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Design and Performance Evaluation of a Low-Cost Adaptive Myoelectric Prosthetic Arm with Multi-Modal Control
Subject area: Science,Engineering and Technology · Area of research: Biomedical Engineering
Abstract
This project addressed the challenge of upper-limb amputation, which significantly limits independence and daily function, making basic activities such as eating, lifting objects, and writing difficult. Conventional myoelectric prosthetic arms offer improved control but remain expensive and largely inaccessible in resource-limited environments. The study aimed to develop a low-cost, adaptive myoelectric prosthetic arm that integrated EMG-based control with a gesture glove backup, incorporating adaptive grip feedback to enhance usability and reliability. This system was designed using locally available materials and off-the-shelf components, including an ESP32 microcontroller, servo motors, and EMG sensors. The hand and wrist frame were fabricated via 3D printing, while the socket and glove utilized adjustable foam and flexible textiles. The design consisted of three subsystems, EMG Control Unit, Flex sensor gesture glove and Adaptive Grip Feedback System, coordinated by the ESP32 for seamless mode switching, with functional diagrams and flow charts illustrating sensor-actuator-controller interaction. Performance was evaluated through functional and user tests, focusing on response time, grip force, error rates, and battery endurance. Participants performed daily activities, including object manipulation, while feedback on comfort, ease of use, and confidence was collected and analyzed using descriptive statistics and thematic grouping. The project delivered a scalable, affordable prosthetic solution aimed at reducing device abandonment and improving amputees' quality of life. Future work should refine control algorithms, test across diverse climates and user groups, and enhance modularity for broader adoption.
Keywords
Electromyography control unit, ESP 32, Adaptive grip.
References
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How to cite this paper
@article{1723260,
author = {Saka Adekunle Ridwan, Olaoye Olusegun Solomon},
title = {Design and Performance Evaluation of a Low-Cost Adaptive Myoelectric Prosthetic Arm with Multi-Modal Control},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {3},
pages = {2561-2572},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723260.pdf},
abstract = {This project addressed the challenge of upper-limb amputation, which significantly limits independence and daily function, making basic activities such as eating, lifting objects, and writing difficult. Conventional myoelectric prosthetic arms offer improved control but remain expensive and largely inaccessible in resource-limited environments. The study aimed to develop a low-cost, adaptive myoelectric prosthetic arm that integrated EMG-based control with a gesture glove backup, incorporating adaptive grip feedback to enhance usability and reliability. This system was designed using locally available materials and off-the-shelf components, including an ESP32 microcontroller, servo motors, and EMG sensors. The hand and wrist frame were fabricated via 3D printing, while the socket and glove utilized adjustable foam and flexible textiles. The design consisted of three subsystems, EMG Control Unit, Flex sensor gesture glove and Adaptive Grip Feedback System, coordinated by the ESP32 for seamless mode switching, with functional diagrams and flow charts illustrating sensor-actuator-controller interaction. Performance was evaluated through functional and user tests, focusing on response time, grip force, error rates, and battery endurance. Participants performed daily activities, including object manipulation, while feedback on comfort, ease of use, and confidence was collected and analyzed using descriptive statistics and thematic grouping. The project delivered a scalable, affordable prosthetic solution aimed at reducing device abandonment and improving amputees' quality of life. Future work should refine control algorithms, test across diverse climates and user groups, and enhance modularity for broader adoption.},
keywords = {Electromyography control unit, ESP 32, Adaptive grip.},
month = {September},
}