PREDICTION OF WALKING TURNS FOCUSING ON THE CENTER OF GRAVITY

• SUGIMOTO Nene

  Keio Univ.

• OGAWA Ami

  Keio Univ.

• MITA Akira

  Keio Univ.

Bibliographic Information

Other Title

• 重心に着目した歩行中の方向転換動作の予測

Abstract

This study revealed proper parameters to predict walking turns to-support the residents as a built environment function. We used a non contact sensor that did not disturb everyday life and aimed to extract highly versatile prediction parameters by considering the movement strategy and the rotation direction. After carefully examining the prediction accuracy for the center-of-gravity shift and the head and upper body rotation parameters, we found the position of the head’s center-of-gravity (Left-Right) and the head rotation (Yaw) were valuable indicators. The time needed for prediction was between 0.18 to 0.48 steps with a prediction accuracy of 70%.

Journal

• AIJ Journal of Technology and Design

  AIJ Journal of Technology and Design 28 (68), 510-514, 2022-02-20

  Architectural Institute of Japan

Keywords

• Motion prediction
• Turning
• Biofied building
• Azure Kinect DK
• Non-contact sensor

Details

• CRID: 1390854107986905344
• NII Article ID: 130008162051
• DOI: 10.3130/aijt.28.510
• ISSN: 18818188
• ISSN: 13419463
• Web Site: https://www.jstage.jst.go.jp/article/aijt/28/68/28_510/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed