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室内团队运动中的运动员监测:惯性测量单元量化平均加速度和峰值加速度值的同时效度

Player Monitoring in Indoor Team Sports: Concurrent Validity of Inertial Measurement Units to Quantify Average and Peak Acceleration Values.

作者信息

Roell Mareike, Roecker Kai, Gehring Dominic, Mahler Hubert, Gollhofer Albert

机构信息

Department for Sports and Sport Science, Albert-Ludwigs-University Freiburg, Freiburg im Breisgau, Germany.

Applied Public Health, Furtwangen University, Furtwangen im Schwarzwald, Germany.

出版信息

Front Physiol. 2018 Feb 27;9:141. doi: 10.3389/fphys.2018.00141. eCollection 2018.

Abstract

The increasing interest in assessing physical demands in team sports has led to the development of multiple sports related monitoring systems. Due to technical limitations, these systems primarily could be applied to outdoor sports, whereas an equivalent indoor locomotion analysis is not established yet. Technological development of inertial measurement units (IMU) broadens the possibilities for player monitoring and enables the quantification of locomotor movements in indoor environments. The aim of the current study was to validate an IMU measuring by determining average and peak human acceleration under indoor conditions in team sport specific movements. Data of a single wearable tracking device including an IMU (Optimeye S5, Catapult Sports, Melbourne, Australia) were compared to the results of a 3D motion analysis (MA) system (Vicon Motion Systems, Oxford, UK) during selected standardized movement simulations in an indoor laboratory ( = 56). A low-pass filtering method for gravity correction (LF) and two sensor fusion algorithms for orientation estimation [Complementary Filter (CF), Kalman-Filter (KF)] were implemented and compared with MA system data. Significant differences ( < 0.05) were found between LF and MA data but not between sensor fusion algorithms and MA. Higher precision and lower relative errors were found for CF (RMSE = 0.05; CV = 2.6%) and KF (RMSE = 0.15; CV = 3.8%) both compared to the LF method (RMSE = 1.14; CV = 47.6%) regarding the magnitude of the resulting vector and strongly emphasize the implementation of orientation estimation to accurately describe human acceleration. Comparing both sensor fusion algorithms, CF revealed slightly lower errors than KF and additionally provided valuable information about positive and negative acceleration values in all three movement planes with moderate to good validity (CV = 3.9 - 17.8%). Compared to x- and y-axis superior results were found for the z-axis. These findings demonstrate that IMU-based wearable tracking devices can successfully be applied for athlete monitoring in indoor team sports and provide potential to accurately quantify accelerations and decelerations in all three orthogonal axes with acceptable validity. An increase in accuracy taking magnetometers in account should be specifically pursued by future research.

摘要

对团队运动中身体需求评估的兴趣日益增加,导致了多种与运动相关的监测系统的发展。由于技术限制,这些系统主要应用于户外运动,而等效的室内运动分析尚未建立。惯性测量单元(IMU)的技术发展拓宽了运动员监测的可能性,并能够在室内环境中对运动动作进行量化。本研究的目的是通过确定团队运动特定动作在室内条件下的平均和峰值人体加速度来验证IMU测量。在室内实验室中进行选定的标准化运动模拟时(n = 56),将包括IMU的单个可穿戴跟踪设备(Optimeye S5,Catapult Sports,墨尔本,澳大利亚)的数据与三维运动分析(MA)系统(Vicon Motion Systems,牛津,英国)的结果进行比较。实施了用于重力校正的低通滤波方法(LF)和两种用于方向估计的传感器融合算法[互补滤波器(CF)、卡尔曼滤波器(KF)],并与MA系统数据进行比较。在LF和MA数据之间发现了显著差异(p < 0.05),但在传感器融合算法和MA之间未发现显著差异。与LF方法(均方根误差 = 1.14;变异系数 = 47.6%)相比,CF(均方根误差 = 0.05;变异系数 = 2.6%)和KF(均方根误差 = 0.15;变异系数 = 3.8%)在所得向量的大小方面具有更高的精度和更低的相对误差,这强烈强调了方向估计的实施对于准确描述人体加速度的重要性。比较两种传感器融合算法,CF显示出的误差略低于KF,并且还提供了关于所有三个运动平面中正负加速度值的有价值信息,有效性为中等至良好(变异系数 = 3.9 - 17.8%)。与x轴和y轴相比,z轴的结果更优。这些发现表明,基于IMU的可穿戴跟踪设备可以成功应用于室内团队运动中的运动员监测,并具有在所有三个正交轴上以可接受的有效性准确量化加速度和减速度的潜力。未来的研究应特别致力于考虑磁力计以提高准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7f9/5835232/d2f9bebe6676/fphys-09-00141-g0001.jpg

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