Prostheses develop in the individual a better quality of life, seeking to get as close as possible to the normal functions that a member would perform. Myoelectric prostheses are more comfortable and have more functionality than mechanical prostheses. However, in order to use a myoeletric system, it is necessary for the users to have muscle potentials that are strong enough to control the prosthesis. Thus, it is necessary to evaluate the active muscle groups and perform muscle recruitment work, so that the individual can control this prosthesis. It is known that repetitive activities are discouraging, which often leads to patients abandoning this rehabilitation work. With this, this work aims to develop a gamified platform for training and muscle assessment that will allow patients to become able to use a myoelectric prosthesis, and to promote a better adaptation to the use of this type of prosthesis. The developed hardware performs the simultaneous capture of 8 EMG signal channels. Multiplexers are used to switch each input to an output, avoiding an EMG signal acquisition circuit for each channel. After being processed, the signals are sent to the computer via Wi-Fi or Bluetooth (user choice) through the ESP32 microcontroller, where they can be viewed in a graphical interface developed using the C# language. Besides presenting the signals, the interface allows access to the envelope, the FFT of the signal, and it also has a biofeedback tab with games that can be controlled with the EMG signal. The developed system will allow the training and assessment of each patient's muscle groups in a more attractive way, promoting a better adaptation to the use of a myoelectric prosthesis.