Development of an Open-Closed Eye Detector of Alternative Communication for Users with Severe Disabilities

Efforts to enhance autonomy for people with disabilities have become a focal point of medical and academic research. Alternative communication methods aim to improve independence and quality of life for individuals with severe disabilities. However, many existing approaches are costly or complex, limiting access for many patients. In this paper, we developed an open-closed eye detection system using the ESP32-CAM microcontroller, which is affordable, independent, and computer-cost-effective. Our hypothesis suggests that by analyzing a grayscale image, we can determine if an eye is open or closed just using an $1 \times 120$ vector dimension, rather than processing all 19200 image pixels. Our results achieved a 100% success rate for the experimental group, validating our proposed approach and hypothesis.