Accelerometer Based Data Can Provide a Better Estimate of Cumulative Load During Running Compared to GPS Based Parameters

与基于 GPS 的参数相比,基于加速度计的数据可以更准确地估算跑步过程中的累积负荷。

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Abstract

Running is a popular way to become or stay physically active and to maintain and improve one's musculoskeletal load tolerance. Despite the health benefits, running-related injuries affect millions of people every year and have become a substantial public health issue owing to the popularity of running. Running-related injuries occur when the musculoskeletal load exceeds the load tolerance of the human body. Therefore, it is crucial to provide runners with a good estimate of the cumulative loading during their habitual training sessions. In this study, we validated a wearable system to provide an estimate of the external load on the body during running and investigated how much of the cumulative load during a habitual training session is explained by GPS-based spatiotemporal parameters. Ground reaction forces (GRF) as well as 3D accelerations were registered in nine habitual runners while running on an instrumented treadmill at three different speeds (2.22, 3.33, and 4.44 m/s). Linear regression analysis demonstrated that peak vertical acceleration during running explained 80% of the peak vertical GRF. In addition, accelerometer-based as well as GPS-based parameters were registered during 498 habitual running session of 96 runners. Linear regression analysis showed that only 70% of the cumulative load (sum of peak vertical accelerations) was explained by duration, distance, speed, and the number of steps. Using a wearable device offers the ability to provide better estimates of cumulative load during a running program and could potentially serve as a better guide to progress safely through the program.

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