INTEGRATION ARTIFICIAL INTELLIGENCE FEATURES TO WHEELCHAIR MODEL

Abstract

The integration of artificial intelligence (AI) in assistive technologies has gained significant attention in recent years, particularly in enhancing mobility devices such as wheelchairs. The potential of incorporating AI features into wheelchair models lies in advancing navigation capabilities and improving user interaction. Traditional wheelchairs often appear basic and may pose safety risks, especially when used by a single individual without assistance. In response to this concern, the researchers conducted this study to design and develop a prototype wheelchair enhanced with AI features, aiming to improve both its strength and safety. This quantitative descriptive study assessed the acceptability of integrated AI features in a wheelchair model. Using purposive sampling, five electrical engineers and five IT experts evaluated the design through a questionnaire, which focused on key aspects such as materials, mechanics, functionality, safety, and overall presentation. Statistical tools—including Student’s Percentage, Weighted Mean, and t-test—were employed to determine any significant differences in the assessments between the two groups of experts. To support the evaluation process, the researchers constructed a prototype wheelchair model using popsicle sticks and cardboard. Both the electrical engineers (overall mean = 3.70) and the IT experts (overall mean = 3.16) rated the AI-integrated wheelchair design as highly acceptable and acceptable, respectively. A t-test analysis (α = 0.05, df = 326, t-critical = 2.306, t-computed = 0.876) revealed no significant difference between the assessments of the two groups across the evaluated criteria: materials, mechanics, functionality, safety, and presentation. As a result, the null hypothesis was accepted. The AI-integrated wheelchair design will be refined based on expert feedback. Proposed improvements include the use of durable yet lightweight materials such as carbon fiber and aluminum alloy and the enhancement of seat comfort through ergonomic cushioning. The motor will be upgraded to ensure smoother and more energy-efficient movement. Additional features will include multi-modal control options such as voice commands, eye tracking, and joystick navigation, as well as integrated fall detection and alert systems. Safety will be further improved through enhanced emergency stop mechanisms and braking systems. Lastly, the overall design will be refined to improve both aesthetics and ergonomic functionality.