Randomized trial demonstrates high detection accuracy in wheelchair control using gaze metrics, indicating enhanced mobility for individuals with impairments.
Intelligent wheelchair systems are crucial for enabling hands-free mobility in individuals with severe physical impairments. This paper presents a novel eye-movement-based wheelchair control system that integrates camera-based gaze detection with fuzzy logic decision-making. By analyzing the Eye Aspect Ratio (EAR), along with horizontal and vertical gaze ratios, the system interprets real-time eye movements into five navigational commands: “Move Forward,” “Move Backward,” “Move Left,” “Move Right,” and “Stop.” A time threshold mechanism (2–5 seconds) ensures intentionality by filtering out involuntary gaze fluctuations. The novelty of this work lies in its hybrid use of real-time video processing and fuzzy logic reasoning to improve directional decision accuracy while maintaining non-invasive interaction. The system achieves a high detection accuracy of 99.8% with excellent performance in terms of precision, recall, and geometric mean. Unlike previous works that depend on wearable electrodes or basic rule-based classifiers, this work emphasizes adaptability, comfort, and stability in dynamic environments. The proposed solution demonstrates strong potential for assistive mobility, promoting independence and user comfort without the need for intrusive hardware.
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Abdulkareem et al. (2026) studied this question.