Physical Education and Sports Science Academic Group, National Institute of Education, Nanyang Technological University, Singapore 637616, Singapore.
Sensors (Basel). 2023 Jan 19;23(3):1171. doi: 10.3390/s23031171.
Traditionally, the biomechanical analysis of Olympic weightlifting movements required laboratory equipment such as force platforms and transducers, but such methods are difficult to implement in practice. This study developed a field-based method using wearable technology and videos for the biomechanical assessment of weightlifters. To demonstrate the practicality of our method, we collected kinetic and kinematic data on six Singapore National Olympic Weightlifters. The participants performed snatches at 80% to 90% of their competition one-repetition maximum, and the three best attempts were used for the analysis. They wore a pair of in-shoe force sensors loadsol (novel, Munich, Germany) to measure the vertical ground reaction forces under each foot. Concurrently, a video camera recorded the barbell movement from the side. The kinematics (e.g., trajectories and velocities) of the barbell were extracted using a free video analysis software (Kinovea). The power-time history was calculated from the force and velocity data. The results showed differences in power, force, and barbell velocity with to reliability. Technical inconsistency in the barbell trajectories were also identified. In conclusion, this study presented a simple and practical approach to evaluating weightlifters using in-shoe wearable sensors and videos. Such information can be useful for monitoring progress, identifying errors, and guiding training plans for weightlifters.
传统上,对奥林匹克举重动作的生物力学分析需要使用力台和换能器等实验室设备,但这些方法在实践中很难实施。本研究开发了一种基于现场的方法,使用可穿戴技术和视频对举重运动员进行生物力学评估。为了展示我们方法的实用性,我们收集了六名新加坡国家奥林匹克举重运动员的运动学和运动学数据。参与者以 80%到 90%的比赛最大重复次数进行抓举,分析时使用了三次最佳尝试。他们穿着一对 in-shoe 力传感器 loadsol(新型,慕尼黑,德国)来测量每只脚的垂直地面反作用力。同时,一台摄像机从侧面记录杠铃的运动。使用免费视频分析软件(Kinovea)提取杠铃的运动学(例如轨迹和速度)。从力和速度数据计算功率-时间历史。结果表明,功率、力和杠铃速度的差异具有 到 可靠性。还确定了杠铃轨迹的技术不一致性。总之,本研究提出了一种使用鞋内可穿戴传感器和视频评估举重运动员的简单实用方法。这些信息对于监测进展、识别错误和指导举重运动员的训练计划非常有用。