A Low Cost Telerehabilitation Device for Training of Wristand Finger Functions After Stroke

ABSTRACTThere is a need for robotic rehabilitation devices that in-crease the outcome while reducing the cost of therapy. Thispaper presents a device for training of supination / pronation,dorsal wrist extension and finger manipulation after stroke.The system exhibits modularity in terms of the communica-tion architecture and different optional components. Userinterfaces (UI) can be implemented on different kinds ofdevices including a Rasperry Pi single-board computer onwhich a Qt-based graphical UI was run. Telerehabilitationfunctionality is included using SSL-encrypted RESTful webservices on a three-tier architecture. Expensive sensors wereomitted in order to have a cost-effective system which isa requirement for home-based rehabilitation. The torquesensing is based on current measurements being evaluatedby comparing it to force-torque sensor values. After cancel-ing out the static friction, the low error justified the omissionof an additional sensor.

Categories and Subject DescriptorsApplied computing [Life and medical sciences]: Con-sumer health

General TermsDesign, Measurement, Performance

1. INTRODUCTIONIn high-income countries, stroke is the third most commoncause of death and the major cause of acquired adult dis-ability [14]. Besides personal consequences, this means ahigh economical impact. The average lifetime cost for strokerehabilitation per case in Germany is 43,129 EUR and pro-jected 3.4 million new cases of ischemic stroke from 2006 to2025 lead to estimated costs of 108.6 billion EUR [5].

Often, the upper limb is affected with only 20% to 56%of all stroke survivors regaining useful function after threemonths [10]. In robotic therapy, training of the distal parts

of the upper-limb of the wrist appears to be a crucial fac-tor. A wrist extension for robotic upper-limb therapy devicefurther increased the rehabilitation outcome in comparisonto training of the shoulder and elbow alone [6]. Reachingand wrist supination / pronation training is particularly im-portant since it promotes progress towards more functionalwhole upper extremity movements [11].

Several robotic systems for upper limb rehabilitation havebeen presented [8]. While some studies show promising re-sults in outcome [13], they are not consistently in favor ofrobotics [7]. This underlines the necessity for a better un-derstanding of motor learning which can be enhanced bymeans of robotic rehabilitation [12]. Seen from another per-spective, these systems do not have to compete against tra-ditional therapy but can extend it, for instance, by deployingrehabilitation devices in the home environment.

Home rehabilitation prospectively reduces costs by increas-ing independent training time and relieving the load of ther-apists. Telerehabilitation gives them a means of control andsurveillance over the training and the possibility to inter-vene if necessary. However, most of the proposed devicesare not suitable for home rehabilitation. Many systems aretoo expensive, e.g. due to the use of force-torque sensors [9],do not offer modularity and virtual rehabilitation [4], or arefitted to other systems [1]. 75% of the devices observed in acomprehensive review have not even undergone any sort oftest due to high complexity and poor usability [2].

Based on the beforementioned points, we propose a devicefor training of wrist (supination / pronation / dorsal exten-sion) and finger functions focusing on its application in thehome environment. The system requires to be cost-effective,provide a user interface, actuator and sensors for virtual re-habilitation and the study of rehabilitation paradigms, par-ticularly visual feedback distortion [3], and give remote ac-cess to session data for telerehabilitation.

2. CONCEPT AND IMPLEMENTATION2.1 Concept and DesignThere are two basic approaches of training devices: End-effectors and exoskeletons. Rotational movements involve ahigh number of the 27 degrees of freedom of the hand, whichexoskeletons have to provide, in order to allow fully uncon-strained movements. Following a cost-effective approach,we chose an end-effector design which allows tasks involvingmany DOF without the need for a high number of mechan-

NavigationDswitchD

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PassiveDModeDCubeTouchscreenDNetbook

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Figure 1: Horizontal (l.) and vertical (r.) orienta-tion of the training device

ical DOF.

