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2019 | OriginalPaper | Buchkapitel

TaRad: A Thing-Centric Sensing System for Detecting Activities of Daily Living

verfasst von : Haiming Chen, Xiwen Liu, Ze Zhao, Giuseppe Aceto, Antonio Pescapè

Erschienen in: Internet and Distributed Computing Systems

Verlag: Springer International Publishing

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Abstract

Activities of Daily Living Scale (ADLs) is widely used to evaluate living abilities of the patients and the elderly. Most of the currently proposed approaches for tracking indicators of ADLs are human-centric. Considering the privacy concerns of the human-centric approaches, a new thing-centric sensing system, named TaRad, for detecting some indicators of ADLs (i.e. using fridge, making a phone call), through identifying vibration of objects when a person interacts with objects. It consists of action transceivers (named ViNode), smart phones and a server. By taking into account the limited computation resource of the action transceiver, and the drift and accuracy issues of the cheap sensor, a method of extracting features from the vibration signal, named ViFE, along with a light-weight activity recognition method, named ViAR, have been implemented in ViNode. Besides, an operator recognition method, named ViOR, has been proposed to recognize the acting person who generates vibration of action transceiver, when two or more people exist simultaneously within an area. Experimental results verify the performance of TaRad with different persons, in terms of the sensitivity to correctly detect the activities, and probability to successfully recognize the operators of the activities.

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Metadaten
Titel
TaRad: A Thing-Centric Sensing System for Detecting Activities of Daily Living
verfasst von
Haiming Chen
Xiwen Liu
Ze Zhao
Giuseppe Aceto
Antonio Pescapè
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-34914-1_34

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