AUTHOR=Yu Lin , Jiang Hanhui , Mei Qichang , Mohamad Nur Ikhwan , Fernandez Justin , Gu Yaodong TITLE=Intelligent prediction of lower extremity loadings during badminton lunge footwork in a lab-simulated court JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=Volume 11 - 2023 YEAR=2023 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2023.1229574 DOI=10.3389/fbioe.2023.1229574 ISSN=2296-4185 ABSTRACT=Badminton playing has been reported with extensive health benefits, while main injuries were documented in the lower extremity. This study was aimed to investigate and predict the knee and ankle joint loadings of badminton athletes with 'gold-standard' facilities. The axial impact acceleration from wearables would be employed to predict joint moments and contact forces during sub-maximal and maximal lunges footwork.Twenty-five badminton athletes participated this study, following a previously established protocol of motion capture and musculoskeletal modelling techniques with integration of wearable IMU (Inertial Magnetic Unit). Authors developed a Principal Component Analysis (PCA) statistical model to extract features in the loading parameters, and a multivariate Partial Least Square Regression (PLSR) machine learning model was employed to correlate easily collected variables, such as the stance time, approaching velocity, and peak accelerations, with knee and ankle loading parameters (moments and contact forces). Key variances of joint loadings were observed from statistical PCA modelling. Promising accuracy of the PLSR model using the input parameters was observed with a prediction accuracy of 94.52%, further sensitivity analysis found a single variable from ankle IMU could predict an acceptable range (93%) of patterns and magnitudes of knee and ankle loadings. The attachment of this single IMU sensor could be employed to record and predict loading accumulation and distribution, and placement would exert little influence for the motions of the lower extremity. The intelligent prediction of loading patterns and accumulation could be integrated to design training and competition schemes in badminton or other court sports with a scientific manner, thus preventing fatigue, reducing loading-accumulation related injury, and maximizing athletic performance.