Development of an Adaptive AI-Enhanced Prosthetic Arm for Physically Impaired Children
Manal Al Khaldi, Tariq Al Balushi, Amin Al Maqbali, Amuthakkannan Rajakannu · International Journal of Electrical and Electronics Engineering · 2025
This research addresses the critical gap in pediatric prosthetics for children by developing an adaptive prosthetic arm tailored to children aged 7 to 14, a demographic often overlooked in prosthetic innovation. Rapid physical growth during this age requires frequent adjustment and more medical care. Because of the requirement for frequent adjustment, pediatric prosthetics are more complex than adult models. Existing solutions have disadvantages, such as difficulty adapting adult designs and lack of the ergonomic, functional, and psychological considerations required for children. This work introduces a novel prosthetic arm that integrates Artificial Intelligence (AI) and Deep Learning (DL) to enhance adaptability, control, and user experience. In the initial phase of the work, the existing models and their disadvantages were considered. Then, the new design is developed, which leverages biosensors and electromyographic (EMG) signals for intuitive gesture recognition, enabling tasks such as gripping, pinching, and twisting. After developing the design, a 3D printer was used to create the arm. The arm was tested in real-time, and the AI developed with the prosthetic arm showed a promising overall accuracy of 91%. This shows the design and other components’ accuracy and that the proposed arm design can be implemented for pediatric prosthetics.