GIFT: Glove for Indoor Fitness Tracking System

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

It has been intensively demonstrated that physical activity can enhance the mental and physical health of practitioners. In recent years, fitness activities became the most common way to engage in physical activities. In this paper, we propose a smart-glove based fitness activity tracking system that can detect athletes activities in any indoor fitness facility, with no need of attaching multiple sensors on the athlete's body. The system adopts force sensitive resistor (FSR) sensors to identify the type of exercise by analyzing the pressure distribution in the hand palm during fitness activities. To evaluate the performance of our proposed system, we ran a pilot study with 10 healthy participants over 10 common fitness activities. The experimental results showed an overall recognition accuracy rate of 87%. We believe the promising results would contribute to the works on personal assisted coaching systems and create enjoyable experiences when performing fitness activities.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages52-57
Number of pages6
ISBN (Electronic)9781538632277
DOIs
Publication statusPublished - Oct 2 2018
Externally publishedYes
Event2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018 - Athens, Greece
Duration: Mar 19 2018Mar 23 2018

Publication series

Name2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018

Conference

Conference2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
CountryGreece
CityAthens
Period3/19/183/23/18

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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