Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases




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Activity and Emotion Recognition to Support Early
               Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
              Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
              Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases



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Activity and Emotion Recognition to Support Early
             Diagnosis of Psychiatric Diseases




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Activity And Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases

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Activity And Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases

  1. 1. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Pervasive Health Conference Tampere, 30th January 2008 B. Arnrich Tampere, January 30th
  2. 2. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Paper Contributors David Tacconi, Oscar Mayora CREATE-NET Paul Lukowicz University of Passau Bert Arnrich, Cornelia Setz, Gerhard Tröster ETH Zurich Christian Haring PSHT PSYCHIATRIC STATE HOSPITAL TIROL PSYCHIATRIC STATE HOSPITAL TIROL B. Arnrich Tampere, January 30th
  3. 3. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Outline Introduction and Motivation Bipolar disorder Pervasive computing to support diagnosis of Bipolar Disorder A proposed System Architecture Discussion and Future Work B. Arnrich Tampere, January 30th
  4. 4. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Introduction Global 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 Depression is 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 disorder account for another 14.1 million (3.0%) DALYs 1World Health Organization, World Bank, Harvard University B. Arnrich Tampere, January 30th
  5. 5. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Motivation Extend psychotherapy beyond the therapy hour State of the Art: computer-aided between-session therapy Online questionnaires Automatic scheduling Our proposal: Activity and Emotion Recognition as a specific contribution to therapy B. Arnrich Tampere, January 30th
  6. 6. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Challenges Few 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 technology providing behavioral assistance is much more difficult than providing physical assistance solutions require considerable amount of domain specific knowledge B. Arnrich Tampere, January 30th
  7. 7. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Bipolar Disorder Characterization repeated relapses of depression and mania Recurrence rates are high at around 50% to 70% Treatment of Bipolar disorder Main: Pharmacotherapy Alternative: 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 B. Arnrich Tampere, January 30th
  8. 8. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Bipolar Disorder: the HAMD 1. Depressed Mood 11. Anxiety Somatic 2. Feelings of Guilty 12. Somatic Symptoms 3. Suicide (Gastrointestinal) 4. Insomnia (early) 13. Somatic Symptoms General 5. Insomnia (middle) 14. General Symptoms 6. Insomnia (late) 15. Hypocondriasis 7. Work and Activities 16. Loss of Weight 8. Retardation: 17. Insight Psychomotor 9. Agitation 18. Diurnal Variation 10. Anxiety (Psychological) 19. Depersonalization and Derealization 20. Paranoid Symptoms B. Arnrich Tampere, January 30th
  9. 9. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Bipolar Disorder: the BRMS 1. Motor activity 7. Self-esteem 2. Verbal activity 8. Contact 3. Flight of thoughts 9. Sleep 4. Voice/Noise level 10. Sexual interest and 5. Hostility activity 6. Mood and feelings of well-being 11. Work level B. Arnrich Tampere, January 30th
  10. 10. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Contributions We 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 B. Arnrich Tampere, January 30th
  11. 11. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Insomnia and Sleep disorders HAMD 4-6, BRMS 9 ”Gold standard” (laboratory settings): polysomnographic monitoring of sleep time physiological parameters (e.g. respiration, heart rate variability) and sleep motion Alternative On-body sensors unobtrusively embedded into biomedical clothes or mattresses allow to obtain preliminary diagnosis and to perform more frequent tests under real-life conditions Alternative sensor mats placed under the mattress thin film, dynamic quasi-piezoelectric sensors capacitive pressure sensor mat B. Arnrich Tampere, January 30th
  12. 12. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Verbal activities and Conversations BRMS 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 B. Arnrich Tampere, January 30th
  13. 13. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Emotion Recognition Restriction to a set of basic emotional states Feasibility study: 10 subjects 6 emotions Recognition rates comparable to humans B. Arnrich Tampere, January 30th
  14. 14. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Activity Recognition HAMD 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) B. Arnrich Tampere, January 30th
  15. 15. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Activity recognition Main sources of activity information Worn combination of accelerometer and microphone Location information Previous experiments Spotting complex activities is feasible Recognition directly on wrist worn device B. Arnrich Tampere, January 30th
  16. 16. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases System Architecture Challenges to be considered: Patients are likely to reject pervasive computing technology in principle Target devices should be as less obtrusive as possible Patients 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 activity pattern or emotions Behaviors that are repeated in time and that can be symptoms of disease’s relapse B. Arnrich Tampere, January 30th
  17. 17. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases System Architecture The User Interfaces module: •present persuasive feedback to the users for motivating healthier patients’ behavior 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 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) B. Arnrich Tampere, January 30th
  18. 18. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Conclusion and Future work Conclusion 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 technology Laboratory testing Field test at the Psychiatric Hospital in Tirol, Austria B. Arnrich Tampere, January 30th
  19. 19. Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases Thank you for your attention. B. Arnrich Tampere, January 30th
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