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与基于全球定位系统(GPS)的参数相比,基于加速度计的数据能更好地估算跑步过程中的累积负荷。

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

作者信息

Vanwanseele Benedicte, Op De Beéck Tim, Schütte Kurt, Davis Jesse

机构信息

Human Movement Biomechanics, Department of Movement Sciences, KU Leuven, Leuven, Belgium.

Department of Computer Science, KU Leuven, Leuven, Belgium.

出版信息

Front Sports Act Living. 2020 Oct 30;2:575596. doi: 10.3389/fspor.2020.575596. eCollection 2020.

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.

摘要

跑步是一种流行的保持身体活跃以及维持和提高肌肉骨骼负荷耐受性的方式。尽管有诸多健康益处,但与跑步相关的损伤每年仍影响着数百万人,并且由于跑步的普及,已成为一个重大的公共卫生问题。当肌肉骨骼负荷超过人体的负荷耐受性时,就会发生与跑步相关的损伤。因此,为跑步者提供其日常训练期间累积负荷的准确估计至关重要。在本研究中,我们验证了一种可穿戴系统,以估计跑步过程中身体的外部负荷,并研究了基于全球定位系统(GPS)的时空参数能解释日常训练期间累积负荷的多少。在九名习惯跑步者在装有仪器的跑步机上以三种不同速度(2.22、3.33和4.44米/秒)跑步时,记录了地面反作用力(GRF)以及三维加速度。线性回归分析表明,跑步过程中的峰值垂直加速度可解释80%的峰值垂直GRF。此外,在96名跑步者的498次日常跑步过程中,记录了基于加速度计以及基于GPS的参数。线性回归分析显示,持续时间、距离、速度和步数仅能解释70%的累积负荷(峰值垂直加速度之和)。使用可穿戴设备能够更准确地估计跑步计划期间的累积负荷,并有可能作为更安全地完成该计划的更好指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f53/7739807/69e90177cc31/fspor-02-575596-g0001.jpg

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