自我报告,触摸和表面肌电图数据集在同度肌肉收缩期间的评估
Jihoon Lim1, Lei Lu2,3, Kusal Goonewardena4
1Department of Mechanical Engineering, The University of Melbourne, Parkville, 3010, Australia.
Scientific data
|February 15, 2024
概括
这项研究比较了自我报告的疲劳,手动触摸和表面电肌图 (EMG) 来测量肌肉疲劳. 它提供了一个数据集,用于比较在同位数收缩过程中身体上部肌肉中的这些方法.
科学领域:
- 生物力学和运动控制
- 体育科学与人类表现
- 康复和物理治疗治疗.
背景情况:
- 评估肌肉疲劳对于理解运动系统功能至关重要.
- 现有的方法包括主观的自我报告和客观的基于传感器的技术.
- 缺乏对这些不同的肌肉疲劳评估措施的全面比较.
研究的目的:
- 为了比较参与者自我报告的感知肌肉疲劳得分,体育物理治疗师手动触摸的肌肉紧张得分,以及表面电肌图 (EMG) 传感器数据.
- 为了评估九个上半身肌肉在同度收缩期间的补偿性肌肉疲劳.
- 为体育科学,康复和人类表现领域的研究人员和从业人员提供一个有价值的数据集.
主要方法:
- 使用了三种评估方法:主观疲劳得分,手动触摸肌肉紧张,以及表面EMG.
- 专注于补偿性肌肉疲劳,分析了九个上肢肌肉.
- 收集了30名男性实验对象进行同度收缩的数据.
主要成果:
- 该研究提供了肌肉疲劳指标的比较数据集.
- 它可以探索对上肢肌肉的各种评估方法.
- 这些发现有助于理解补偿性疲劳机制.
结论:
- 这项研究弥合了肌肉疲劳评估技术的比较分析的差距.
- 这些发现支持综合使用主观,手动和基于传感器的方法来全面评估肌肉疲劳.
- 这一数据集对于推动体育科学,康复和人类表现方面的研究具有价值.
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