Advanced Eye Movement Tracking Using Computer Vision for Physically Disabled Patients

Authors

Anitha V R, BMS Institute of Technology and Management, BengaluruFollow
Nisha Ponnambalam, BMS Institute of Technology and Management, BengaluruFollow
Impana Bharadwaj, BMS Institute of Technology and Management, BengaluruFollow
Rajat Mundhra, BMS Institute of Technology and Management, BengaluruFollow

Abstract

The paper introduces an efficient mobility assistance system to empower individuals with moderate to severe physical disabilities and chronic disorders such as Quadriplegia (Paralysis of four limbs) and Amyotrophic Lateral Sclerosis, utilizing advanced technology. The project focuses on developing an affordable eye-controlled wheelchair using Raspberry Pi, Pi camera, DC motors, proximity sensor, and computer vision technology. The core innovation involves integrating a Pi camera onto the wheelchair to obtain a live acquisition feed of the patient’s eye. This captured eye movement serves as a control input to the Raspberry Pi board. Advanced computer vision algorithms analyze and translate the patient’s gaze into precise direction commands for the DC motor drivers, facilitating wheelchair navigation. In addition, an integrated proximity sensor enhances patient safety by detecting obstacles and preventing collisions. The core objective of this project is to provide an affordable, accessible, and efficient solution for individuals with disabilities caused because of paraplegic and quadriplegic diseases, to improve their quality of life and independence.

Recommended Citation

V R, Anitha; Ponnambalam, Nisha; Bharadwaj, Impana; and Mundhra, Rajat (2024) "Advanced Eye Movement Tracking Using Computer Vision for Physically Disabled Patients," Manipal Journal of Science and Technology: Vol. 9: Iss. 1, Article 3.
Available at: https://impressions.manipal.edu/mjst/vol9/iss1/3