Detecting Changes in Elderly's Mobility Using Inactivity Profiles

Abnormal inactivity indicates situations, where elderly need assistance. Systems detecting the need for help models the amount of inactivity using inactivity profiles. Depending on the analysis of the profiles, events (e.g. falls) or long-term changes (decrease of mobility) are detected. Until now, inactivity profiles are only used to detect abnormal behavior on the short-term (e.g. fall, illness), but not on the long-term. Hence, this work introduces an approach to detect significant changes on mobility using long-term inactivity profiles, since these changes indicate enhanced or decreased mobility of elderly. Preliminary results are obtained by the analysis of the motion data of an elderly couple over the duration of 100 days and illustrates the feasibility of this approach.