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A Wavelet Multiscale Based Method to Separate the High and Low Frequency Components of Mechanomyographic Signals

机译:基于小波多尺度的机电信号高频分量和低频分量分离方法

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摘要

The study of mechanomyographic (MMG) signals during dynamic contraction requires a criterion to select the cut-off frequency of the filter utilized to separate the low frequency (LF) component (basically due to gross movement of the muscle or of the body) and the high frequency (HF) component (related with the vibration of the muscle fibers during contraction). To date, there is not an established criterion to carry out this selection. In this study, we propose a wavelet multiscale based method to aid to select a suitable cut-off frequency to separate correctly the LF and HF components. This method has been tested in an animal model, with the signal acquired during spontaneous ventilations with a capacitive accelerometer applied on the costal wall. This signal, as the MMG signals during dynamic contractions, has a LF component that is related with the movement of the thoracic cage, and a HF component that could be related with the vibration of diaphragm muscle fibers during contraction. The results obtained in the two respiratory tests analyzed indicate that cut-off frequencies around 10 and 3 Hz, respectively, must be employed to eliminate the LF component. The proposed wavelet multiscale method appears to be suitable to carry out a preliminary study of the MMG frequency content in dynamic contraction protocols
机译:对动态收缩过程中的机电原理(MMG)信号的研究需要一个标准来选择用于分离低频(LF)分量的滤波器的截止频率(主要是由于肌肉或身体的总体运动)和高频(HF)成分(与收缩期间肌肉纤维的振动有关)。迄今为止,尚无确定的标准来进行这种选择。在这项研究中,我们提出了一种基于小波多尺度的方法,以帮助选择合适的截止频率以正确分离低频分量和高频分量。该方法已在动物模型中进行了测试,并在肋骨壁上使用电容式加速度计在自发通气期间获取信号。该信号作为动态收缩过程中的MMG信号,具有与胸廓运动相关的LF分量和与收缩过程中diaphragm肌纤维振动有关的HF分量。在两次呼吸测试中获得的分析结果表明,必须分别采用10 Hz和3 Hz左右的截止频率来消除LF分量。提出的小波多尺度方法似乎适合进行动态收缩协议中MMG频率内容的初步研究

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