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The Study on the sEMG Signal Characteristics of Muscular Fatigue Based on the Hilbert-Huang Transform

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Muscular fatigue refers to temporary decline of maximal power ability or contractive ability for muscle movement system. The signal of surface electromyographic signal (sEMG) can reflect the changes of muscular fatigue at certain extent. In many years, the application of signal of sEMG on evaluation muscular fatigue mainly focus on two aspects of time and frequency respectively. The new method Hilbert-Huang Transform(HHT) has the powerful ability of analyzing nonlinear and non-stationary data in both time and frequency aspect together. The method has self-adaptive basis and is better for feature extraction as we can obtain the local and instantaneous frequency of the signals. In this paper, we chose an experiment of the static biceps data of twelve adult subjects under the maximal voluntary contraction (MVC) of 80%. The experimental results proved that this method as a new thinking has an obvious potential for the biomedical signal analysis.
机译:肌肉疲劳是指最大功率能力或肌肉运动系统的收缩能力的暂时下降。表面电拍摄信号(SEMG)的信号可以在一定程度上反映肌肉疲劳的变化。多年来,SEMG信号在评价肌疲劳中的应用主要关注时间和频率的两个方面。新方法Hilbert-Huang变换(HHT)具有在两个时间和频率方面分析非线性和非静止数据的强大能力。该方法具有自适应的基础,并且可以更好地提取特征提取,因为我们可以获得信号的局部和瞬时频率。在本文中,我们选择了在最大自愿收缩(MVC)为80%下的十二个成年受试者的静态二头肌数据的实验。实验结果证明,这种方法作为新思维具有明显的生物医学信号分析的潜力。

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