Data Fusion for Analysis of Persistence in Pervasive Actimetry of Elderly People at Home, and the Notion of Biological Age

Abstract

If we watch elderly people at home for health or security purposes, we need a reliable pervasive information from a domestic network of localizing sensors allowing to follow the different locations at which the dependent persons can be detected. The data recorded can be treated as the sequence of color coded numbers of balls (symbolizing rooms) taken in a Polya's urn, in which the persistence of the presence in a room is taken into account by adding a certain number of balls of the same color as the ball just drawn. We discuss the pertinency of such a procedure to early detect sudden or chronic changes in the parameters values of the random process made of the succession of ball numbers and we use it to trigger alarms, whose level depends on the real biological age of the elderly people watched at home.

Pervasive Informatics and Persistent Actimetric Information in Health Smart Homes: From Language Model to Location Model

“…If E i,1 is in the confidence interval of E i,3 , then we should use this Markovian model due to its simplicity (despite Polya's urns approach is available [6]). It it is not the case, the same work has to be done for Polya's urns approach.…”

“…The Polya's urn model has been precisely described in [6]. We will focus now on the description of the first order Markov chain model and its generalization by the n-grams approach proposed.…”

“…The first one, described more precisely in [6] use Polya's urns. The second one is a statistical approach based on n-grams including two back-offs levels.…”

“…Two modelling approaches Among the possible approaches for modelling the actimetric data, two methods have been selected. The first one focus on the Polya's urns [6] in which the observed activity at time t is depending on the whole past (since a reset supposed to be made at the beginning of each day). The second one concerns a first order Markov chain approach in which the dependency of the future of t lies only through the present time t. In both models, a persistence parameter is defined.…”

Telemonitoring of the Elderly at Home: Real-Time Pervasive Follow-up of Daily Routine, Automatic Detection of Outliers and Drifts

“…each second here), a ball is withdrawn, its colour pointed out and the ball is put back in the urn along with additional balls of the same colour (Fig 4.). This last feature is precisely the way we chose to represent the persistence of an action/a location (Demongeot et al 2008. In this approach, the persistence in task i parameter � � (t) is the ratio between the number k i (t) of balls of colour i added after the withdrawing of a ball of colour i at time t and the initial total number of balls b 0 unknown a priori .…”