Prosthetic Hand Driven by Electromyographic Signals

Loss of upper limbs from accidents or medical conditions severely impacts an individual's quality of life, limiting mobility and independence. This project showcases the design implementation of a real-time prosthetic hand control system utilizing Electromyographic signals alongside motion data for incredibly natural movement simulation. The proposed system integrates the Arduino ESP32 MPU6050 accelerometer alongside the PCA9685 Servo Driver for interpreting muscle activity via complex algorithms. Leveraging EMG signals for muscle contraction detection alongside an accelerometer enables relatively smooth motion sensing, so the prosthetic hand offers an intuitive user experience. Researchers delve into hardware design, signal acquisition, and processing methods that facilitate the conversion of biological signals into functional hand gestures. This method significantly boosts prosthetic control precision, remaining affordable, making it a promising solution for people with upper limb issues.