Distinguishing working state by palm orientation

Kenta Hayashi, Shingo Kumazoe, Shigemi Ishida, Yutaka Arakawa

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

When working from home, self-management becomes of paramount importance due to the absence of a boss or colleagues. As a result, individuals tend to waste time surfing the internet and playing with our smartphones. We propose a wrist-worn sensor-based system that identifies whether a desk worker is working or not for self-management and productivity. Our main hypothesis is that the identification of the various tasks that occur during desk work, such as using computers, reading books, manipulating a smartphone, and writing, can be simply distinguished by the direction of the palm. In this paper, to verify our hypothesis, we measure various tasks with the wrist-worn sensor attached to clarify the relationship between hand orientation and each task. At the same time, we develop a machine learning-based classifier to distinguish between the states of’working’ and’not-working’ using the obtained hand orientation data. We performed 10-fold cross-validation and Leave-One-Person-Out validation and we found that it was possible to distinguish whether a desk worker is working or not with an F1-value of 0.8 or higher.

本文言語英語
ホスト出版物のタイトルLifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies
出版社Institute of Electrical and Electronics Engineers Inc.
ページ256-260
ページ数5
ISBN(電子版)9781665418751
DOI
出版ステータス出版済み - 3 9 2021
イベント3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021 - Nara, 日本
継続期間: 3 9 20213 11 2021

出版物シリーズ

名前LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies

会議

会議3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021
国/地域日本
CityNara
Period3/9/213/11/21

All Science Journal Classification (ASJC) codes

  • 生体医工学
  • 健康情報学
  • 健康(社会科学)
  • 生化学
  • 人工知能
  • コンピュータ サイエンスの応用

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