Dynamic Motion Tracking Based on Point Cloud Matching with Personalized Body Segmentation

Tomoko Ono, Ryo Eguchi, Masaki Takahashi

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Falling is a serious problem with the growing elderly population. In this sense, clinical institutions have implemented motor function assessment programs. In particular, the timed up and go test (TUG) is the most frequently applied clinical trial to assess the elderly walking ability in many clinical institutions and communities. In this study, we proposed a gait measurement system that can evaluate motor function in dynamic gait tests, such as the TUG test, using the point clouds of depth sensors (Kinect). The TUG test is a dynamic task that includes 3m of walking and turning motion. However, estimating joint positions using conventional methods that use Kinect skeleton function or point clouds is difficult. To solve these problems, before applying the iterative closest point algorithm, we proposed a method to move the segment model to a pre-estimated position and perform matching. In the accuracy verification experiments of several young people, the average error of each joint position was less than approximately 0.03 m, and the average error of the knee angle was approximately 4.54 to 5.13 degrees. These results indicate that the values estimated by the proposed method are useful as values for evaluating clinical tasks.

本文言語English
ホスト出版物のタイトル2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
出版社IEEE Computer Society
ページ61-67
ページ数7
ISBN(電子版)9781728159072
DOI
出版ステータスPublished - 2020 11月
イベント8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020 - New York City, United States
継続期間: 2020 11月 292020 12月 1

出版物シリーズ

名前Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
2020-November
ISSN(印刷版)2155-1774

Conference

Conference8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
国/地域United States
CityNew York City
Period20/11/2920/12/1

ASJC Scopus subject areas

  • 人工知能
  • 生体医工学
  • 機械工学

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