activity and emotion recognition to support early diagnosis of psychiatric diseases
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Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Activity and Emotion Recognition to Support Early
Diagnosis of Psychiatric Diseases
Pervasive Health ConferencePervasive Health ConferenceTampere, 30Tampere, 30thth January 2008January 2008
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
David Tacconi, Oscar MayoraCREATE-NET
Paul LukowiczUniversity of Passau
Bert Arnrich, Cornelia Setz, Gerhard TrösterETH Zurich
Christian HaringPSYCHIATRIC STATE HOSPITAL TIROL
Paper ContributorsPaper Contributors
PSHTPSYCHIATRIC STATE HOSPITAL TIROL
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
OutlineOutlineIntroduction and Motivation
Bipolar disorder
Pervasive computing to support diagnosis of Bipolar Disorder
A proposed System Architecture
Discussion and Future Work
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
IntroductionIntroductionGlobal Burden of Disease
Mental illness accounts for over 15% of the burden of diseases in established market economies1
Disability Adjusted Life Years (DALYs) measure the lost years of healthy life due to premature death or disability
Depressionis the most common psychiatric disorder, accounting for 50.8 million DALYs or 10.7% of the global burden of disease It is ranked fourth among all causes of DALYs and is the leading nonfatal condition globally
Mental disorders like the bipolar disorderaccount for another 14.1 million (3.0%) DALYs
1World Health Organization, World Bank, Harvard University
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
MotivationMotivationExtend psychotherapy beyond the therapy hour
State of the Art: computer-aided between-session therapy
Online questionnairesAutomatic scheduling
Our proposal: Activity and Emotion Recognition as a specific contribution to therapy
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
ChallengesChallengesFew technological solutions exist to aid people affected by mental illness
Obvious reasons are:people affected by mental illness are more likely to have problems dealing with complex technologyproviding behavioral assistance is much more difficult than providing physical assistancesolutions require considerable amount of domain specific knowledge
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Bipolar DisorderBipolar DisorderCharacterization
repeated relapses of depression and maniaRecurrence rates are high at around 50% to 70%
Treatment of Bipolar disorderMain: PharmacotherapyAlternative: teach the patients to recognize and manage Early Warning Signs (EWS)
Diagnosis through patient questionnaires Depression: Hamilton Depression Scale (HAMD)Mania: Bech-Rafaelsen Mania Scale (BRMS)Both contain a series of questions related to patient’s state, activities and feelings
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Bipolar Disorder: the HAMDBipolar Disorder: the HAMD
1. Depressed Mood2. Feelings of Guilty3. Suicide4. Insomnia (early)5. Insomnia (middle)6. Insomnia (late)7. Work and Activities8. Retardation:
Psychomotor9. Agitation10. Anxiety (Psychological)
11. Anxiety Somatic12. Somatic Symptoms
(Gastrointestinal)13. Somatic Symptoms
General14. General Symptoms15. Hypocondriasis16. Loss of Weight17. Insight18. Diurnal Variation19. Depersonalization and
Derealization20. Paranoid Symptoms
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Bipolar Disorder: the BRMSBipolar Disorder: the BRMS
1. Motor activity
2. Verbal activity
3. Flight of thoughts
4. Voice/Noise level
5. Hostility
6. Mood and feelings of well-being
7. Self-esteem
8. Contact
9. Sleep
10. Sexual interest and activity
11. Work level
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
ContributionsContributionsWe identify Bipolar Disorder as a condition that can realistically benefit from behavioral monitoring
We identify support in early detection of imminent transitions between normal, manic and depressed states as the specific contribution to therapy
We identify specific behaviors that need to be detected by the proposed system, using the HAMD and the BRMS
Based on literature study and previous work by the authors, we argue that detecting these specific behaviors is feasible
We propose an appropriate system architecture based on existing devices and previous systems implemented by the authors groups
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Insomnia and Sleep disordersInsomnia and Sleep disordersHAMD 4-6, BRMS 9
”Gold standard” (laboratory settings):polysomnographic monitoring of sleep timephysiological parameters (e.g. respiration, heart rate variability) and sleep motion
Alternative On-body sensorsunobtrusively embedded into biomedical clothes or mattressesallow to obtain preliminary diagnosis and to perform more frequent tests under real-life conditions
Alternative sensor mats placed under the mattressthin film, dynamic quasi-piezoelectric sensorscapacitive pressure sensor mat
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Verbal activities and ConversationsVerbal activities and ConversationsBRMS 2, 4 and BRMS 8
Spoken messages convey non-textual characteristics like intonation, speaking rate or emotional state
Automatic speech character identification would allow to extract features describing contextual side information
Emotion recognition can give the therapists information about variation of the patient’s mental state
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Emotion RecognitionEmotion RecognitionRestriction to a set of basic emotional states
Feasibility study: 10 subjects6 emotionsRecognition rates comparable to humans
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Activity RecognitionActivity RecognitionHAMD 7-11 and BRMS 1
Several past works on activity recognition
Based on previous experience, we target systematic real life trials to:
quantify Work and Activities (HAMD 7 and BRMS 1)detect Agitation (HAMD 9) and Anxiety (HAMD 10, 11)measure Psychomotoric Retardation (HAMD 8)
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Activity recognitionActivity recognitionMain sources of activity information
Worn combination of accelerometer and microphoneLocation information
Previous experimentsSpotting complex activities is feasibleRecognition directly on wrist worn device
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
System Architecture System Architecture Challenges to be considered:
Patients are likely to reject pervasive computing technology in principleTarget devices should be as less obtrusive as possiblePatients cannot be asked to perform any training of devices
Activity and emotion recognition is targeted to medium and long term behavior
Higher errors in single activity recognition are allowed Focus on average behaviors rather than in instantaneous activitypattern or emotionsBehaviors that are repeated in time and that can be symptoms of disease’s relapse
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
System ArchitectureSystem ArchitectureThe User Interfaces module:•present persuasive feedback to the users for motivating healthier patients’ behavior
The User Model includes all patient’s characteristics, disease’s peculiarities and his preferences. Information stored in:•User Profile (UP)•Disease Description (DD)•Patient Description (PD)
The Context Acquisition module gathers data from Sensors and is driven by:•Emotion Recognition Manager that selects sensors for emotion recognition•Activity Recognition Manager that selects sensors for recognizing user’s activity•User model manager gives proper inputs
The Content Manager module is responsible:•For uploading the data to the EMR through the Data Upload module•For presenting information to the patient through the Feedback Manager module
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Conclusion and Future workConclusion and Future workConclusion
Concept on applying existing pervasive computing techniques to support the early diagnosis of bipolar disorder Proposal of a system architecture designed to monitor patient’s behavior
Future work:Integrating the currently available technologyLaboratory testingField test at the Psychiatric Hospital in Tirol, Austria
Tampere, January 30thB. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Thank you for your attention.Thank you for your attention.