A Low-Cost Smart Glove System for Real-time Fitness Coaching

Yongpan ZOU, Dan WANG, Shicong HONG, Rukhsana RUBY, Dian ZHANG, Kaishun WU*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

27 Citations (Scopus)

Abstract

Strength training is becoming increasingly popular among all age groups, as it helps participants increase muscle strength, improve body flexibility, reduce health risks and reshape physical forms. However, strength training imposes strict regulations on gestures and requires professional instruction in real time for the sake of body-building efficiency and safety. For this purpose, in this paper, we propose a novel low-cost system named iCoach, to provide real-time monitoring and coaching service for strength training participants. Specifically, we design and implement a smart fitness glove, which can be seamlessly equipped with a pervasive inertial unit. With this customized but low-cost device, we can recognize various training programs, detect non-standard behaviors while exercising, and assess exercising qualities of a user. Our primary experimental results show that iCoach can recognize fifteen sets of training programs, detect three common non-standard behaviors and assess the quality of training with high accuracy and reliability.
Original languageEnglish
Article number9046259
Pages (from-to)7377-7391
Number of pages15
JournalIEEE Internet of Things Journal
Volume7
Issue number8
Early online date24 Mar 2020
DOIs
Publication statusPublished - Aug 2020

Bibliographical note

We really appreciate the kind effort of the AE and anonymous reviewers, for giving precious suggestions to improve the manuscript. This research was supported in part by the China NSFC Grant (61802264, 61872248, U1736207), Shenzhen Science and Technology Foundation (No. JCYJ20180305124807337, No. ZDSYS20190902092853047), Guangdong NSF 2017A030312008, Fok Ying-Tong Education Foundation for Young Teachers in the Higher Education Institutions of China (Grant No. 161064), GDUPS (2015), and Natural Science Foundation of SZU (No. 860-000002110537, No. 827-000175).

Keywords

  • Inertial measurement unit (IMU)
  • strength training
  • training exercise assessment

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