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Related Data for: Field-based biomechanical assessment of the snatch in Olympic weightlifting using wearable in-shoe sensors and videos: A preliminary report

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DataCite Commons2023-04-05 更新2025-04-16 收录
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https://researchdata.nie.edu.sg/citation?persistentId=doi:10.25340/R4/CVVUOX
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资源简介:
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 moderate to almost perfect 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,奥林匹克举重动作的生物力学分析需依赖测力平台、传感器等实验室设备,但此类方法在实际场景中难以落地推行。本研究开发了一种现场适用的评估方案,借助可穿戴设备与视频技术开展举重运动员的生物力学评估。为验证本方案的实用性,我们招募6名新加坡国家奥林匹克举重队运动员,采集其动力学与运动学数据。受试者以其竞赛单次最大重量(one-repetition maximum)的80%~90%完成抓举动作,选取其中表现最佳的3次试举用于后续分析。受试者穿戴一对loadsol®鞋内置力传感器(novel,德国慕尼黑),采集双足的垂直地面反作用力。与此同时,通过一台摄像机从侧方记录杠铃的运动过程。借助免费视频分析软件Kinovea,提取杠铃的运动学参数(包括运动轨迹与运动速度)。根据测力数据与速度数据,计算得到功率-时间历程曲线。研究结果显示,功率、作用力与杠铃速度存在显著差异,且该测试方法具有中等至近乎完美的信度;同时还识别出受试者的杠铃运动轨迹存在技术动作不一致的问题。综上,本研究提出了一种借助鞋内置力可穿戴传感器与视频技术的简易实用方法,用于举重运动员的表现评估。该评估结果可用于监测运动员竞技进展、识别技术动作缺陷,并辅助制定举重训练计划。
提供机构:
NIE Data Repository
创建时间:
2023-01-19
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