Combining Spatial and Temporal Information for Inactivity Modeling

Unusual inactivity is caused by events, where elderly need help (e.g., falls, illness). In order to detect unusual behavior, modeling of activity results in inactivity profiles. State-of-the-Art approaches focus on temporal aspects of inactivity by only considering deviations of inactivity over time. This work proposes the use of spatial information in combination with temporal aspects to enhance the robustness and reduce the number of false alarms. The proposed approach is evaluated on two different datasets containing 100 days resp. 50 days of activity data of elderly people and results are compared to the State-of-the-Art.