Using sensor patterns to predict a depression or addiction relapse - Jan Peter Larsen
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Using sensor patterns to predict a depression or addiction relapse - Jan Peter Larsen
- 1. Towards an application for depression and addiction relapse prevention
- 3. Complexity Sociological Psychological Biological
- 4. Question from doctors • Collect objective data on all three levels (biological, psychological, sociological) • Collect data continuously
- 5. CommonSense - Storage - Interpret - Visualisation - Predict - Sharing - Triggers - Combine - Learning
- 6. Growing functionality • Measuring data • Pattern analysis – Converting sensor data into behaviour data – Higher level patterns for correlation and forecasting • Interventions • Aggregation of data for research
- 7. Lessons learned • Sensordata from smartphones is very promising as useful data for monitoring people with depression and addiction • Dynamics of patterns is more in days and weeks, than in minutes / hours • All steps already have value as application • Next steps: – Testing with 60 patients for 4-6 weeks – Extending pattern recognition and intervention capabilities