This project demonstrates how electromyographic (EMG) signals can be used to control a prosthetic hand. The software acquires raw EMG data from surface electrodes, processes it in real time using digital filters, and translates the extracted muscle activity into control commands for servo motors.

All content pushed to this repository is part of my master’s thesis project titled "Decoding Concurrent Multi-DOF Wrist Movements from Electromyography Signals Using Deep Reinforcement Learning".

EMG signal classification for hand gesture recognition using machine learning for prosthetic control applications.