Wearable Accelerometer Optimal Positions for Human Motion Recognition

Chengshuo Xia, Yuta Sugiura

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

An intelligent human activity recognition system is influenced to some extent by sensor placement. In this paper, the number, and placement positions, of wearable accelerometers have been investigated to determine their influence on a human activity recognition system. Given 17 possible human sensor placements, we developed a multi-stage and multi-swarm discrete particle swarm optimization algorithm to explore the optimal sensor combination for various required sensor amounts. Relevant experimentation involved 10 different human daily activities, achieving an average prediction accuracy for a 4-sensor optimal combination of 95.12% via support vector machine classifier. The number and corresponding placement of sensors required for activity recognition have also been provided in this paper.

本文言語English
ホスト出版物のタイトルLifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies
出版社Institute of Electrical and Electronics Engineers Inc.
ページ19-20
ページ数2
ISBN(電子版)9781728170633
DOI
出版ステータスPublished - 2020 3
イベント2nd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2020 - Kyoto, Japan
継続期間: 2020 3 102020 3 12

出版物シリーズ

名前LifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies

Conference

Conference2nd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2020
CountryJapan
CityKyoto
Period20/3/1020/3/12

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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