Provot Thomas, Millot Benjamin, Hazotte Eline, Rousseau Thomas, Slawinski Jean
EPF-Engineering School, 55 Avenue du Président Wilson, 94230 Cachan, France.
Arts et Métiers Institute of Technology, Institut de Biomécanique Humaine Georges Charpak, IBHGC, UR 4494, 75013 Paris, France, Université Sorbonne Paris Nord, 93000 Bobigny, France.
Methods Protoc. 2024 Dec 20;7(6):103. doi: 10.3390/mps7060103.
The accurate measurement of spatiotemporal parameters, such as step length and step frequency, is crucial for analyzing running and sprinting performance. Traditional methods like video analysis and force platforms are either time consuming or limited in scope, prompting the need for more efficient technologies. This study evaluates the effectiveness of a commercial Global Positioning System (GPS) unit integrated with an Inertial Measurement Unit (IMU) in capturing these parameters during sprints at varying velocities. Five experienced male runners performed six 40 m sprints at three velocity conditions (S: Slow, M: Medium, F: Fast) while equipped with a GPS-IMU system and an optical system as the gold standard reference. A total of 398 steps were analyzed for this study. Step frequency, step length and step velocity were extracted and compared using statistical methods, including the coefficient of determination (r) and root mean square error (RMSE). Results indicated a very large agreement between the embedded system and the reference system, for the step frequency (r = 0.92, RMSE = 0.14 Hz), for the step length (r = 0.91, RMSE = 0.07 m) and the step velocity (r = 0.99, RMSE = 0.17 m/s). The GPS-IMU system accurately measured spatiotemporal parameters across different running velocities, demonstrating low relative errors and high precision. This study demonstrates that GPS-IMU systems can provide comprehensive spatiotemporal data, making them valuable for both training and competition. The integration of these technologies offers practical benefits, helping coaches better understand and enhance running performance. Future improvements in sample rate acquisition GPS-IMU technology could further increase measurement accuracy and expand its application in elite sports.
准确测量时空参数,如步长和步频,对于分析跑步和短跑表现至关重要。传统方法,如视频分析和测力平台,要么耗时,要么范围有限,因此需要更高效的技术。本研究评估了一种集成了惯性测量单元(IMU)的商用全球定位系统(GPS)设备在不同速度短跑过程中捕捉这些参数的有效性。五名经验丰富的男性跑步者在三种速度条件下(S:慢,M:中,F:快)进行了六次40米短跑,同时配备了GPS-IMU系统和作为金标准参考的光学系统。本研究共分析了398步。使用统计方法,包括决定系数(r)和均方根误差(RMSE),提取并比较步频、步长和步速。结果表明,对于步频(r = 0.92,RMSE = 0.14 Hz)、步长(r = 0.91,RMSE = 0.07 m)和步速(r = 0.99,RMSE = 0.17 m/s),嵌入式系统与参考系统之间存在非常大的一致性。GPS-IMU系统能够准确测量不同跑步速度下的时空参数,显示出较低的相对误差和高精度。本研究表明,GPS-IMU系统可以提供全面的时空数据,使其在训练和比赛中都具有价值。这些技术的整合带来了实际益处,有助于教练更好地理解和提高跑步表现。GPS-IMU技术在采样率采集方面的未来改进可能会进一步提高测量精度,并扩大其在精英运动中的应用。