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Related Experiment Video

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A low-cost real-time embedded EOG-based assistive mobility system for individuals with motor function disorders.

Preetha S1, Sasikala M1, Mohanavelu K2

  • 1Department of Biomedical Engineering, College of Engineering Guindy, Anna University, Chennai, India.

Disability and Rehabilitation. Assistive Technology
|May 7, 2026
PubMed
Summary

This study developed a low-cost, real-time electrooculography (EOG) device to help individuals with motor impairments control wheelchairs using eye movements. The system achieved high accuracy, offering an accessible mobility solution.

Keywords:
Human-computer interaction (HCI)electrooculography (EOG)eye movementsreal-time wheelchair controlthreshold based classification

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Area of Science:

  • Biomedical Engineering
  • Assistive Technology
  • Human-Computer Interaction

Background:

  • Motor function disorders significantly impair mobility and well-being, increasing reliance on care.
  • Eye movements offer a viable channel for communication and control when motor function is compromised.
  • Electrooculography (EOG) records eye movements, presenting potential for advanced human-computer interaction (HCI).

Purpose of the Study:

  • To develop a real-time, low-cost electrooculography (EOG)-based assistive device for individuals with motor impairments.
  • To enable intuitive control of mobility devices, such as wheelchairs, through eye movement detection.
  • To create an accessible and reliable assistive technology solution, particularly for low-resource settings.

Main Methods:

  • A two-channel EOG system was designed, incorporating a custom amplifier and ESP32 microcontroller for signal processing.
  • EOG signals from various eye movements and blinks were recorded from both able-bodied and disabled participants.
  • A lightweight, subject-specific threshold-based classifier was implemented for efficient and accurate embedded deployment.

Main Results:

  • The system achieved 100% accuracy in healthy participants and 99.2% in disabled participants.
  • Mean response times were recorded at 2.03s for healthy and 2.04s for disabled participants, with high information transfer rates.
  • Classified eye movements and blinks were successfully mapped to wheelchair navigation commands, demonstrating intuitive control.

Conclusions:

  • The developed portable, real-time EOG system offers a practical and effective mobility solution for severe motor disabilities.
  • The low-cost and reliable design makes it suitable for low-resource environments, promoting inclusive assistive technology.
  • User feedback confirmed the system's ease of use, safety, and comfort, highlighting its potential for enhancing quality of life.