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使用基于标记的3D运动捕捉技术对pitchAI无标记运动捕捉进行验证。

Validation of pitchAI markerless motion capture using marker-based 3D motion capture.

作者信息

Dobos Tyler J, Bench Ryan W G, McKinnon Colin D, Brady Anthony, Boddy Kyle J, Holmes Michael W R, Sonne Michael W L

机构信息

Department of Kinesiology, Brock University, St. Catharines, ON, Canada.

3MotionAI, Oakville, ON, Canada.

出版信息

Sports Biomech. 2022 Nov 21:1-21. doi: 10.1080/14763141.2022.2137425.

DOI:10.1080/14763141.2022.2137425
PMID:36409062
Abstract

This study sought to compare and validate baseball pitching mechanics, including joint angles and spatiotemporal parameters, from a single camera markerless motion capture solution with a 3D optical marker-based system. Ten healthy pitchers threw 2-3 maximum effort fastballs while concurrently using marker-based optical capture and pitchAI (markerless) motion capture. Time-series measures were compared using -squared (r), and root mean square error (RMSE). Discrete kinematic measures at foot plant, maximal shoulder external rotation, and ball release, plus four spatiotemporal parameters were evaluated using descriptive statistics, Bland-Altman analyses, Pearson's correlation coefficients, p-values, r, and RMSE. For time-series angles, r ranged from 0.69 (glove arm shoulder external rotation) to 0.98 (trunk and pelvis rotation), and RMSE ranged from 4.37° (trunk lateral tilt) to 20.78° (glove arm shoulder external rotation). Bias for individual joint angle and spatiotemporal parameters ranged from -11.31 (glove arm shoulder horizontal abduction; MER) to 12.01 (ball visible). RMSE was 3.62 m/s for arm speed, 5.75% height for stride length and 21.75 ms for the ball visible metric. pitchAI can be recommended as a markerless alternative to marker-based motion capture for quantifying pitching kinematics. A database of pitchAI ranges should be established for comparison between systems.

摘要

本研究旨在比较并验证基于单摄像头无标记运动捕捉解决方案与基于3D光学标记系统的棒球投球力学,包括关节角度和时空参数。十名健康投手在同时使用基于标记的光学捕捉和pitchAI(无标记)运动捕捉的情况下,投出2至3个全力快速球。使用决定系数(r²)和均方根误差(RMSE)对时间序列测量值进行比较。使用描述性统计、布兰德-奥特曼分析、皮尔逊相关系数、p值、r²和RMSE对脚落地、肩部最大外旋和球释放时的离散运动学测量值以及四个时空参数进行评估。对于时间序列角度,r²范围从0.69(手套臂肩部外旋)到0.98(躯干和骨盆旋转),RMSE范围从4.37°(躯干侧倾)到20.78°(手套臂肩部外旋)。各个关节角度和时空参数的偏差范围从-11.31(手套臂肩部水平外展;MER)到12.01(球可见)。手臂速度的RMSE为3.62米/秒,步长的RMSE为身高的5.75%,球可见指标的RMSE为21.75毫秒。对于量化投球运动学,pitchAI可作为基于标记的运动捕捉的无标记替代方案被推荐。应建立pitchAI范围的数据库以用于系统间的比较。

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