基于希尔伯特-黄变换的肌动图估计肌肉疲劳研究  

A Study of Mechanomyography Analysis for Muscle Fatigue with Hilbert-Huang Transform

作　　者：胡淑娴[1] 施俊[1] 

机构地区：[1]上海大学通信与信息工程学院,上海200072

出　　处：《生物医学工程学杂志》2011年第2期243-247,共5页Journal of Biomedical Engineering

基　　金：国家自然科学基金资助项目(60701021);上海市教委重点学科建设项目资助(J50104)

摘　　要：肌动图(MMG)记录了肌纤维的低频侧向振动,表征了肌肉活动的力学特性。MMG信号可用于估计肌肉疲劳。希尔伯特-黄变换(HHT)作为一种时频分析方法,具有自适应性,适合于非线性、非平稳信号分析。本文利用HHT对上肢肱二头肌等长收缩疲劳实验中记录的MMG信号进行分析,提取计算瞬时频率的最高值与最低值的差(频带值)作为特征量,以估计肌肉疲劳特性。实验结果表明,当肌肉完全疲劳以后,50%最大力矩值和70%最大力矩值情况下,频带比分别为0.431±0.607和0.286±0.218,说明肌肉疲劳以后,频率有了明显地下降。The mechanomyography（MMG） records and quantifies the low-frequency lateral oscillations of active muscle fibers.It can represent the mechanical characteristics of muscle activity.MMG has been used to evaluate muscle fatigue.Hilbert-Huang transform（HHT） is a time-frequency method with the feature of self-adaptation,and designed specifically for nonlinear and nonstationary signal analysis.In this study,MMG signal was recorded from biceps brachii during isometric fatigue contraction.HHT was used to calculate the difference between the maximum and minimum values of instantaneous frequency,named as the band ratio,to estimate muscle fatigue.The results showed that the band ratios were 0.431±0.607 and 0.286±0.218 after fatigue for the maximum voluntary contraction（MVC） of 50% and 70%,respectively.These indicated that the frequency declined after muscles fatigue.

关 键 词：肌动图 希尔伯特-黄变换 肌肉疲劳 肌电图 频带 

分 类 号：TN911.7[电子电信—通信与信息系统]