Electrooculogram Based Wheelchair Control in Real-Time

DOI

10.2991/978-94-6463-252-1_8How to use a DOI?

Keywords

Electrooculogram; Motor disability; Wheelchair; Human-Machine Interface

Abstract

The goal of this work is to provide solutions for needs of patients suffering from Amyotrophic Lateral Sclerosis (ALS), tetraplegic clinical conditions (e.g., the locked-in syndrome), paralysis or other progressive illnesses, disabled and/or elderly with acute disabilities in moving their whole bodies due to motor system disorders which prevent accurate and correct limb and facial muscular responses. We propose to establish an efficient alternative channel for communication and control based on Electrooculogram (EOG) that operates by the only muscular movement that these patients are capable of i.e., the eyeball movement. Ability to control some household devices, electric wheelchair, and computer with eye movement facility by elderly or severely disabled persons reduces their dependency on others. This not only improves their lives, but also makes them more self-assured and self-reliant. This paper describes the design and development of a Smart, Motorized, Bluetooth controlled Wheelchair for the physically differently abled people where their eyeball movements act as commands and controls the movements of the wheelchair. To test the performance of the system, four volunteers were asked to make 20 eye movements randomly per person and the direction of movement of wheelchair was observed for each movement. All the 80 eye movements made by the four volunteers were identified with 100% accuracy, generating the corresponding command, and moving the wheelchair in the desired direction.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Harikrishna Mulam
AU  - Malini Mudigonda
AU  - B. P. Santosh Kumar
AU  - Harish Kuchulakanti
PY  - 2023
DA  - 2023/11/09
TI  - Electrooculogram Based Wheelchair Control in Real-Time
BT  - Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
PB  - Atlantis Press
SP  - 55
EP  - 67
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-252-1_8
DO  - 10.2991/978-94-6463-252-1_8
ID  - Mulam2023
ER  -