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A Wearable Electrostatic Sensor for Human Activity Monitoring

Hu, Yonghui, Yan, Yong (2022) A Wearable Electrostatic Sensor for Human Activity Monitoring. IEEE Transactions on Instrumentation and Measurement, 71 . Article Number 4009410. ISSN 0018-9456. (doi:10.1109/TIM.2022.3214295) (KAR id:97220)

Abstract

Human activity monitoring based on wearable sensors is important in a wide range of biomedical and healthcare applications. Existing wearable sensors using a single unit cannot capture the movements of all body segments. This paper presents a novel wearable electrostatic sensor that can detect limb and torso movements during routine daily activities from any location on the body. Because the electric potential of the human body varies during movements, the sensor measures the potential difference between the body and the electrode for motion sensing. A charge amplifier converts the induced charge on the electrode into a voltage signal, which is further amplified, filtered, digitalized and transmitted via ZigBee. Experimental assessment was carried out by collecting sensor signals from three locations simultaneously while the subject performing different movements. The capability of the sensor to capture limb and torso movements from any location is validated. The characteristics of the sensor are quantified by correlating the sensor signal to simple and cyclic movements. It is found that the sensor signal depends on the sensor’s mounting location on the body, the type of activity and various factors.

Item Type: Article
DOI/Identification number: 10.1109/TIM.2022.3214295
Uncontrolled keywords: Wearable sensor, electrostatic sensor, human activity monitoring, capacitive coupling, charge amplifier
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA165 Engineering instruments, meters etc. Industrial instrumentation
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Yong Yan
Date Deposited: 30 Sep 2022 13:56 UTC
Last Modified: 01 Mar 2023 12:55 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/97220 (The current URI for this page, for reference purposes)

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