投球動作から病変を予測するシミュレーションシステムの開発

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Background: We reported that the humeral head abnormality and the subacromial bursitis at asymptomatic phase were the lesions which were near-related to the consecutive onset of throwing shoulder injury. We also developed the lesion prediction system using dynamic analysis of pitching motion. However, in this system there were some problems in making the pitching motion efficiently. The purpose of this study is to develop a new system that can predict the lesions easily and can simulate the new pitching motion which prevents the lesion efficiently. Methods: The subjects were 18 asymptomatic collegiate baseball players who took part in both MRI and pitching motion analysis. We analyzed the data of 26 joint angles during pitching motion with principal component analysis and classified the motion patterns into the principal component scores. We did logistic regression analysis with the lesions on MRI and the principal component scores and found out the principal components which significantly affected the lesion. We also calculated regression formula which predict the probability of the lesion existence and evaluated the validity of the regression model. Results: We could calculate regression formula which predict the lesion existence with high accuracy. We can make the new pitching motion easily while we operate the parameters of principal component scores referring to the probability of the lesion existence. We can express the new motion with 3D animations. Conclusion: We developed the system that could predict the humeral head abnormality and the subacromial bursitis and could simulate new pitching motions which prevents the lesion effectively.

投球動作から病変を予測するシミュレーションシステムの開発

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