Analysis and Comparison of Fast Fourier and Wavelet Transform Techniques on Raw sEMG Data From Textile-Based Electrodes

Surface electromyography is an assessment tool that is frequently used in many areas of medical science today and is used to analyze muscle function. This measurement technique, which provides important information about the contraction of our body’s muscles, identifies which muscles are activated during which movements. Thanks to the development of technology and studies on smart textiles for physiological state monitoring, which are growing rapidly in the scientific and technological fields, real-time body monitoring during exercise and rehabilitation can be achieved. In this study, Fast Fourier Transform (FFT) and Wavelet Transform (WT) techniques were applied to the raw sEMG data obtained using textile-based electrodes, and the results were compared. The analysis of both techniques on the raw data was examined in detail. According to the results obtained, it has been seen that the Wavelet Transform method in signal processing offers a much more detailed analysis than the Fast Fourier technique.