Badan Riset dan Inovasi Nasional
07-11-2022
12-08-2024
11c8cdc3-b6d2-4818-b647-bae9dcbec44d
In this paper, an application of nonlinear adaptive filter for online P300 extra...
By extracting specific brain activity from recorded EEG signals and linking it t...
An instrument that has special function to record electrical brain activity in s...
Artifacts or noise sources increase the difficulty in analyzing the EEG and to o...
The purification of recombinant proteins is an important stage in biopharmaceuti...
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A Comparison of Extraction Techniques for the rapid EEG-P300 Signals
In this paper, three different methods for brain signal acquisition are presented. All methods deal with feature extraction method of Electroencephalogram (EEG) based P300 waves. The performance of the three methods is investigated through backpropagation neural network classifier. EEG-P300 recordings provide an important means of brain-computer communication, but their classification accuracy and transfer rate are limited by unexpected signal variations due to artifacts and noises. A comparison of extraction methods (i.e., AAR, JADE, and SOBI) entailing time-series EEG signals is proposed. Finally, the promising results reported here reflect the considerable potential of EEG for the continuous classification of mental states. Advanced Science Letters, Volume 20, Number 1, January 2014 , pp. 80-85(6)