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Updated: Jul 5, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
Published on: December 11, 2015
A DSL-Based Approach for Detecting Activities of Daily Living by Means of the AGGIR Variables
José Manuel Negrete Ramírez1, Philippe Roose2, Marc Dalmau2
1LIFO, Institut National des Sciences Appliquées Centre Val de Loire, Université d'Orléans, 18000 Bourges, France.
Abstract:
In this paper, we propose a framework for studying the AGGIR (Autonomie Gérontologique et Groupe Iso Ressources-Autonomy Gerontology Iso-Resources Groups) grid model, with the aim of assessing the level of independence of elderly people in accordance with their capabilities of performing daily activities as well as interacting with their environments. In order to model the Activities of Daily Living (ADL), we extend a previously proposed Domain Specific Language (DSL), by defining new operators to deal with constraints related to time and location of activities and event recognition. The proposed framework aims at providing an analysis tool regarding the performance of elderly/disabled people within a home environment by means of data recovered from sensors using a smart-home simulator environment. We perform an evaluation of our framework in several scenarios, considering five of the AGGIR variables (i.e., feeding, dressing, toileting, elimination, and transfers) as well as health-care devices for tracking the occurrence of elderly activities. The results demonstrate the accuracy of the proposed framework for managing the tracked records correctly and, thus, generate the appropriate event information related to the ADL.
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