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Depression is a major public health issue with directand significant effects on both physical and mental health. In thisstudy, we analyze smartphone sensing data to find differentialbehavioral features that are correlated with depression measuressuch as patient health questionnaire (PHQ-9). Our approachuses an innovative multi-view bi-clustering algorithm. It takesmultiple views of sensing data as...
In this paper we present a classification of human movement in physical space into spatio-temporal activities (STAs) and classes thereof. Drawing from our experiences with real human data from GPS traces we define a clustering approach for STA extraction based on the amount of motion of the user in space and time. Our solution captures these properties in a lightweight online algorithm that can run...
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