GestuLearn: Hand Tracking and Gesture Recognition Technology for Assistive Teaching in Special Education
Ivan Renz T. Eser, Adonis S. Santos, Marco A. Burdeos · 2024
Students with disabilities have received inadequate attention in terms of their engagement with technology. Research pertaining to this area is underdeveloped and while generic research often excludes this sector of the student population. Special education gives students with disabilities the opportunity to get quality education in line with their unique needs. As children progress through different stages, guided and comprehensive education becomes a cornerstone for maximizing their potential. Proper education equips them with the tools to navigate the challenges of abstract thinking and cultivates a well-rounded cognitive. Appropriate assistive technology has a direct impact on the well-being of children by supporting their functionality and inclusion into society, thereby increasing the opportunities for education. The project “GestuLearn” is an interactive learning system that utilizes real-time hand detection, tracking, and gesture recognition via computer vision, customized programming, and machine learning algorithms that is designed for assistive teaching to aid students with disabilities particularly the deaf, mute and with learning disabilities.