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使用可穿戴设备估算手球中的投掷速度。

Estimating Throwing Speed in Handball Using a Wearable Device.

机构信息

Department of Public Health, Aarhus University, 8000 Aarhus, Denmark.

Human Movement Analysis Laboratory, Department of Orthopaedic Surgery, Copenhagen University Hospital Amager-Hvidovre, 2650 Hvidovre, Denmark.

出版信息

Sensors (Basel). 2020 Aug 31;20(17):4925. doi: 10.3390/s20174925.

Abstract

Throwing speed is likely a key determinant of shoulder-specific load. However, it is difficult to estimate the speed of throws in handball in field-based settings with many players due to limitations in current technology. Therefore, the purpose of this study was to develop a novel method to estimate throwing speed in handball using a low-cost accelerometer-based device. Nineteen experienced handball players each performed 25 throws of varying types while we measured the acceleration of the wrist using the accelerometer and the throwing speed using 3D motion capture. Using cross-validation, we developed four prediction models using combinations of the logarithm of the peak total acceleration, sex and throwing type as the predictor and the throwing speed as the outcome. We found that all models were well-calibrated (mean calibration of all models: 0.0 m/s, calibration slope of all models: 1.00) and precise (R2 = 0.71-0.86, mean absolute error = 1.30-1.82 m/s). We conclude that the developed method provides practitioners and researchers with a feasible and cheap method to estimate throwing speed in handball from segments of wrist acceleration signals containing only a single throw.

摘要

投掷速度可能是肩部特定负荷的关键决定因素。然而,由于当前技术的限制,在手球的现场环境中,由于有许多运动员在场,很难估计投掷速度。因此,本研究的目的是开发一种使用低成本加速度计的新型方法来估计手球的投掷速度。19 名经验丰富的手球运动员每人进行了 25 次不同类型的投掷,同时我们使用加速度计测量手腕的加速度,并使用 3D 运动捕捉测量投掷速度。通过交叉验证,我们使用对数峰值总加速度、性别和投掷类型作为预测因子以及投掷速度作为结果的组合开发了四个预测模型。我们发现所有模型的校准都很好(所有模型的平均校准值为 0.0 m/s,所有模型的校准斜率均为 1.00),且非常精确(R2 = 0.71-0.86,平均绝对误差 = 1.30-1.82 m/s)。我们得出结论,所开发的方法为从业者和研究人员提供了一种可行且廉价的方法,可在手球的单个投掷包含的手腕加速度信号段中估计投掷速度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5778/7506947/adec263388ac/sensors-20-04925-g001.jpg

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