Eye-Tracking Based Control of a Robotic Arm and Wheelchair for People with Severe Speech and Motor Impairment (SSMI)

EasyChair Preprint 12221

Abstract

Eye-tracking technology has rapidly gained popularity as a revolutionary solution for individuals with severe physical disabilities, empowering them to engage in their daily activities with newfound independence and efficiency. By utilizing advanced eye-tracking systems, individuals with limited mobility are able to control various devices and interfaces simply by moving their eyes. This paper utilizes deep learning techniques to create a low-cost real-time eye-tracking interface for controlling systems. A smart wheelchair and a robotic arm have been developed to design an eye-tracker, aiming to address the challenges faced by paralyzed people with severe physical limitations. The results demonstrate that eye-tracking is both fast and accurate, making it an effective tool for improving the interactions and accessibility for disabled individuals.

Keyphrases: Smart Wheelchair, computer vision, control system, deep learning, eye tracking, robotic arm

@booklet{EasyChair:12221,
  author    = {Maryam Asad Samani and Kiana Hooshanfar and Helia Shams Jey and Seyed Majid Esmailzadeh},
  title     = {Eye-Tracking Based Control of a Robotic Arm and Wheelchair for People with Severe Speech and Motor Impairment (SSMI)},
  howpublished = {EasyChair Preprint 12221},
  year      = {EasyChair, 2024}}