Assessing real-world movements using consumer-grade wearable devices: Measuring segment orientations and movement quality.

IF 3.5 Q2 ENGINEERING, BIOMEDICAL
Wearable technologies Pub Date : 2025-11-19 eCollection Date: 2025-01-01 DOI:10.1017/wtc.2025.10034
T Alexander Swain, Melitta A McNarry, Samuel Manzano-Carrasco, Kelly A Mackintosh
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Abstract

In recent years, there has been growing interest regarding the impact of human movement quality on health. However, assessing movement quality outside of laboratories or clinics remains challenging. This study aimed to evaluate the capabilities of consumer-grade wearables to assess movement quality and to consider optimal sensor locations. Twenty-two participants wore Polar Verity Sense magnetic, angular rate, and gravity (MARG) sensors on their chest and both wrists, thighs, and ankles, while performing repeated bodyweight movements. The Madgwick sensor-fusion algorithm was utilized to obtain three-dimensional orientations. Concurrent validity, quantified using the root-mean-square-error (RMSE), was established against a Vicon optical motion capture system following time-synchronization and coordinate-system alignment. The chest sensors demonstrated the highest accuracies overall, with mean RMSE () less than 9.0° across all movements. In contrast, the wrist sensors varied considerably (). Ankle and thigh sensors yielded mixed results, with the ranging from 2.0° to 40.0°. Notably, yaw angles consistently demonstrated higher discrepancies overall, while pitch and roll were relatively more stable. This study highlights the potential of consumer-grade MARG sensors to increase the real-world applicability and accessibility of complex biomechanical models. It also accentuates the requirement for strategic sensor placement and refined calibration and postprocessing methods to ensure accuracy.

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使用消费级可穿戴设备评估真实世界的运动:测量分段方向和运动质量。
近年来,人们对人体运动质量对健康的影响越来越感兴趣。然而,在实验室或诊所之外评估运动质量仍然具有挑战性。本研究旨在评估消费级可穿戴设备在评估运动质量和考虑最佳传感器位置方面的能力。22名参与者在他们的胸部、手腕、大腿和脚踝上佩戴了极地真实感磁场、角速率和重力(MARG)传感器,同时重复做体重运动。利用Madgwick传感器融合算法获得三维方位。采用时间同步和坐标系对齐后的Vicon光学运动捕捉系统,采用均方根误差(RMSE)对并发有效性进行量化。胸部传感器总体上显示出最高的精度,所有运动的平均RMSE()小于9.0°。相比之下,手腕的传感器变化很大()。脚踝和大腿的传感器产生了不同的结果,范围从2.0°到40.0°。值得注意的是,偏航角始终表现出更高的差异,而俯仰和翻滚相对更稳定。这项研究强调了消费级MARG传感器在提高复杂生物力学模型在现实世界中的适用性和可及性方面的潜力。它还强调了对战略传感器放置和精细校准和后处理方法的要求,以确保准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.80
自引率
0.00%
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0
审稿时长
11 weeks
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