Building a spatial-temporal index to detect the global pattern deviations in daily activities of elderly subjects

To follow up the daily activities of elderly populations living independently in their home, is of central importance because the level and variety of activities performed reflect the correct functioning of their homeostasis, thus their health and well being. But the workers, in charge on the field for the remote follow up, need a ready to use and easy to interpret composite information. Our work aims at producing and evaluating this unique index, built from data fusion of heterogeneous information, such as the electrical activities on the power line.