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1714539 Vol 9 · Issue 8 Download Paper

Eye-Controlled Wheelchair by Eye Coordinates Extraction

Adarsh Ajayan Saranya S R

Subject area: Science,Engineering and Technology  ·  Area of research: Mechatronics

DOI: https://doi.org/10.64388/IREV9I8-1714539

Abstract

This project deals with a motorized wheelchair designed for those who cannot move their limbs. The project aims to motorize a wheelchair, control the wheelchair's speed, interface a camera module to micro-controller and assign controls to the wheelchair corresponding to the movement of eyeballs. Here the motion of the wheelchair is based on tracking of eyeballs. The camera captures the eyeball movement and is correspondingly coded, so that the wheelchair is moved. This method replaces the joystick mechanism, which cannot be used by paralyzed people. First, the code is tested using Python language using the Open-CV library on Anaconda IDE. Later, it will be tested on the Raspberry Pi module

Keywords

Dlib Library, Eye-Tracking, Image Processing, Raspberry Pi.

References

[1] Sandesh Pai, Sagar Ayare, Romil Kapadia, “Eye Controlled Wheelchair”, International Journal of Scientific Engineering Research, Volume 3, Issue 10, October- 2012 1 ISSN 2229-5518.

[2] Snehlata Yadav, Poonam Sheoran, "Smart Wheelchairs - A literature review", International Journal of Innovative and Emerging Research in Engineering, Volume 3, Issue 2, 2016.

[3] Shawn Plesnick, Domenico Repice, Patrick Loughnane, "Eye-Controlled Wheelchair", Department of Electrical and Computer Engineering, IEEE Canada International Humanitarian Technology Conference - (IHTC), 2014.

[4] Dulari Sahu, ”Automatic Camera Based Eye Controlled Wheelchair System Using Raspberry Pi”, International Journal of Science, Engineering and Technology Research (IJSETR), Volume 5, Issue 1, January 2016.

[5] Anita Jindal, Rashmi Priya, "Landmark Points Detection in Case of Human Facial Tracking and Detection", International Journal of Engineering and Advanced Technology (IJEAT), December 2019.

[6] Aleksandar Pajkanovic and Branko Dokic, "Wheelchair Control by Head Motion", Serbian Journal of Electrical Engineering, Vol. 10, No. 1, 135-151, February 2013.

How to cite this paper

Adarsh Ajayan, Saranya S R "Eye-Controlled Wheelchair by Eye Coordinates Extraction" Iconic Research And Engineering Journals Volume 9 Issue 8 2026 Page 2148-2152 https://doi.org/10.64388/IREV9I8-1714539
Adarsh Ajayan, Saranya S R "Eye-Controlled Wheelchair by Eye Coordinates Extraction" Iconic Research And Engineering Journals, vol. 9, no. 8, Feb. 2026, doi: https://doi.org/10.64388/IREV9I8-1714539
Adarsh Ajayan, Saranya S R (2026). Eye-Controlled Wheelchair by Eye Coordinates Extraction. Iconic Research And Engineering Journals, 9(8). doi: https://doi.org/10.64388/IREV9I8-1714539
Adarsh Ajayan, Saranya S R "Eye-Controlled Wheelchair by Eye Coordinates Extraction" Iconic Research And Engineering Journals, vol. 9, no. 8, Feb. 2026. Crossref, https://doi.org/10.64388/IREV9I8-1714539
@article{1714539,
      author = {Adarsh Ajayan, Saranya S R},
      title = {Eye-Controlled Wheelchair by Eye Coordinates Extraction},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {8},
      pages = {2148-2152},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1714539.pdf},
      abstract = {This project deals with a motorized wheelchair designed for those who cannot move their limbs. The project aims to motorize a wheelchair, control the wheelchair's speed, interface a camera module to micro-controller and assign controls to the wheelchair corresponding to the movement of eyeballs. Here the motion of the wheelchair is based on tracking of eyeballs. The camera captures the eyeball movement and is correspondingly coded, so that the wheelchair is moved. This method replaces the joystick mechanism, which cannot be used by paralyzed people. First, the code is tested using Python language using the Open-CV library on Anaconda IDE. Later, it will be tested on the Raspberry Pi module},
      keywords = {Dlib Library, Eye-Tracking, Image Processing, Raspberry Pi.},
      month = {February},
      doi = {https://doi.org/10.64388/IREV9I8-1714539}
  }