PRISM: A data-driven platform for monitoring mental health
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Talk presented at the 21st Pacific Symposium on Biocomputing Conference, Big Island of Hawaii, January 2016. Video Screencast: https://www.youtube.com/watch?v=IPVmu0bCmMU
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PRISM: A data-driven platform for monitoring mental health
- 1. PRISM: A DATA-DRIVEN PLATFORM FOR MONITORING MENTAL HEALTH Maulik Kamdar & Michelle Wu 21st Pacific Symposium on Biocomputing Big Island of Hawaii || January 4-8th, 2016
- 2. THE BURDEN OF MENTAL HEALTH Prince, M. et al. "No health without mental health." The lancet (2007).
- 3. THE STATE OF THE ART IN MENTAL HEALTH DIAGNOSIS American Psychiatric Association DSM-5 Task Force. "Diagnostic and statistical manual of mental disorders. 5th edition." (2013).
- 7. A BRIEF PILOT STUDY ➢ 13 anonymized participants ➢ Gear S watch ○ UV light, ambient light, heart rate, accelerometer, pedometer ➢ Brain Health Web Application ○ blog entry, keyboard Interactions, mouse interactions predicted energy level observedenergylevel
- 9. ACKNOWLEDGEMENTS Zeshan Hussain Dave Stark Tim SweeneyRuss Altman Steve Bagley Pilot participants
- 10. THANK YOU! maulikrk@stanford.edu · mjwu@stanford.edu
Notas del editor
- Good morning everyone! Maulik and I will be telling you about the platform we built called PRISM, which aims to take a data-driven approach for monitoring mental health.
- We believe that the burden of mental health is often underestimated because people focus on mortality ratesas a quantitative measure of disease burden. here we show DALYs, disability adjusted life years, a measure developed by the WHO which intends to capture the number of years of healthy life lost. You can see that neuropsychiatric disorders account for the largest proportion of DALYs lost, more than cardiovascular disease and cancer.
- Diagnosis of mental health is often problematic because it is extremely subjective. The state of the art in mental health diagnosis is described in the diagnostic and statistical manual of mental disorders, or DSM-5, which is largely based on surveys which are highly subjective. Espcially when compared directly to diagnostics for diseases such as cardiovascular disease and cancer, there are no clear physical indiciations or clinical tests to quantitatively characterize mental health. We believe that wearables provide a huge opportunity for passively monitoring mental health patients. A lot of owkr has been done for specific disease, such as seizures and sleep apnea. We would like to develop a generalized pipeline for data collection that could be applied to many disease
- 5 layers of architecture Security, Connectivity, Longevity
- Smart watch screen shot.
- keyboard interactions : key press time, interkey latency, speed, number of errors, number of presses - back keys, enter, Ctrl+Z mouse interactions: move speed, drag speed, clicks We engineered features based on these data to create models to predict the user reported ratings.
- We envision a future in which the smart devices that we carry with us in daily life will be able to detect abnormalities before we feel the effects of mental abnormalities, as exemplified by this comic. Data quality …
- Pilot study participants Dr. David Stark, Dr. Tim Sweeney Dr. Russ Altman, Dr. Steve Bagley Samsung Engineers Stanford Biomedical Informatics Training Program