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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 2 (February 2026).... Submit articles

Design of an EEG-controlled wheelchair and home automation through brain computer interface

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  • Design of an EEG-controlled wheelchair and home automation through brain computer interface

K M Priya *, A Rishikumar and S Dhanaseelan

Department of ECE, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu, India.

Research Article

World Journal of Advanced Engineering Technology and Sciences, 2025, 14(2), 127-137

Article DOI: 10.30574/wjaets.2025.14.2.0066

DOI url: https://doi.org/10.30574/wjaets.2025.14.2.0066

Received on 31 December 2024; revised on 11 February 2025; accepted on 14 February 2025

This paper presents the design of an EEG-based brain-controlled wheelchair and home automation system using Brain Computer Interface (BCI) with the NeuroSky Mind Wave Mobile 2 headset. Mobility impairment is a significant challenge that affects the daily lives of millions of individuals with disabilities worldwide. While traditional assistive devices such as wheelchairs offer mobility support, they often require significant physical manipulation. The integration of neurotechnology presents an exciting opportunity to overcome these limitations by enabling direct control of assistive devices using brain signals. This system acquires EEG signals from the brain and analyzes them to obtain attention and eyeblink parameters. These parameters are then utilized to control the wheelchair's movement and operate simple electrical devices such as fans and lights for home automation. The system is primarily intended to assist Quadriplegic patients who are unable to move any part of their body below their neck. It incorporates various components including the HC-05 Bluetooth module, HC-SR04 module, L293D, 16x2 LCD, Arduino UNO, and ESP 32 microcontroller.

Electroencephalogram (EEG); Brain-Computer Interface (BCI); Attention level; Eyeblink; Wheel chair; Home automation

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2025-0066.pdf

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K M Priya, A Rishikumar and S Dhanaseelan. Design of an EEG-controlled wheelchair and home automation through brain computer interface. World Journal of Advanced Engineering Technology and Sciences, 2025, 14(2), 127-137. Article DOI: https://doi.org/10.30574/wjaets.2025.14.2.0066.

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