Abstract:
This project presents the design and implementation of an Arduino-based prosthetic hand with adaptive EMG control, offering an affordable and functional solution for upper-limb amputees. Traditional prosthetics are often prohibitively expensive and lack intuitive control, creating accessibility challenges. Our system integrates EMG sensors to detect muscle signals, an Arduino Nano for real-time signal processing, servo motors for finger actuation, and a lightweight 3D-printed structure, resulting in a total cost under 11,000 BDT. The prosthetic hand translates residual muscle activity into natural grasping motions through threshold-based algorithms, achieving 95% movement accuracy in user testing with a response time of 0.5 seconds. Key innovations include customizable 3D-printed components, open-source hardware, and energy-efficient operation powered by a lithium-ion battery. The project addresses critical gaps in affordability and adaptability while adhering to biomedical engineering standards. Results demonstrate the potential to democratize access to advanced prosthetics, particularly in resource-limited settings. Future work may incorporate machine learning for enhanced control and Bluetooth connectivity for user customization. This research contributes to the growing field of low-cost assistive technologies, merging biomedical engineering with accessible design principles to improve quality of life for amputees.
