GymSense: Exploration in Measuring Bench Press Form Using Sensor Technology

Ritavash Chowdhury, Michael Chung, Dylan Gnagey, Jason Forsyth
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Abstract

Proper weightlifting form is essential to prevent injuries, particularly for beginners. Our GymSense project is a computer system that monitors and provides feedback on critical aspects of form during the bench press exercise, including grip width, shoulder distance, shoulder abduction angle, tilt, and back arch. The system employs force and camera sensors, ArUco markers, and the BlazePose algorithm to measure the key parameters of form and provides feedback to the user during and after each set. The feedback loop allows users to identify areas for improvement and reduce the risk of injury. We conducted a user study to assess the accuracy of the first iteration of the system. We found through the user study that our system is not as accurate as a personal trainer, but our project presents the initial phase of an alternative approach for obtaining feedback on a user’s bench press form.
GymSense:用传感器技术测量台式压力机成形的探索
正确的举重姿势对防止受伤至关重要,尤其是对初学者来说。我们的GymSense项目是一个计算机系统,它监控并提供卧推运动中形体的关键方面的反馈,包括握把宽度、肩距、肩外展角度、倾斜和背弓。该系统采用力和摄像传感器、ArUco标记和BlazePose算法来测量形状的关键参数,并在每次设置期间和之后向用户提供反馈。反馈回路允许用户确定需要改进的地方,并减少受伤的风险。我们进行了一次用户研究,以评估系统第一次迭代的准确性。我们通过用户研究发现,我们的系统不如私人教练准确,但我们的项目展示了一种获取用户卧推形式反馈的替代方法的初始阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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