A smart glove to track fitness exercises by reading hand palm

A. H.Elder Akpa, Masashi Fujiwara, Hirohiko Suwa, Yutaka Arakawa, Keiichi Yasumoto

研究成果: Contribution to journalArticle査読

3 被引用数 (Scopus)

抄録

Medical studies have intensively demonstrated that sports activity can enhance both the mental and the physical health of practitioners. In recent years, fitness activity became the most common way to motivate and engage people in sports activity. Recently, there have been multiple attempts to elaborate on the “ideal” IoT-based solution to track and assess these fitness activities. Most fitness activities (except aerobic activities like running) involve one or multiple interactions between the athlete's hand palms and body or between the hand palms and the workout materials. In this work, we present our idea to exploit these biomechanical interactions of the hand palms to track fitness activities via a smart glove. Our smart glove-based system integrates force-sensitive resistor (FSR) sensors into wearable fitness gloves to identify and count fitness activity, by analyzing the time series of the pressure distribution in the hand palms observed during fitness sessions. To assess the performance of our proposed system, we conducted an experimental study with 10 participants over 10 common fitness activities. For the user-dependent activity recognition case, the experimental results showed 88.90% of the F score for overall activity recognition. The result of leave-one-participant-out cross-validation showed an F score ranging from 58.30% to 100%, with an average of 82.00%. For the exercise repetition count, the system achieved an average counting error of 9.85%, with a standard deviation of 1.38.

本文言語英語
論文番号9320145
ジャーナルJournal of Sensors
2019
DOI
出版ステータス出版済み - 1 1 2019

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Instrumentation
  • Electrical and Electronic Engineering

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