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动态等扭矩用力过程中用于背部肌肉疲劳检测的肌电图小波分析。

Wavelet analysis of electromyography for back muscle fatigue detection during dynamic constant-torque exertions.

作者信息

Sparto P J, Jagadeesh J M, Parnianpour M

机构信息

Biomedical Engineering Center, Ohio State University, Columbus 43210, USA.

出版信息

Biomed Sci Instrum. 1997;33:82-7.

PMID:9731340
Abstract

The fatigue of the back muscles appears to be strongly implicated as a risk factor for acquisition of low back pain, which is one of the leading ills of our industrial society. Previously, researchers have successfully measured the level of muscular fatigue by using the Fourier transform to analyze the frequency content of the electromyogram (EMG). However, due to the requirement that the EMG signal be stationary, the Fourier transform is suitable only for the analysis of static muscle exertions in which the muscle is held at constant length and tension. Because the majority of industrial work tasks are not static in nature, new methods for quantifying fatigue during dynamic work are needed. The wavelet transform is a novel, although mathematically well developed, technique for analyzing non-stationary signals that has only recently been applied to the study of EMG. Consequently, the main objective of this project is to develop techniques, using the wavelet transform, for the quantification of back muscle fatigue during dynamic repetitive working conditions.

摘要

背部肌肉疲劳似乎是导致下背痛的一个重要危险因素,下背痛是我们工业社会的主要疾病之一。此前,研究人员已通过使用傅里叶变换分析肌电图(EMG)的频率成分成功测量了肌肉疲劳程度。然而,由于EMG信号需为平稳信号这一要求,傅里叶变换仅适用于分析静态肌肉活动,即肌肉保持恒定长度和张力的情况。由于大多数工业工作任务本质上并非静态,因此需要新的方法来量化动态工作期间的疲劳。小波变换是一种新颖的技术,尽管在数学上已得到充分发展,用于分析非平稳信号,且直到最近才应用于EMG研究。因此,本项目的主要目标是开发利用小波变换的技术,以量化动态重复工作条件下的背部肌肉疲劳。

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