title: Behaviour monitoring of the elderly by trajectories analysis.
abstract: This paper presents a way to keep the elderly autonomous in their daily activities. The principle is to monitor their behaviour and more specifically their trajectories of movement in the living area. Two methods have been developed and compared: supervised and unsupervised classification. Some results from data collected in a long-stay setting are shown. They highlight the possibility of determining normal trajectory classes, and by comparison with the usual situation, to trigger alarms when the trajectories are unusual.
authors.affiliation: LAAS-CNRS Laboratoire d'Analyse et d'Architecture des Systèmes, Toulouse, France. campo@laas.fr
authors.forename: Eric
authors.initials: E
authors.lastname: Campo
authors.forename: Marie
authors.initials: M
authors.lastname: Chan
authors.forename: Walid
authors.initials: W
authors.lastname: Bourennane
authors.forename: Daniel
authors.initials: D
authors.lastname: Esteve
mesh_terms: D000203:Activities of Daily Living; D000204:Activity Cycles; D000368:Aged; D000465:Algorithms; D001519:Behavior; D015374:Biosensing Techniques; D004867:Equipment Design; D006299:Health Services for the Aged; D006801:Humans; D018670:Monitoring, Ambulatory / Q000379:methods*; D009068:Movement; D012146:Rest; D012890:Sleep; D016138:Walking / Q000502:physiology