Analysis and Processing of Surface Electromyography (sEMG) Signals

MATLAB programs for analyzing and processing surface electromyography (sEMG) signals are highly valuable tools in biomedical signal processing. These implementations help researchers perform essential analyses including spectral analysis using FFT algorithms, cepstrum computation through inverse Fourier transform of log-spectrum, power spectrum estimation via periodogram or Welch's method, and median frequency calculation using spectral moment analysis. Through these processing techniques, we can better understand and investigate the characteristics of electromyography signals. Furthermore, MATLAB provides numerous additional functions and toolboxes, such as the Signal Processing Toolbox and Wavelet Toolbox, which can significantly expand our research and analytical capabilities. Key functions like fft(), cceps(), pwelch(), and medfreq() can be effectively utilized for these analyses. Therefore, employing MATLAB for surface EMG signal processing represents an intelligent choice for both academic research and clinical applications.