The electromyographic (EMG) signals analysis is imperative to understand the muscles behaviour under several diseases or fatigue studies. Although there are required sophisticated devices and algorithms, it is possible to obtain information using simpler techniques. The prototype that was developed has features for sEMG recording, such as high common mode reject (CMR), high coupling impedance, high gain and 2 stages of active filters. Besides, the analog to digital conversion is performed with an ADC Delta-Sigma converter. Besides, we propose a decomposition algorithm with 5 stages: pre-processing, segmentation, clustering, classification and a spatial filtering stage. We obtained successfully sEMG signals and we detect Motor Unit Action Potentials (MUAPs) of the same Motor Unit (MU) with a similarity over 80% between them.