Greenberg Elliot M, Thomas Stephen J, Kablan John, Condon John, Backstrom Erik, Lawrence J Todd
Children's Hospital of Philadelphia Sports Medicine and Performance Center, Philadelphia, Pennsylvania.
Department of Orthopedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Sports Health. 2025 Apr 2:19417381251329921. doi: 10.1177/19417381251329921.
The volume and frequency of throwing activity are among the most significant risk factors for developing overuse injuries in youth athletes. Despite introducing systematic guidelines for 'pitch counts,' throwing injuries continue to rise. Using technology to create enhanced measures of workload exposure in this unique population of athletes may help generate more effective and personalized injury prevention strategies.
The wrist-worn sensor system (PhySens) will: 1) accurately detect and differentiate throwing activity from other baseball movements, and 2) accurately predict ball velocity, arm slot angle, and elbow valgus torque.
Descriptive laboratory study.
Level 5.
Youth pitchers (n = 10) performed a standardized protocol of pitching, field-throwing, and batting. Pitching velocity and biomechanical data were simultaneously captured by the PhySens and traditional 3-dimensional motion capture. The accuracy of the pitching detection algorithm (throw vs batting) was analyzed by comparing truth data with throwing events cataloged by the device. Ball velocity, elbow valgus torque, and arm slot angle predictions were assessed with Pearson correlation coefficients and Bland-Altman plots.
A total of 230 events (pitches and bat swings) were analyzed. Pitch detection was excellent, with a sensitivity of 99.4% and specificity 97.9%. Pearson correlations were significant and excellent across all predicted variables, with ball velocity = 0.96, elbow valgus torque = 0.95, and arm slot angle = 0.87. The system demonstrated excellent estimations of ball velocity, elbow valgus torque, and arm slot angle.
This novel single-sensor wrist worn device was highly accurate in detecting pitching events, predicting ball velocity, and estimating arm slot angle and elbow valgus torque.
Throwing volume is highly associated with overuse injuries in youth baseball players. Sensor-based measures of workload monitoring can address inherent limitations related to human error and underestimation of true throwing exposure.
投掷活动的量和频率是青少年运动员发生过度使用损伤的最重要风险因素之一。尽管引入了“投球数”的系统指南，但投掷损伤仍在增加。利用技术为这一独特的运动员群体创建增强的工作量暴露测量方法，可能有助于制定更有效和个性化的损伤预防策略。
腕部佩戴的传感器系统（PhySens）将：1）准确检测并区分投掷活动与其他棒球动作，以及2）准确预测球速、手臂投球角度和肘部外翻扭矩。
描述性实验室研究。
5级。
青少年投手（n = 10）进行了投球、场内投掷和击球的标准化方案。投球速度和生物力学数据由PhySens和传统的三维运动捕捉同时采集。通过将真实数据与设备记录的投掷事件进行比较，分析投球检测算法（投球与击球）的准确性。用Pearson相关系数和Bland-Altman图评估球速、肘部外翻扭矩和手臂投球角度的预测。
共分析了230个事件（投球和击球挥棒）。投球检测效果极佳，灵敏度为99.4%，特异性为97.9%。所有预测变量的Pearson相关性均显著且极佳，球速=0.96，肘部外翻扭矩=0.95，手臂投球角度=0.87。该系统对球速、肘部外翻扭矩和手臂投球角度的估计效果极佳。
这种新型的单传感器腕部佩戴设备在检测投球事件、预测球速以及估计手臂投球角度和肘部外翻扭矩方面具有高度准确性。
投掷量与青少年棒球运动员的过度使用损伤高度相关。基于传感器的工作量监测措施可以解决与人为误差和对真实投掷暴露估计不足相关的固有局限性。
