Validation of gyroscope sensors for snow sports performance monitoring

Cameron Ross, P. Lamb, P. McAlpine, G. Kennedy, C. Button
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引用次数: 2

Abstract

Abstract Wearable sensors that can be used to measure human performance outcomes are becoming increasingly popular within sport science research. Validation of these sensors is vital to ensure accuracy of extracted data. The aim of this study was to establish the validity and reliability of gyroscope sensors contained within three different inertial measurement units (IMU). Three IMUs (OptimEye, I Measure U and Logger A) were fixed to a mechanical calibration device that rotates through known angular velocities and positions. RMS scores for angular displacement, which were calculated from the integrated angular velocity vectors, were 3.85° ± 2.21° and 4.34° ± 2.57° for the OptimEye and IMesU devices, respectively. The RMS error score for the Logger A was 22.76° ± 23.22°, which was attributed to a large baseline shift of the angular velocity vector. After a baseline correction of all three devices, RMS error scores were all below 3.90°. Test re-test reliability of the three gyroscope sensors were high with coefficient of variation (CV%) scores below 2.5%. Overall, the three tested IMUs are suitable for measuring angular displacement of snow sports manoeuvres after baseline corrections have been made. Future studies should investigate the accuracy and reliability of accelerometer and magnetometer sensors contained in each of the IMUs to be used to identify take-off and landing events and the orientation of the athlete at those events.
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雪上运动性能监测用陀螺仪传感器的验证
可穿戴式传感器可用于测量人类表现结果,在体育科学研究中越来越受欢迎。这些传感器的验证对于确保提取数据的准确性至关重要。本研究的目的是建立陀螺仪传感器包含在三个不同的惯性测量单元(IMU)的有效性和可靠性。三个imu (OptimEye, I Measure U和Logger A)固定在一个机械校准装置上,该装置通过已知的角速度和位置旋转。根据综合角速度矢量计算的角位移RMS评分,OptimEye和IMesU装置的角位移RMS评分分别为3.85°±2.21°和4.34°±2.57°。记录器A的RMS误差评分为22.76°±23.22°,这是由于角速度矢量的基线偏移较大。在对所有三种设备进行基线校正后,RMS误差评分均低于3.90°。三种陀螺仪传感器的重测信度较高,变异系数(CV%)得分均在2.5%以下。总的来说,三个测试imu适合测量基线修正后的雪上运动动作的角位移。未来的研究应调查每个imu中包含的加速度计和磁力计传感器的准确性和可靠性,用于识别起降事件以及运动员在这些事件中的方向。
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来源期刊
International Journal of Computer Science in Sport
International Journal of Computer Science in Sport Computer Science-Computer Science (all)
CiteScore
2.20
自引率
0.00%
发文量
4
审稿时长
12 weeks
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