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• W2790698444 abstract "Decomposition of EMG (electromyography), in which the MUAPs (Motor Units Action Potentials) are extracted from the original EMG signals, is a useful approach for evaluating the physiological properties of muscles and studying the neural mechanism of human motions. Existing decomposition methods usually extracted the MUAPs via the waveform matching between the detected spikes and MUAP templates. However, those methods always involve too many artificial parameters and have no generally mathematical expression, which make them inflexible in practical applications and also cause poor robustness under interference. With respect to the problem, in this paper, a wavelet-based decomposition method is proposed to detect the “true” MUAPs from sEMG. Two standard Gaussian wavelets are firstly defined as the basic MUAP expressions; then, wavelet transform is performed to describe scales and magnitudes of different MUAPs from different nerve fibers. Experiments were conducted to verify the performance of the proposed method, where MUAPs decomposed from sEMG under different levels of muscle contraction can be effectively detected by the method." @default.
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• W2790698444 date "2017-12-01" @default.
• W2790698444 modified "2023-09-22" @default.
• W2790698444 title "Wavelet-based detection on MUAPs decomposed from sEMG under different levels of muscle isometric contraction" @default.
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• W2790698444 doi "https://doi.org/10.1109/robio.2017.8324542" @default.
• W2790698444 hasPublicationYear "2017" @default.
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