Motion factors related to joint contact force of the lower extremity during gait

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K11445
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 59030:Physical education, and physical and health education-related
• Research Institution: Kagawa University
• Principal Investigator: Inoue Koh 香川大学, 創造工学部, 講師 (90624205)
• Co-Investigator(Kenkyū-buntansha): 松岡 諒 北九州市立大学, 国際環境工学部, 准教授 (40780391)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 歩行 / 筋骨格モデル / 関節面接触力

Outline of Final Research Achievements

The analysis of human walking motion with a musculoskeletal model revealed that extending the knee joint during the stance phase is an effective strategy for reducing knee joint contact force. To eliminate subjectivity in proposing strategies, a machine learning model was developed to estimate contact force based on whole-body motion information. The visualization technology identified the lower and upper extremities as the body parts that significantly contributed to the estimation. The result of the lower extremity supports the validity of maintaining the knee joint angle as a strategy. Moreover, it is suggested that the estimation of contact force and the potential for modifying it could be inferred from the motion of the upper limbs.

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Academic Significance and Societal Importance of the Research Achievements

本研究の成果は、関節における傷害や疾病によって生涯にわたる歩行の継続が阻害されるリスクの低減に貢献する。学術的には、研究者の経験に基づいてシミュレーション的に提案された動作方略が、実際のヒトの歩行動作で実現可能か検証している。そして、方略の選定において研究者の主観によらない機械学習による網羅的な調査を行い、上記方略の有用性や別の方略の可能性を示している。また、筋骨格モデルでの分析から、同手法の限界を示すと共に、改善方法の提案と実証実験に至っている。