Research Article
Detecting Elderly Behavior Shift via Smart Devices and Stigmergic Receptive Fields
@INPROCEEDINGS{10.1007/978-3-319-58877-3_50, author={Marco Avvenuti and Cinzia Bernardeschi and Mario Cimino and Guglielmo Cola and Andrea Domenici and Gigliola Vaglini}, title={Detecting Elderly Behavior Shift via Smart Devices and Stigmergic Receptive Fields}, proceedings={Wireless Mobile Communication and Healthcare. 6th International Conference, MobiHealth 2016, Milan, Italy, November 14-16, 2016, Proceedings}, proceedings_a={MOBIHEALTH}, year={2017}, month={6}, keywords={Elderly monitoring Smart sensing Stigmergy Neural receptive field User’s behavior shift}, doi={10.1007/978-3-319-58877-3_50} }- Marco Avvenuti
Cinzia Bernardeschi
Mario Cimino
Guglielmo Cola
Andrea Domenici
Gigliola Vaglini
Year: 2017
Detecting Elderly Behavior Shift via Smart Devices and Stigmergic Receptive Fields
MOBIHEALTH
Springer
DOI: 10.1007/978-3-319-58877-3_50
Abstract
Smart devices are increasingly used for health monitoring. We present a novel connectionist architecture to detect elderly from data gathered by wearable or ambient sensing technology. Behavior shift is a pattern used in many applications: it may indicate initial signs of disease or deviations in performance. In the proposed architecture, the input samples are aggregated by functional structures called . The trailing process is inspired by , an insects’ coordination mechanism, and is managed by computational units called (SRFs), which provide a (dis-)similarity measure between sample streams. This paper presents the architectural view, and summarizes the achievements related to three application case studies, i.e., indoor mobility behavior, sleep behavior, and physical activity behavior.