Chair of Performance Analysis and Sports Informatics, Technical University Munich, 80992 Munich, Germany.
Department of Computer Science, UiT The Arctic University of Norway, 9037 Tromsø, Norway.
Sensors (Basel). 2021 Nov 4;21(21):7331. doi: 10.3390/s21217331.
This study describes a method for extracting the stride parameter ground contact time (GCT) from inertial sensor signals in sprinting. Five elite athletes were equipped with inertial measurement units (IMU) on their ankles and performed 34 maximum 50 and 100-m sprints. The GCT of each step was estimated based on features of the recorded IMU signals. Additionally, a photo-electric measurement system covered a 50-m corridor of the track to generate ground truth data. This corridor was placed interchangeably at the first and the last 50-ms of the track. In total, 863 of 889 steps (97.08%) were detected correctly. On average, ground truth data were underestimated by 3.55 ms. The root mean square error of GCT was 7.97 ms. Error analyses showed that GCT at the beginning and the end of the sprint was classified with smaller errors. For single runs the visualization of step-by-step GCT was demonstrated as a new diagnostic instrument for sprint running. The results show the high potential of IMUs to provide the temporal parameter GCT for elite-level athletes.
本研究描述了一种从短跑惯性传感器信号中提取步幅参数地面接触时间(GCT)的方法。5 名精英运动员在脚踝上配备了惯性测量单元(IMU),并进行了 34 次最大的 50 米和 100 米冲刺。根据记录的 IMU 信号的特征,估算了每个步的 GCT。此外,一个光电测量系统覆盖了跑道的 50 米走廊,以生成地面真实数据。这条走廊可以在跑道的前 50 毫秒和最后 50 毫秒之间交替放置。总共正确检测到了 863 步中的 889 步(97.08%)。平均而言,地面真实数据被低估了 3.55 毫秒。GCT 的均方根误差为 7.97 毫秒。误差分析表明,短跑开始和结束时的 GCT 分类误差较小。对于单次跑步,逐步 GCT 的可视化被证明是一种新的短跑诊断工具。结果表明,IMU 非常有潜力为精英运动员提供时间参数 GCT。