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Wavelet transform to recognize muscle fatigue

机译:小波变换识别肌肉疲劳

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摘要

Electromyography (EMG) is to measure the muscle response to nervous stimulation. The power spectrum of the EMG shifts towards lower frequencies during a continued muscle contraction due to muscular fatigue. Muscle fatigue is the decline in ability of a muscle to create force. This research presents the effectiveness of the wavelet transform applied to the surface EMG (SEMG) signal as a means of understanding muscle fatigue during walk. Power spectrum and bispectrum analysis on the EMG signal getting from right rectus femoris muscle is executed utilizing various wavelet functions (WFs). It is possible to recognize muscle fatigue appreciably with the proper choice of the WF. The outcome proves that, the most momentous changes in the EMG power spectrum symbolized by WF Daubechies4. Moreover, bispectrum properties compared to the other WFs. To determine muscle fatigue during gait, Daubechies45 is used in this research to analyze SEMG signal.
机译:肌电图(EMG)用于测量肌肉对神经刺激的反应。由于肌肉疲劳,在持续的肌肉收缩过程中,EMG的功率谱向低频移动。肌肉疲劳是指肌肉产生力量的能力下降。这项研究提出了将小波变换应用于表面肌电图(SEMG)信号作为了解步行过程中肌肉疲劳的方法的有效性。利用各种小波函数(WF)对从右股直肌获得的EMG信号进行功率谱和双频谱分析。通过选择适当的WF,可以明显地识别肌肉疲劳。结果证明,以WF Daubechies4为代表的EMG功率谱中最重大的变化。此外,与其他WF相比,双光谱特性。为了确定步态期间的肌肉疲劳,本研究使用Daubechies45分析SEMG信号。

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