauseumsetzenlässtundsichfür

dieselbstständigeDurchführungdurchSchlaganfallpatienteneignet.ZudemistdieklinischeWirksamkeit

hinsichtlich motorischer Leistungsfähigkeiten (z.B. der Gehfähigkeit) bei Schlaganfallpatienten noch

ungewiss.DieseoffenenFragenstelleneineLegitimationfürweitereForschungdar,umdieEntwicklung

voneffektivenSchlaganfall-RehabilitationsmassnahmenfürzuHausevoranzutreiben.

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Danksagungen

AndieserStellebenutzeichgernedieGelegenheit,michbeidenvielenMenschenzubedanken,diemich

währendderZeitmeinesDoktoratsbegleitetundunterstützthaben.

EingrosserDankgehtanmeinenDoktorvater,PDDr.ElingD.deBruin.

DubistmirinjederPhasemeinesDoktoratsstetsunterstützendzurSeitegestanden.AllunsereREWIRE-

Reisenwaren fürmich eine grosse Bereicherung;wir nutzten diese Zeit für spannendeberuflichewie

auchprivateGespräche.WährendmeinesgesamtenDoktoratsdurfteichimmerwiederaufdeinereiche

berufliche Kompetenz zählen und nebst den fachlichen Inputs auch deinen persönlichen Rückhalt

erfahren.DeinezuversichtlicheArtbewogmich immerwieder,„Stolpersteine“ ineinpositivesLichtzu

rückenunddiesealsChancezunutzen.Esfreutmich,unsereberuflicheTätigkeitfortzusetzenundauch

zukünftigmiteinanderinKontaktzubleiben.

MeinDankgiltProf.Dr.KurtMurer.

Kurt,ichdankedir,dassdumirstetseinAnsprechpartnerwarst,infachlichenwieauchinpersönlichen

Angelegenheiten. Ich schätzte deinen Freiraum, den dumir bei der Arbeit eingeräumt hast, dies liess

michimmerwiederdeinVertrauenspüren.

MeinDankgiltProf.Dr.DavidP.Wolfer.

Ichbedankemichfür Ihr InteresseanmeinerDoktorarbeitundfür IhreBereitschaftalsCo-Referentzu

fungieren.

Ein weiteres Dankeschön widme ichmeinenMitarbeiterinnen undMitarbeiter des IBWS, die meinen

täglichenAlltagbereicherten:

Eva, icherinneremichnochgut anmeinenerstenArbeitstag.DankdeinerherzlichenundoffenenArt

fühlteichmichimIBWS-Teamsofortgutaufgehoben.InzwischensindeinigeJahrevergangen,eswuchs

eineFreundschaftheran,dieichnichtmehrmissenmöchte.Ichdankedir,dassichmichaufdich–deine

Hilfe,deineUnterstützung,deinVerständnisunddeineMotivation–jederzeitverlassendurfte.Ichhätte

mirkeinwertvolleresDoktoranden-sowiedividat-„Gspändli“wünschenkönnen.AufunsereZukunft!

Rolf, ichhabeindirnichtnureinenäusserstkompetentenArbeitskollegen,sondernaucheinenFreund

gefunden. Dank unseren gemeinsamen Interessen, insbesondere aber unserer gemeinsamen Freude

über „Gott und dieWelt“ zu diskutieren, hast dumir viele bereicherndeMomente geschenkt. Deine

lehrreichen fachlichen Anregungen und deine sorgfältige Durchsicht meinerManuskript-Entwürfe mit

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denkonstruktivenKommentaren,habenviel zumGelingenmeinerDoktorarbeitbeigetragen. Ichhabe

eineMengevondirgelernt,soauch,etwasGelassenheitzubewahren.

Brigitte,unsereJogging-Rundenbedeutetenmirsehrviel.Siegabenmirfixe,wöchentlicheZeitfenster,

auf welche ich mich immer freute. Sie boten mir Raum dir Dinge anzuvertrauen, die mich gerade

beschäftigten.DeineRatschläge,deineMeinungunddeineUnterstützungbedeutetenmirsehrviel.

