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Real-time target selection based on electroencephalogram (EEG) signal


Article Information

Title: Real-time target selection based on electroencephalogram (EEG) signal

Authors: Muhammad Shaufil Adha, Norlaili Mat Safri, Mohd Afzan Othman

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2015

Volume: 10

Issue: 19

Language: English

Categories

Abstract

Electroencephalogram (EEG)-based mobile system are getting mainstream although the true potential of EEG signals are yet to be discovered. With the help of a specific control paradigm, the success rate of a mobile system to reach to a certain location could be increased. To further extend the existed control paradigm of EEG-Based mobile robotic system, this paper demonstrated the real time target selection of a wireless mobile robot using only human mind. A unique protocol was developed to mimic a scanning process while at the same time allowing subject to make a selection. Our system utilized only single EEG channel with no subject training. We statistically verify that it is feasible to select a target by manipulating only alpha content of EEG. We also show that it is hard to achieve a stable high performance of synchronous EEG-Based BCI application in one trial with a single frequency band. However, we found that the BCI’s performance in term of sensitivity are getting more stable with increase in trial.


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