Towards smartphone-based sensing of social interaction for ambulatory assessment
Anja Bachmann · 2015
In ambulatory assessment, especially when handling subjects with personality disorders, it is important to monitor the subject's social interactions. Smartphones are already applied to assess information via self-reports. Related work also uses them to log context information or prompt event-specific self-reports. We see a high potential for them to be used for monitoring social interactions in in-field studies as they are constant companions in real life and a platform for virtual interactions. Our system will apply pattern recognition and machine learning algorithms to physical sensor measurements such as microphone and radio signals, but also to virtual sensor information such as call and message history and activity of messaging apps. We will evaluate to which extent and how well our system can automatically and unobtrusively find indicators for social interactions and, based on them, identify anomalies in the subject's behavior.