ELECTROMYOGRAPHY (EMG) SENSOR - CONTROLLED PROSTHETIC ARM

Electronics and Communication, Signal Processing, Biomedical Engineering, and Assistive Technology

Electromyography (EMG) sensor-controlled prosthetic arms represent a significant advancement in assistive technology, offering individuals with limb loss an intuitive way to control artificial limbs using natural muscle signals. This research focuses on the design and development of a cost-effective, Arduino-based prosthetic arm, leveraging open-source technology to provide an accessible alternative to expensive commercial options. The system employs EMG sensors to detect electrical activity generated by muscle contractions in the residual limb. These signals are processed through amplification and filtering circuits, then interpreted by an Arduino microcontroller to control the prosthetic arm’s movements. Advanced noise-reduction filters and threshold algorithms ensure accurate signal interpretation, enabling precise control of actions like gripping, lifting, and releasing. The prosthetic is constructed using lightweight actuators and 3D-printed components, offering a modular and affordable design that closely mimics the natural motion of a human hand. Testing confirms the prototype’s ability to interpret EMG signals with minimal delay, providing users with responsive and functional control over a range of movements. The adaptability of the Arduino platform allows for customization based on individual user needs, making the system highly versatile. This study contributes to the field of prosthetic technology by demonstrating the potential for scalable, open-source solutions that enhance independence and improve quality of life for users. It bridges neuroscience and engineering, paving the way for future innovations in affordable and customizable assistive devices.

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