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Eyeball Movement Based Wheel Chair Control System
Subject area: Science,Engineering and Technology · Area of research: Electronics and communication Engineering
Abstract
Many people are suffering from the disease called Quadriplegia which means the forelimbs of those people do not work. Some People cannot walk, and they can?t even move because of major accidents. The number of persons suffering from Quadriplegia is increasing with increase in the population of the world. For such people, the main source for movement is the Wheelchair. It is very helpful for the people if those wheel chairs are automated. Some systems have already come into existence such as voice controlled wheel chair, gesture controlled wheel chair. But these systems have some drawbacks as they cannot be used by the persons who cannot move their hands, and voice controlled systems are vulnerable to noise. Therefore, to overcome those, we propose Eye ball movement Based Wheel chair control system which moves in the desired direction that the person wants to move. Here we are counting the eye blinks. Based on the blinks count we are going to monitor the eye ball movement. We use eye detection, processing of the captured images and interfacing the raspberry pi with motor drivers to control the wheelchair. We also include IR sensors for obstacle detection in left, right, forward direction.
Keywords
Eye blink, Eye ball movement, IR(infrared) sensor, Quadriplegia, Raspberry pi
References
[1] Shawn Plesnick, Domenico Repice and Patrick Loughnane Eye controlled Wheelchair IEEE Canada International Humanitarian Technology conference 2014
[2] Miss. Maind Pallavi R Eye monitoring Wheel chair using Raspberry pi International Journal for Research trends and innovation volume 3 2018
[3] Jatin Sharma Iris movement based Wheel chair control using raspberry pi Institute of Physics publishing Conference series 2017
[4] D. Sharath babu rao, T. Anusha Gesture Controlled Wheel chair International Journal of Science Engineering and Technology Research volume 4 august 2015.
[5] Sugandh goswami Eye movement based Wheel chair control system for physically challenged persons paper presented in National conference on research engineering trends NCRET Iconic journal of Research 2016
[6] Srimathi P Kanthini B Wheel chair control using Eye tracking system for assisted mobility Intenational journal for research in applied science and engineering Technology volume 1 2015
[7] Dulari Sahu Automatic Camera Based Eye Controlled Wheelchair System Using Raspberry Pi International Journal of Science, Engineering and Technology Research 2016
[8] https://www.pyimagesearch.com/2017/04/24/eye- blink-detection-opencv-python-dlib
How to cite this paper
@article{1702056,
author = {M.Vasantha Lakshmi, N. V. Srinivas, M. Lakshminadh, N. Sathish Kumar, M. Hareesh Teja},
title = {Eyeball Movement Based Wheel Chair Control System},
journal = {Iconic Research And Engineering Journals},
year = {2020},
volume = {3},
number = {9},
pages = {191-195},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1702056.pdf},
abstract = {Many people are suffering from the disease called Quadriplegia which means the forelimbs of those people do not work. Some People cannot walk, and they can?t even move because of major accidents. The number of persons suffering from Quadriplegia is increasing with increase in the population of the world. For such people, the main source for movement is the Wheelchair. It is very helpful for the people if those wheel chairs are automated. Some systems have already come into existence such as voice controlled wheel chair, gesture controlled wheel chair. But these systems have some drawbacks as they cannot be used by the persons who cannot move their hands, and voice controlled systems are vulnerable to noise. Therefore, to overcome those, we propose Eye ball movement Based Wheel chair control system which moves in the desired direction that the person wants to move. Here we are counting the eye blinks. Based on the blinks count we are going to monitor the eye ball movement. We use eye detection, processing of the captured images and interfacing the raspberry pi with motor drivers to control the wheelchair. We also include IR sensors for obstacle detection in left, right, forward direction.},
keywords = {Eye blink, Eye ball movement, IR(infrared) sensor, Quadriplegia, Raspberry pi},
month = {March},
}