期刊
IEEE INTERNET OF THINGS JOURNAL
卷 9, 期 23, 页码 24051-24064出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2022.3188916
关键词
Activity recognition; channel state information (CSI); gymnastics activity assessment; Wi-Fi sensing
资金
- NSFC [61772364, 61902211]
- NSF [ECCS-1923163]
This article introduces Wi-Gym, a gymnastics activity assessment system that utilizes Wi-Fi technology to compare the dynamic channel state information for evaluating the quality of training. Domain adaptation is also employed to adapt to environmental changes. Experimental results validate the effectiveness and robustness of the proposed approach.
Practicing gymnastics activities at home with online resources has become an increasingly popular choice due to its convenience and accessibility. However, without face-to-face guidance by a trainer, a major challenge is how to assess the quality of performed gymnastics activities, effectively and fairly. Existing intrusive assessing approaches usually require live cameras or wearable sensors, which usually generate privacy and feasibility concerns. There is a lacking of accurate approaches to assess the quality of the activities. To address these challenges, a gymnastics activity assessment approach is proposed in this article, and Wi-Gym, an effective first-of-its-kind gymnastics activity assessment system is developed utilizing commodity Wi-Fi. Wi-Gym is designed to compare the activity-induced channel state information (CSI) dynamics by an exerciser and that of a trainer utilizing dynamic time warping (DTW). The comparison results are provided by a fuzzy inference system (FIS). To make Wi-Gym robust to the changes in the environment, domain adaptation is leveraged to mitigate the data distribution imbalance caused by the environment changes. Extensive experimental studies have been conducted using Wi-Gym, acoustic, and video-based sensing systems. The experimental results validate the effectiveness and robustness of the proposed approach.
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