Abd Gani, Shamsul Fakhar and A Aziz, Khairul Azha and Kamalrudin, Massila and Miskon, Muhammad Fahmi and Hamzah, Rostam Affendi and Kadmin, Ahmad Fauzan and Jidin, Aiman Zakwan and Md Basar, Mohd Farriz and A Razak, 'Eizza Noor Sabrina and Md Ali Shah, M. A.S. (2021) Electrical Appliance Switching Controller By Brain Wave Spectrum Evaluation Using A Wireless EEG Headset. International Journal of Emerging Technology and Advanced Engineering, 11 (10). pp. 109-117. ISSN 2250-2459
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Abstract
Disabled people are usually unable to interact with their surroundings efficiently, and performing tasks like switching an appliance on or off can be troublesome if the user is bedridden, for example. This article discusses an electrical appliance switching controller using a wireless EEG headset that is aimed to aid elderly people and the disabled. The system comprises of a MindLink EEG headset that is Bluetooth-connected to an Arduino microcontroller board. The system permits the user to separately switch on and off the 4 electrical devices connected to the power socket. The EEG signal is obtained to investigate the brain activity throughout the experiments done. Based on the brain wave signals read, attention and meditation are determined to be the most suitable for this project and is used to trigger the relay switching of the power socket. It is found that the response time to trigger the switching is slow as some users require practice or training to control their brain wave signals effectively. The work performed provides a rudimentary insight of a BCI system functionalities and presents a brainwave-controlled hardware switching for the bedridden or disabled patients.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Electroencephalography, EEG, Smart Home, Brain Computer Interface, BCI Application. |
| Depositing User: | Norfaradilla Idayu Ab. Ghafar |
| Date Deposited: | 05 May 2022 12:13 |
| Last Modified: | 05 May 2022 12:13 |
| URI: | http://eprints.utem.edu.my/id/eprint/25764 |
| Statistic Details: | View Download Statistic |
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