Sistema de control para sillas de ruedas mediante seguimiento ocular para mejorar la movilidad de personas con discapacidad motriz.

This research project develops an eye-tracking-based control system for wheelchairs, designed to improve the mobility and autonomy of people with severe motor disabilities. The implementation integrates tools such as real-time video processing with MediaPipe, a camera for eye movement detection, an ESP32 with drivers for brushless motor management, and a central processor. The effectiveness of the system was validated using the Barthel Index. The project was carried out in three phases. First, after a literature review, a non-invasive tracking technique was selected that guarantees safety and accuracy. Second, the system was programmed in Python under the criteria of a modular architecture, allowing the system to be adapted to different chairs without complex structural modifications. Third, tests were carried out in a controlled environment; the comparative results showed a significant improvement in user independence, reducing the need for external assistance. It is concluded that eye control is a viable and safe technological solution. It is recommended that future versions integrate hybrid modalities, such as joysticks and line-tracking technology, to maximize the robustness and versatility of the tool, thus promoting the inclusion and quality of life of the user.

• Auteur principal: Guzque Llamuca, Henry Leonardo (author)
• Autres auteurs: Quintero Gamboa, Henry Joshua (author)
• Format: bachelorThesis
• Langue: spa
• Publié: 2026
• Sujets: MediaPipe; Python; Seguimiento ocular; Silla de ruedas
• Accès en ligne: http://dspace.unach.edu.ec/handle/51000/16429