The work was designed to offer a lower-cost and reliable option for acquiring surface electromyography (sEMG) signals. Initially, an acquisition system was developed, where, using an ESP32 Bluetooth module, the acquisition of biosignals was implemented with the help of the biopotential sensor based on AD8232. The backend was developed in the Python language and the Flask framework was used for the web application. The front end includes two pages. The main page is responsible for displaying the current value of each parameter, thus allowing the user to have control over the most relevant parameters for activating functional electrical stimulation (FES). The secondary page allows real-time visualization of data over time. The tool was developed with almost all the functionalities initially planned. However, this did not affect the final result, enabling professionals in the field and researchers to obtain sEMG data with a constant sampling rate, view the data live, and even manipulate the data acquired with the file that can be exported.