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