Depending on the orientation of the device and the usedhandle, different movements can be trained. Supination andpronation exercises are performed in the horizontal positionwith the arm aligned to the motor axis. Dorsal wrist ex-tension and fine finger exercises require the device to beorientated vertically (see Fig. 1). The motor axis, thus,lies perpendicular to the arm so that the way of interact-ing changes and other muscles are activated. This way, onlyone actuator is necessary reducing complexity and cost butstill allowing for different trainings. The whole device is ro-tated by using an adjustable table. The advantages are thatthe mechanical design is kept simpler, the height can bechanged, and the table can be omitted, if a table-top deviceis sufficient.

The end-effector’s main component is a motor that supportsor impedes the patient in performing rotational movements.The motor is placed within a casing that also houses thepower supply with an emergency switch, a microcontrollerboard, electronics, a control panel, and connections. Option-ally, a single-board computer (Rasperry Pi) can be included.

A chuck attached to the motor can fasten different handlesthat give more flexibility in training. Supination / pronationrequires another handle than dorsal wrist extension and byvarying the hand size, the difficulty for fine manipulationtraining can be tuned.

Different training modes are provided. In passive mode,the patient is mobilized either by continuously following asine trajectory with adjustable amplitude and frequency orby using the passive mode cube. It allows hemiparetic pa-tients to control the motor by turning a knob with theirhealthy hand [15]. Depending on the progress of the pa-tient, the support can be reduced or counter-torques can beapplied. The range of motion and patient-induced torquemeasurements are compared over sessions to give feedbackon the progress. Simple rehabilitation games have been im-plemented to make training more diverse. Visual feedbackdistortion can be applied which is subject to studies of thecooperating neurologists.

2.2 Actuation, Sensing, and Electronics

A brushed motor with a nominal torque of 270 mNm, anda gear with a reduction gear ratio of 7:1 was used. Regard-ing the efficiency, the maximum total torque is 1.7 Nm. Thecombination of a strong motor with a low reduction gearratio results in low backdrivability while achieving decentmaximum torque. It is not sufficient to work against strongspasms, but safety concerns and backdrivability outweighedthis possibility. An encoder with 1024 impulses per revolu-tion delivers the relative angle in incremental steps of 0.05◦.A VHN2SP30 H-bridge motor driver amplifies the pulse-width modulation (PWM) signals from the microcontrollerand switches between the directions, breaking and coastingdepending on the input pins.

Torque measurements are an important factor in assessingthe patient’s capabilities. Force-torque sensors were not anoption, since they cost many times more than the presentedsystem. Therefore, the torque measurement utilizes the lin-ear relationship to the armature current. A Hall effect basedcurrent sensor IC, dimensioned for the Ampere range of themotor, converts the current to a voltage measured by themicrocontroller’s 10-bit analog-to-digital converter (ADC).The maximum torque can, then, be restricted by comparingthe measured current to a set point and adjusting the PWMsignal with an integrative controller. We use two differentmicrocontroller boards that both use ATmega328P chips butdiffer in the UART transmission. One uses a CP2102 USBto UART bridge that allows a tethered USB connection toa virtual COM port on the PC. The second board uses aBTM-222 bluetooth module with Serial Port Profile (SPP)to set up a serial connection.

2.3 Software and CommunicationThe software is designed in a modular way. It consists of athree-tier architecture to provide tele or home rehabilitationcapabilities. The client, located at the patient’s side, gathersdata for the evaluation of the rehabilitation progress. Thisinformation is preprocessed and transmitted to the serverlocated at the clinic side.

To maximize the flexibility in client hardware, our prototypeclient software is a cross-platform implementation based onQt4 which runs on standard PCs (Windows, Linux, Ma-cOSX) as well as on single-board computers like the Rasp-berry Pi. The QtonPi group provides support for Qt4 andQt5 on the Rasperry Pi. We ported and natively com-piled our software on a Rasperry Pi Model-B running Rasp-bian wheezy to provide an all-in-one client. The softwareincludes a GUI for progress measurements, motivating re-habilitation games and progress visualization. The inter-face can alternatively be controlled by the integrated nav-igational switch panel, touchscreen or standard PC inputdevices (keyboard/mouse).

