Unsupervised Analysis of Daily Routine Evolution for Elderly People Using Room-Level Localisation.

This work proposes the use of room-level or symbolic localisation for the analysis of the daily life of elderly people. The elderly people tend to be quite routine, so variations in behaviour patterns can be an indication of physical or cognitive impairment. Then, it is essential to develop solutions for the early detection of changes or anomalies that can be the onset of physical or cognitive impairment. In this work, the behaviour of the monitored person is modelled by the probability of staying in each room of their place of residence. The proposed system is based on the generation of a baseline behaviour, defined by groups of similar days during an initial training period. From this model, each new day is compared with the baseline behaviour and the evolution is analysed. Two databases are used for the evaluation of the proposed system: a real database and a synthetic one. The initial results are very promising, being possible to classify location-based daily activities as main and secondary routines, detecting when a day is considered unusual.