2022 Fiscal Year Final Research Report
Research on injury risk prediction of lower limbs using 3D range sensor
| Project/Area Number |
19K11487
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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 | University of Tsukuba |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
藤井 範久 筑波大学, 体育系, 教授 (10261786)
足立 和隆 筑波大学, 体育系, 准教授 (70221041)
福田 崇 筑波大学, 体育系, 准教授 (30375472)
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| Project Period (FY) |
2019-04-01 – 2023-03-31
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| Keywords | 障害予防 |
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| Outline of Final Research Achievements |
The purpose of this study was to collect daily gait data using a 3D distance measurement sensor and to be able to predict the risk of injury based on the changes in the data.
Although we were not able to obtain research results that could lead to the prediction of injury risk from the gait data within the study period, we were able to obtain the following results. (1) A measurement method and know-how to obtain gait data from about 40 research subjects in about 10 minutes, and (2) A measurement area setting method to obtain gait data without restricting athletes' daily activities at sports fields. In the future, we aim to analyze point cloud data of gait obtained from distance measurement sensors to obtain parameters that can be used to predict injuries based on the day-to-day fluctuations of gait data.
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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 |
通常，ヒトの運動を計測する場合には，身体各部にマーカーを貼付して高額な赤外線カメラを複数設置して撮影したり，ビデオカメラからの映像を用いて，マニュアルで関節位置を指定するデジタイズ作業を行なったりする必要がある．こうした方法では，研究対象者や研究者自身への負担が大きく，日常の活動データを継続的に取り続けることは難しい．
本研究では，比較的安価な測距センサーを用いることで，研究対象者への事前準備や，撮影後の手作業を減らし，日常の動作（歩行）からスポーツ活動中のケガの予測につながるデータを継続的に収集できる方法を確立することができた．
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