Different Techniques for the Segmentation of the EMG Signal-A Review

In this paper, the electromyographic (EMG) signals of a patient and the normal person are considered. In order to decompose both the signals, different segmentation techniques are used. The two segmentation techniques used in this work are: i) Segmentation using daubechies wavelet transform (DWT), ii) by identifying the peaks of the MUAPs. The MUAPs (motor unit action potentials) are the important source of the EMG signal to provide information about any kind of disorder in the muscles or any disturbance in the functioning of the muscle cells. In this paper, the electromyographic (EMG) signals of a patient and the normal person are considered. In order to decompose both the signals, different segmentation techniques are used. The two segmentation techniques used in this work are: i) Segmentation using daubechies wavelet transform (DWT), ii) by identifying the peaks of the MUAPs. The MUAPs (motor unit action potentials) are the important source of the EMG signal to provide information about any kind of disorder in the muscles or any disturbance in the functioning of the muscle cells.