Design of a Wheelchair Control System Based on Hand Gesture Recognition Using ResNet18: Published online: 10/11/2025 - Tran, Vi Do; Nguyen, Cong Trung (Journal of Technical Education Science, 2025)
The development of wheelchairs utilizing advanced technology at low costs is gaining attention to improve the quality of life for approximately 800 million people with disabilities worldwide. These individuals often face challenges in mobility, access to education, and social integration. Among various wheelchair control methods, hand gesture control is considered optimal due to its efficiency and health safety. However, in Vietnam, research in this field remains limited. This project focuses on designing a smart wheelchair system using computer vision to recognize hand gestures and convert them into control commands, combining hardware and software solutions. The study employs deep learning models such as ResNet-18 for image processing, integrated on a Jetson Nano device, and hardware optimization to achieve the highest efficiency. Although challenges remain, such as ensuring accuracy in diverse environments and maintaining stable control under real-world conditions, this research promises not only to enhance user independence but also to open new opportunities in biomedical engineering. It contributes to improving the quality of life and fostering social inclusion for people with disabilities.