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Pervasive Health 2008 conference presentation
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Tampere, January 30th B. 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 Conference
Tampere, 30Tampere, 30thth January 2008 January 2008
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
David Tacconi, Oscar Mayora, CREATE-NET
Paul Lukowicz, University of Passau
Bert Arnrich, Cornelia Setz, Gerhard Tröster, ETH Zurich
Christian Haring, PSYCHIATRIC STATE HOSPITAL TIROL (PSHT)
Paper ContributorsPaper Contributors
PSHTPSYCHIATRIC STATE HOSPITAL TIROL
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
OutlineOutline
IntroductionBipolar disorder Objectives and System RequirementsPervasive computing to support Bipolar
Disorder diagnosisA proposed System ArchitectureDiscussion and future work
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
IntroductionIntroduction Global Burden of Disease
Mental illness accounts for over 15% of the burden of diseases in established market economies (source World Health Organization, World Bank, Harvard University)
Disability Adjusted Life Years (DALYs): Measure the lost years of healthy life (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
Bipolar disorder: account for another 14,1 million (3.0%) DALYs
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
IntroductionIntroduction 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 and can only be developed in close cooperation with psychiatrists
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Bipolar DisorderBipolar Disorder Bipolar disorder
repeated relapses of mania and depression Recurrence rates are high at around 50% at one year and 70% at
four years Treatments for Bipolar disorder:
Pharmacotherapy is the main treatment nowadays Alternative: teach the patients to recognize and manage Early
Warning Signs (EWS) Diagnosing through patient questionnaires:
for depression the Hamilton Depression Scale (HAMD) for mania the Bech-Rafaelsen Mania Scale (BRMS) Both contain a series of questions related to patients’ activities and
feelings
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Bipolar Disorder: the HAMDBipolar Disorder: the HAMD1. 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
Evaluate between 0 and 4 to obtain the total score
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Bipolar Disorder: the BRMSBipolar Disorder: the BRMS1. motor activity2. verbal activity3. flight of thoughts4. voice/noise level5. hostility/
destructiveness6. mood and
feelings of well-being
7. self-esteem
8. contact
9. sleep (based on the average of the previous 3 nights)
10.sexual interest and activity
11.work levelEvaluate between 0 and 4 to obtain the total score
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
ObjectivesObjectives 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 so called Hamilton Depression Scale (HAMD) and Bech-Rafaelsen Mania scale (BRMS), which are generally accepted tools in the diagnosis of depression and mania
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 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Pervasive Computing for diagnosis of BDPervasive Computing for diagnosis of BD From our experience and a literature study, we propose to
look at the following parameters: HAMD:
items 4,5,6 (insomnia) 7 (work and activities) 8 (psychomotoric retardation) 9 (agitation) 10, 11(anxiety)
BRMS: items 1 (motoric activities) 2 (verbal activities) 4 (voice-noise level) 8 (contacts) 9 (sleep)
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Early Diagnosis 1/3Early Diagnosis 1/3 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 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 Other solutions:
thin film, dynamic quasi-piezoelectric sensors placed under the mattress capacitive pressure sensor mat would allow monitoring sleep motion
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Early Diagnosis 2/3Early Diagnosis 2/3 Verbal activities (BRMS 2, 4),
Contacts/Conversation (BRMS 8)
automatic speech character identificationwould allow to extract features describing contextual side
informationspoken messages convey besides information on
characteristics as intonation, speaking rate or emotional state.
emotion recognition can give to the therapists information about variation of the patient’s mental state.
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Early Diagnosis 3/3Early Diagnosis 3/3 Activity Recognition (HAMD 7,8,9,10,11, BRMS 1)
Several past works on activity recognition: it remains unclear how most prior systems will perform under real
life conditions
Based on previous experience, we target systematic real life trials to: quantify his Work and Activities (HAMD 7 and BRMS 1) understand the Agitation (HAMD 9) and Anxiety (HAMD 10, 11) he
experiences measure an eventual Psychomotoric Retardation (HAMD 8)
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
System Architecture System Architecture Constraints 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, and
this complicates things for emotion and activity recognition. Activity and emotion recognition is targeted to medium and
long term behavior Higher errors in activity recognition are allowed doctors are more interested in average behaviors rather than in
instantaneous activity pattern or emotions a patient is feeling in a given moment.
Doctors are interested in behaviors that are repeated in time and that can be symptoms of disease’s relapse.
Tampere, January 30th B. 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 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Activity recognitionActivity recognition
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Emotion RecognitionEmotion Recognition
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Discussion and future workDiscussion and future work We have shown a feasibility study on applying existing pervasive computing
techniques to support the early diagnosis of bipolar disorder We have formulated proper system requirements, showing then how current
research and authors’ expertise can be leveraged for helping doctors and patients in recognizing early symptoms of depression and mania
We have also defined a system architecture meeting such requirements Future work:
Refine the P-cube platform implementation for the bipolar disorder scenario Integrate the implementation with indoor environment (e.g. Living Lab at Create-
Net) including hand-over between outdoors and indoors Integrate the context recognition platforms we have in the context data block Continue in a close cooperation with doctors to define proper UI and medical
records Test-bed trials to refine the system (in cooperation with doctors) Start working with patients for developing a first proof of concept of the proposed
system
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Back-up slides: Mania SymptomsBack-up slides: Mania Symptoms Increased energy, activity, and restlessness Excessively "high," overly good, euphoric mood Extreme irritability Racing thoughts and talking very fast, jumping from one idea to another Distractibility, can't concentrate well Little sleep needed Unrealistic beliefs in one's abilities and powers Poor judgment Spending sprees A lasting period of behavior that is different from usual Increased sexual drive Abuse of drugs, particularly cocaine, alcohol, and sleeping medications Provocative, intrusive, or aggressive behavior Denial that anything is wrong
List taken from: http://www.nimh.nih.gov/publicat/bipolar.cfm
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Back-up slides: Depression SymptomsBack-up slides: Depression Symptoms Lasting sad, anxious, or empty mood Feelings of hopelessness or pessimism Feelings of guilt, worthlessness, or helplessness Loss of interest or pleasure in activities once enjoyed, including sex Decreased energy, a feeling of fatigue or of being "slowed down" Difficulty concentrating, remembering, making decisions Restlessness or irritability Sleeping too much, or can't sleep Change in appetite and/or unintended weight loss or gain Chronic pain or other persistent bodily symptoms that are not caused by
physical illness or injury Thoughts of death or suicide, or suicide attempts
iopList taken from: http://www.nimh.nih.gov/publicat/bipolar.cfm
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Existing devices: Existing devices: QBIC Belt Integrated ComputerQBIC Belt Integrated Computer
Key Features XScale CPU up to 400Mhz 256 MB SDRAM Low power Standard interfaces (USB,
Serial, VGA, Bluetooth)
Applications Data recording with on-line
processing and communication
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Existing devices: SensorbuttonExisting devices: Sensorbutton
SensorsAccelerometers, light
sensor, microphone, microprocessor
ApplicationsOn-line context
recognition
Algorithmsnearest-neighbor and
C4.5 decision tree
Tampere, January 30th B. Arnrich
Activity and Emotion Recognition to Support Early Diagnosis of Psychiatric Diseases
Existing devices: Textile Pressure SensorExisting devices: Textile Pressure Sensor
Pure textile, capacitive sensor
Individually connected electrodes using silver coated yarn
Localized detection of pressure distribution