Performance Study of DWT and EMD Techniques for Denoising Electromyographic Signal

Electromyography (EMG) is a popular technique for muscle activity study and many biomedical applications, like prosthetic arm development, muscle fatigue detection, etc. However, the EMG signal is usually contaminated with various types of noises during the acquisition. To use the EMG signal effectively a denoising technique should be applied to the signal. In this study, EMG signal has been recorded during the wrist flexion movement of the volunteer from right flexor carpi radialis muscle. Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT) techniques have been used for denoising the signal. Both EMD and DWT denoising techniques have shown excellent denoising performance for EMG signal. However, DWT denoising technique has outperformed EMD technique for the parameters of Signal to Noise Ratio (SNR), Mean Square Error (MSE), and execution time. The results of this study can contribute and assist to the development of more accurate and reliable EMG-based applications in biomedical engineering and clinical diagnosis.