• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2023 Fiscal Year Final Research Report

Redundant strategy in motor learning process for preventing a fall from unstable movement

Research Project

  • PDF
Project/Area Number 21H03343
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Review Section Basic Section 59030:Physical education, and physical and health education-related
Research InstitutionKyoto University

Principal Investigator

Motoki Kouzaki  京都大学, 人間・環境学研究科, 教授 (30313167)

Project Period (FY) 2021-04-01 – 2024-03-31
Keywords運動制御 / 運動適応 / 筋シナジー / 相転移
Outline of Final Research Achievements

In order to clarify the motor control related to fall avoidance from unstable movements during the transition from standing to walking, 1) stepping movements in various directions while standing still, and 2) adaptation process of lower limb muscles for crossing over an obstacle at different height were investigated. 1) The weighting of muscle synergy differed depending on the direction in step motion. When a visual rotational disturbance was applied to the toe position in the forward direction, adaptation of lower limb motion was observed by adjusting muscle synergy activity. 2) It was observed that the obstacle clearance movement was controlled by the muscle synergy activation coefficient. These results suggest that the fall avoidance from unstable movements is simplified by muscle synergy, and that muscle synergy is involved in the adaptation process of movements.

Free Research Field

運動制御

Academic Significance and Societal Importance of the Research Achievements

高齢者の生活の質を損なう転倒は、歩行中のつまずきが原因とされている。歩行中のつまずきには、定常状態ではなく、歩行動作の相転移時の不安定動作に関連していると考えられるが、不安定動作時に関する歩行動作の研究は皆無であった。本研究は、立位から歩行への移行、歩行から障害物回避作への移行という不安定な歩行動作に着目した。これら本研究の検討により、不安定な歩行時の筋の協調構造およびその適応過程を明確になり、運動制御、神経生理学、ロボット工学の分野の研究が飛躍的に向上するという学術的意義がある。さらに、その知見を基に高齢者の転倒防止に関する提言を行うことが可能になるという大きな社会的意義がある。

URL: 

Published: 2025-01-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi