EMG-RoboArm: Restoring Hand Function Utilizing EMG Technology for Intuitive Prosthetic Control | ||||
| Advanced Sciences and Technology Journal | ||||
| Articles in Press, Accepted Manuscript, Available Online from 22 August 2025 | ||||
| Document Type: Case Study | ||||
| DOI: 10.21608/astj.2025.369893.1054 | ||||
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| Author | ||||
Shukri Mahmoud Shukri 
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| Faculty of Engineering, Shubra, Benha University | ||||
| Abstract | ||||
| This research focuses on developing an affordable, intuitive, and customizable robotic prosthetic arm for individuals with partial hand amputations. The prosthetic leverages electromyography (EMG) technology to detect residual muscle activity in the forearm, allowing for natural and precise control. The primary goal is to restore essential hand functions, such as grasping, holding, and releasing objects, to improve the user’s quality of life. The design integrates EMG signal acquisition, an Arduino-based control system, and 3D-printed mechanical components, ensuring a lightweight, durable, and cost-effective solution. Modularity is a key aspect, allowing for customization based on individual user needs and enabling future upgrades as technology advances. Significant achievements of the project include the successful integration of EMG sensors with an Arduino microcontroller, which processes muscle signals in real-time to control servo motors accurately. Advanced control algorithms map EMG signals to specific hand gestures, making the prosthetic intuitive and highly responsive. Additionally, the use of 3D printing and open-source components significantly reduces manufacturing costs, making the prosthetic more accessible to underserved populations. By addressing key challenges such as signal reliability, user adaptability, and affordability, this research contributes to the development of practical, scalable prosthetic solutions. The findings underscore the importance of integrating EMG technology with open-source hardware to create functional, cost-effective alternatives to traditional prosthetics, ultimately enhancing the independence and daily capabilities of individuals with partial hand amputations. | ||||
| Keywords | ||||
| Myoelectric systems; Biomedical signal processing; Assistive robotics; Open-source hardware; Rehabilitation engineering | ||||
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