Institute of Biomedical Engineering, Department of Electrical and Computer Engineering, University of New Brunswick, Canada.
J Electromyogr Kinesiol. 2013 Oct;23(5):1004-11. doi: 10.1016/j.jelekin.2013.05.005. Epub 2013 Jun 22.
Several EMG-based approaches to muscle fatigue assessment have recently been proposed in the literature. In this work, two multivariate fatigue indices developed by the authors: a generalized mapping index (GMI) and the first component of principal component analysis (PCA) were compared to three univariate indices: Dimitrov's normalized spectral moments (NSM), Gonzalez-Izal's waveletbased indices (WI), and Talebinejad's fractal-based Hurst Exponent (HE). Nine healthy participants completed two repetitions of fatigue tests during isometric, cyclic and random fatiguing contractions of the biceps brachii. The fatigue assessments were evaluated in terms of a modified sensitivity to variability ratio yielding the following scores (mean±std.dev.): PCA: (12.6±5.6), GMI: (11.5±5.4), NSM: (10.3±5.4), WI: (8.9±4.6), HE: (8.0±3.3). It was shown that PCA statistically outperformed WI and HE (p<0.01) and that GMI outperformed HE (p<0.02). There was no statistical difference among NSM, WI and HE (p>0.2). It was found that taking the natural logarithm of NSM and WI, although reducing the parameters' sensitivity to fatigue, increased SVR scores by reducing variability.
最近有一些基于肌电图的肌肉疲劳评估方法在文献中被提出。在这项工作中,作者提出了两个多变量疲劳指数:广义映射指数(GMI)和主成分分析(PCA)的第一分量,与三个单变量指数进行了比较:Dimitrov 的归一化光谱矩(NSM)、Gonzalez-Izal 的基于小波的指数(WI)和 Talebinejad 的基于分形的赫斯特指数(HE)。九名健康参与者完成了两次等长、循环和随机肱二头肌疲劳收缩的疲劳测试。疲劳评估是根据变异敏感性比的一种改进来进行的,得到以下分数(平均值±标准差):PCA:(12.6±5.6),GMI:(11.5±5.4),NSM:(10.3±5.4),WI:(8.9±4.6),HE:(8.0±3.3)。结果表明,PCA 在统计学上优于 WI 和 HE(p<0.01),GMI 优于 HE(p<0.02)。NSM、WI 和 HE 之间没有统计学差异(p>0.2)。发现对 NSM 和 WI 取自然对数,虽然降低了参数对疲劳的敏感性,但通过降低变异性提高了 SVR 分数。