The communication architecture allows for a variety of plat-forms to access the functionality and visualize sensor data.The client connects to the microcontroller alternatively overa wired or bluetooth serial UART connection to gather dataor set parameters like torque or target position. The data ofeach training session is transmitted to the clinic side serveror cached locally to be transmitted whenever a server con-nection is possible. With this implicit offline mode the train-ing can be continued anywhere and anytime.

PrintedEcircuitEboard

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Figure 2: Schematic of the system and possible interaction platforms

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Figure 3: Comparison of force-torque to cur-rent measurements including the setpoint trajectorywith and without regarding the static friction. Allcurrents are converted with the torque constant de-termined from the force-torque test.

The server software is hosted on a Glasfish application serverand implements a SSL-encrypted RESTful web service whichreceives data from training sessions and provides configura-tion values to the client software like targets. It consists ofa web front-end based on the JavaServer Faces FrameworkPrimeFaces and connects to a JavaDB database. The REST-ful approach combined with the PrimeFaces UI ensures thecompatibility to various client and web-browsers. The inter-face features administrative, therapists’, and patient viewswith restricted rights.

3. PERFORMANCE EVALUATIONThe first experiment evaluates the accuracy of the torqueestimation from the current measurement. We use a force-torque sensor that is rigidly connected to the device. Acurrent profile is applied on the end-effector and the esti-mated torque is compared to the measured one. The profileincludes a step at the beginning and a drop at the end ofthe sampling period. These two points are used for synchro-nization and scaling of the two sensors that return sampleswith constant but different frequencies. The values afterthe initial step and before the increase of current define thebaseline on which the force-torque sensor is calibrated. Theresults are plotted in Fig. 3.

The dotted line represents the initial setpoint current whichis converted using the linear relation between torque andcurrent. At the beginning of the slope, the increase of cur-rent does not result in higher torque. This is caused byunwanted influences of the gear, mostly by static friction.We determine the static friction together with the torqueconstant by fitting a linear model with T (i) = kmi + b,where T is torque, i is current and km is the torque con-stant, to the torque measurement. Iteratively, we increasethe static friction and repeat the fitting without the valuesbelow the threshold until b is approximately zero. The staticfriction was determined to be 188 mA. The slope representsthe torque constant. With 50.77 mNm/A, it lies close tothe quotient of the starting current and the stall torque of52.75 mNm/A from the datasheet.

Then, we determined the static friction with the traditionalmethod and compared it to our former result. The currentwas increased until a movement occurred, determined by anencoder value unequal to zero. After repeating 100 runs,the measured threshold currents were averaged and resultedin a breakaway current of 120 mA. The lower value comesfrom the encoder’s high sensitivity in conjunction with thegear’s backlash. Since the application of the higher thresholdcurrent onto the motor does not lead to unwanted contin-uous movement, the higher value is valid. It can now beutilized to decrease the initial user induced torque and im-prove the accuracy of the torque estimation. We measured aroot-mean-square error of 25.78 mNm for the fitted dataset.Applied to the measurements from a second run, the errorwas only slightly higher with 30.08 mNm.

The torque control can be applied in different training modes.We implemented a virtual spring where the torque or thecurrent set point, respectively, is linearly increased with theangle difference to a neutral position. A representative shortsession is shown in Fig. 4 with the angle, velocity, and torqueplotted against the samples of 10ms length.

4. CONCLUSIONA rehabilitation device for training wrist and finger func-tions has been proposed. The torque estimation based oncurrent measurements and the angle sensing from the motorencoder readings permits virtual rehabilitation and study-ing rehabilitation paradigms. The performance evaluationrevealed a relative root-mean-square error of 2.2% which isacceptable considering the saved cost by omitting a force-torque sensor. It means that expensive sensors can be omit-

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Figure 4: Representative short session in virtualspring mode.

ted without relinquishing torque control and measurement.However, closed-loop force control, e.g. necessary for ad-mittance devices, is not possible. The Qt GUI can be runon a Rasperry Pi which offers full capabilities of a PC forless than 50$. The device can be accessed remotely andsession data can be transmitted to therapists using webser-vices. The cost-effective therapy device provides remote ac-cess capabilities which are important prerequisites for homerehabilitation.

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