Interdisciplinary Program of Engineering, National Tsing Hua University, Hsinchu 300044, Taiwan.
Department of Electrical Engineering, National Tsing Hua University, Hsinchu 300044, Taiwan.
Sensors (Basel). 2022 Aug 19;22(16):6244. doi: 10.3390/s22166244.
A greater variety of technologies are being applied in sports and health with the advancement of technology, but most optoelectronic systems have strict environmental restrictions and are usually costly. To visualize and perform quantitative analysis on the football kick, we introduce a 3D motion analysis system based on a six-axis inertial measurement unit (IMU) to reconstruct the motion trajectory, in the meantime analyzing the velocity and the highest point of the foot during the backswing. We build a signal processing system in MATLAB and standardize the experimental process, allowing users to reconstruct the foot trajectory and obtain information about the motion within a short time. This paper presents a system that directly analyzes the instep kicking motion rather than recognizing different motions or obtaining biomechanical parameters. For the instep kicking motion of path length around 3.63 m, the root mean square error (RMSE) is about 0.07 m. The RMSE of the foot velocity is 0.034 m/s, which is around 0.45% of the maximum velocity. For the maximum velocity of the foot and the highest point of the backswing, the error is approximately 4% and 2.8%, respectively. With less complex hardware, our experimental results achieve excellent velocity accuracy.
随着技术的进步，越来越多的技术被应用于体育和健康领域，但大多数光电系统都有严格的环境限制，且通常成本高昂。为了对足球踢腿进行可视化和定量分析，我们引入了一种基于六轴惯性测量单元（IMU）的 3D 运动分析系统，以重建运动轨迹，同时分析后摆过程中脚的速度和最高点。我们在 MATLAB 中构建了一个信号处理系统，并规范了实验过程，使用户能够在短时间内重建脚部轨迹并获得运动信息。本文提出了一种直接分析脚背踢球运动的系统，而不是识别不同的运动或获取生物力学参数。对于路径长度约为 3.63 米的脚背踢球运动，均方根误差（RMSE）约为 0.07 米。脚速的 RMSE 为 0.034 米/秒，约为最大速度的 0.45%。对于脚的最大速度和后摆的最高点，误差分别约为 4%和 2.8%。我们的实验结果表明，与更复杂的硬件相比，该系统具有出色的速度精度。