Rahel,dieTageam IBWSverbrachte ichgernemitdir.DankdeinerumgänglichenundnatürlichenArt

konnten wir Wichtigkeiten und Nichtigkeiten unseres „Doktorandinnen-Alltags“ austauschen. Du

konntestmichindenrichtigenMomentenmotivieren,vielenDankdafür.

Patrick, ichgenossnichtnurdie jeweiligenWochentage,andenenwir zusammenam IBWSanwesend

waren, sondern freutemich auch immer per SMS von dir zu hören.Durch dich bin ich ein „richtiger“

Fussball-Fangeworden…vielleichtschaffenwiresja,einmalzusammeneinenMatchzubesuchen,hopp

FCL!

AndreaundGiusy,wiegernehätteichunseregemeinsameZeitamIBWSverlängert, ihrhabtmirnach

euremAbschlussgefehlt.DarankonntenichteinmaldieÜbernahmedes schönstenDoktoranden-Pult-

PlatzesmitderherrlichenAussichtaufdenKäferbergetwasändern(ichhattejaschliesslichauchkaum

Zeit, aus dem Fenster zu schauen… *hihihii*). Ich danke euch für die kurze, aber sehr schöne Zeit

zusammenamIBWS.

Alexandra,eswarschön,dichwährendden letztenMonatenmeinesDoktoratesalsPult-Nachbarinzu

haben. Ich habe dich als aufgeschlossene und unkomplizierte Person kennen gelernt, die sich nicht

einmalüberBücherundMaterialienärgerte,welchesichvonmeinerPult-Seitezudeinerdrängten.Für

deineweitereDoktorandenzeitwünscheichdirallesGuteundvielFreudeandeinerArbeit.

Andi, Federico, Franziska, Laura, Oli, Regula, Roger, Roli, Sarah, Sämi und Yvonne, ein grosses

Dankeschön gilt auch euch. Ihr habt viel zu einem harmonischen Arbeitsklima beigetragen und –

insbesonderewährend denMittagspausen – für fröhliche Stimmung gesorgt. Ich fühltemich in eurer

Gesellschaftimmerwillkommen.

DesWeiterendankeichdemgesamtendividat-Team:

Bujar, Eling, Eva,Hans, Joris undMarco, euer unermüdlicher Einsatz und Engagement für dividat ist

„Weltklasse“. IchdankefüreuergrossesVerständnisbezüglichmeinerknappenZeitressourcewährend

derFertigstellungderDoktorarbeit.Obwohl ichkaumaktiv tätigseinundmitwirkenkonnte, fühlte ich

michstetsalsTeildesTeams.EingrossesDankeschön!

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VonganzemHerzenbedankeichmichbeimeinenwertvollstenFreunden:

Céline,Maika,RamiundSandra,ihrseid„minhellschtStärnamHimmel,minFelsideBrandig,ohniüch

fühlechmechwienesZältohniHering“.Danke,füreureeinmaligeFreundschaft.

MeineabschliessendenWortewidmeichmeinenElternEstherundGregorundmeinerSchwesterCarla.

IhrschenktmirLebensmut,LebensfreudeundLiebe–jedenTagvonNeuem.

MeinDankaneuchistgrösser,alsichauszudrückenvermag.

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Curriculumvitae

Name SelineWüest

Dateofbirth 01-02-1985

Citizenof Grosswangen,Lucerne,Switzerland

Education

2011–2015 PhDinScienceattheInstituteofHumanMovementSciencesandSport,

ETHZurich,Switzerland

2008–2010 MasterofScienceDegreeinHumanMovementSciencesandSport,ETH

ZurichwithMajorinMotorControlandMotorLearning

2004–2008 Bachelor of Science Degree in HumanMovement Sciences and Sport,

ETHZurich

1999–2003 AcademicUpperSecondarySchool,Matura

Masterthesisandacademicinternships

11/2009–06/2010 Master thesis ETH Zurich, Switzerland [completed as an exchange

studentatCardiffUniversity,UnitedKingdom]

“Reliability and validity of a ‘Real Time Location System’ as a tool for

peoplelocatingandinactivitymeasuring”

04/2009–06/2009 Academic internship II in sports therapy at the RehabilitationHospital

Hasliberg,Switzerland

10/2008–12/2008 Academic internship I in physical activity assessment at ETH Zurich,

Switzerland