2022 Fiscal Year Final Research Report
Skill Assessment on Pedaling Exercise by using Muscular Synergy and Artificial Intelligence
| Project/Area Number |
20K11408
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 59020:Sports sciences-related
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| Research Institution | Fukuoka Institute of Technology |
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Principal Investigator |
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | ペダリング運動 / 機械学習 / 筋シナジー |
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| Outline of Final Research Achievements |
This study aimed to understand the pedaling techniques in competitive cycling by visualizing the features of muscle synergy in two dimensions and using machine learning to compare novice and expert groups. The proposed method revealed that the key technique separating the two groups was the upward motion. However, there were individual differences in the characteristics of the muscle activity involved in pedaling, which prevented the numerical evaluation of pedaling techniques. Furthermore, in order to fully understand pedaling techniques, it is necessary to continuously and multidimensionally evaluate body movements under dynamic riding conditions, as approaches using data measurement in the laboratory or surface electromyography have limitations.
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| Free Research Field |
スポーツ科学
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| Academic Significance and Societal Importance of the Research Achievements |
SDGsや物価上昇により，我が国の自転車利用者数は今後も増え続け，競技者も増えてくることが予想される．昨今，我が国の自転車ロードレースはプロチームによるリーグ戦が開催され，Youtubeなどで配信されるようになり，一時期よりも盛り上がりを見せているが，肝心の競技力については底上げがなされているとは言い難い．本研究の成果を通して，自転車競技力の向上にはペダリング運動における引き足動作への意識が重要であり，それをスムーズに行うためには自身の骨格や筋力など身体的特徴に応じた自転車のセッティングが必要であることがわかった．
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