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用于识别肌肉活动和疲劳的肌动图。

Mechanomyogram for identifying muscle activity and fatigue.

作者信息

Yang Zhao Feng, Kumar Dinesh Kant, Arjunan Sridhar Poosapadi

机构信息

Bio-signal Lab, School of Electrical and Computer Engineering, RMIT University, GPO Box 2476V, Melbourne, VIC 3001 Australia.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:408-11. doi: 10.1109/IEMBS.2009.5333666.

Abstract

Mechanomyogram is the recording of the acoustic activity associated with the muscle contraction. While discovered nearly a decade ago with the intention of providing an alternate to the surface electromyogram, it has not yet been investigated thoroughly and there are no current applications associated with MMG. This paper reports an experimental study of MMG against force of contraction and muscle fatigue during cyclic contraction. The results indicate that there is a relationship between the intensity of the MMG recording and force of contraction. A change in the intensity of MMG is also observed with the onset of muscle fatigue. However, the inter-subject variation is very large. The results also indicate that the spectrum of the MMG is very inconsistent and not a useful feature of the signal.

摘要

肌动图是与肌肉收缩相关的声学活动记录。虽然近十年前就已发现,旨在提供一种替代表面肌电图的方法,但尚未进行充分研究,目前也没有与肌动图相关的应用。本文报告了一项关于肌动图在周期性收缩过程中对抗收缩力和肌肉疲劳的实验研究。结果表明,肌动图记录的强度与收缩力之间存在关系。随着肌肉疲劳的出现,肌动图强度也会发生变化。然而,个体间差异非常大。结果还表明,肌动图的频谱非常不一致,不是该信号的一个有用特征。

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