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Article

A Framework for Detecting and Analyzing Behavior Changes of Elderly People over Time Using Learning Techniques

1
LAMIH UMR CNRS 8201, Université Polytechnique Hauts-de-France, 59300 Valenciennes, France
2
ReDCAD Laboratory, University of Sfax, B.P. 1173, 3029 Sfax, Tunisia
3
IMT Lille Douai, Digital Systems Center, Institut Mines-Telecom, University of Lille, 59000 Lille, France
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(24), 7112; https://doi.org/10.3390/s20247112
Received: 4 November 2020 / Revised: 7 December 2020 / Accepted: 9 December 2020 / Published: 11 December 2020
A sensor-rich environment can be exploited for elder healthcare applications. In this work, our objective was to conduct a continuous and long-term analysis of elderly’s behavior for detecting changes. We indeed did not study snapshots of the behavior but, rather, analyzed the overall behavior evolution over long periods of time in order to detect anomalies. Therefore, we proposed a learning method and formalize a normal behavior pattern for elderly people related to her/his Activities of Daily Living (ADL). We also defined a temporal similarity score between activities that allows detecting behavior changes over time. During the periods of time when behavior changes occurred, we then focused on each activity to identify anomalies. Finally, when a behavior change occurred, it was also necessary to help caregivers and/or family members understand the possible pathology detected in order for them to react accordingly. Therefore, the framework presented in this article includes a fuzzy logic-based decision support system that provides information about the suspected disease and its severity. View Full-Text
Keywords: behavior change observation; elderly people; smart home; activities of daily living; decision support system; fuzzy logic system behavior change observation; elderly people; smart home; activities of daily living; decision support system; fuzzy logic system
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MDPI and ACS Style

Zekri, D.; Delot, T.; Thilliez, M.; Lecomte, S.; Desertot, M. A Framework for Detecting and Analyzing Behavior Changes of Elderly People over Time Using Learning Techniques. Sensors 2020, 20, 7112. https://doi.org/10.3390/s20247112

AMA Style

Zekri D, Delot T, Thilliez M, Lecomte S, Desertot M. A Framework for Detecting and Analyzing Behavior Changes of Elderly People over Time Using Learning Techniques. Sensors. 2020; 20(24):7112. https://doi.org/10.3390/s20247112

Chicago/Turabian Style

Zekri, Dorsaf, Thierry Delot, Marie Thilliez, Sylvain Lecomte, and Mikael Desertot. 2020. "A Framework for Detecting and Analyzing Behavior Changes of Elderly People over Time Using Learning Techniques" Sensors 20, no. 24: 7112. https://doi.org/10.3390/s20247112

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