Investigating Powered Wheelchair Control via a Pupil-Center Detection Algorithm with a Glass-Mounted Visible-Light Camera

Abstract

Gaze input for electric wheelchairs offers an alternative to joysticks, but conventional dwell-time methods suffer from user fatigue and the "Midas Touch"problem. Furthermore, their reliance on infrared (IR) cameras leads to high costs and poor robustness outdoors due to sunlight. This study proposes an IR-free system combining the Eye-Glance gesture method with a low-cost, visible-light (RGB) camera. While our prior work introduced this concept, its simple algorithm was limited to indoor use. We overcome this by introducing a new pupil-center detection algorithm based on image saturation, shape constraints, and blink handling, specifically designed to tolerate ambient light changes. Evaluation with 8 participants performing four gestures under indoor and outdoor conditions achieved average first-attempt success rates of 95.9% (indoors) and 94.4% (outdoors). This work demonstrates that our visible-light pipeline provides a low-cost, robust gaze interface suitable for electric wheelchairs in varied environments.