Physical activity group classification algorithm using triaxial acceleration and heart rate

Motofumi Nakanishi, Shintaro Izumi, Sho Nagayoshi, Hironori Sato, Hiroshi Kawaguchi, Masahiko Yoshimoto, Takafumi Ando, Satoshi Nakae, Chiyoko Usui, Tomoko Aoyama, Shigeho Tanaka

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

As described in this paper, a physical activity classification algorithm is proposed for energy expenditure estimation. The proposed algorithm can improve the classification accuracy using both the triaxial acceleration and heart rate. The optimal classification also contributes to improvement of the accuracy of the energy expenditures estimation. The proposed algorithm employs three indices: the heart rate reserve (%HRreserve), the filtered triaxial acceleration, and the ratio of filtered and unfiltered acceleration. The percentage HRreserve is calculated using the heart rate at rest condition and the maximum heart rate, which is calculated using Karvonen Formula. Using these three indices, a decision tree is constructed to classify physical activities into five classes: sedentary, household, moderate (excluding locomotive), locomotive, and vigorous. Evaluation results show that the average classification accuracy for 21 activities is 91%.

本文言語English
ホスト出版物のタイトル2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
出版社Institute of Electrical and Electronics Engineers Inc.
ページ510-513
ページ数4
ISBN(電子版)9781424492718
DOI
出版ステータスPublished - 2015 11 4
外部発表はい
イベント37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
継続期間: 2015 8 252015 8 29

出版物シリーズ

名前Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
2015-November
ISSN(印刷版)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
国/地域Italy
CityMilan
Period15/8/2515/8/29

ASJC Scopus subject areas

  • 信号処理
  • 生体医工学
  • コンピュータ ビジョンおよびパターン認識
  • 健康情報学

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