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Content Provider | IET Digital Library |
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Author | Saha, Simanto Ahmed, Khawza I. Mostafa, Raqibul Khandoker, Ahsan H. Hadjileontiadis, Leontios |
Abstract | Electroencephalography (EEG) captures electrophysiological signatures of cortical events from the scalp with high-dimensional electrode montages. Usually, excessive sources produce outliers and potentially affect the actual event related sources. Besides, EEG manifests inherent inter-subject variability of the brain dynamics, at the resting state and/or under the performance of task(s), caused probably due to the instantaneous fluctuation of psychophysiological states. A wavelet coherence (WC) analysis for optimally selecting associative inter-subject channels is proposed here and is being used to boost performances of motor imagery (MI)-based inter-subject brain computer interface (BCI). The underlying hypothesis is that optimally associative inter-subject channels can reduce the effects of outliers and, thus, eliminate dissimilar cortical patterns. The proposed approach has been tested on the dataset IVa from BCI competition III, including EEG data acquired from five healthy subjects who were given visual cues to perform 280 trials of MI for the right hand and right foot. Experimental results have shown increased classification accuracy (81.79%) using the WC-based selected 16 channels compared to the one (56.79%) achieved using all the available 118 channels. The associative channels lie mostly around the sensorimotor regions of the brain, reinforced by the previous literature, describing spatial brain dynamics during sensorimotor oscillations. Apparently, the proposed approach paves the way for optimised EEG channel selection that could boost further the efficiency and real-time performance of BCI systems. |
Starting Page | 39 |
Ending Page | 43 |
Page Count | 5 |
Volume Number | 4 |
e-ISSN | 20533713 |
Issue Number | Issue 1, Feb (2017) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/htl/4/1 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/htl.2016.0073 |
Journal | Healthcare Technology Letters |
Publisher | The Institution of Engineering and Technology |
Publisher Date | 2017-02-20 |
Access Restriction | Open |
Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
Subject Keyword | Actual Event Related Sources Aids For The Handicapped Associative Sensorimotor Oscillations BCI Bioelectric Signal Biology And Medical Computing Biomedical Electrodes Brain Dynamics Brain Sensorimotor Regions Brain-computer Interfaces Classification Accuracy Computer Assistance For Persons with Handicaps Cortical Events Digital Signal Processing EEG Electrical Activity in Neurophysiological Processes Electrodiagnostics And Other Electrical Measurement Technique Electroencephalography Electrophysiological Signatures Enhanced Intersubject Brain Computer Interface Handicapped Aids High-dimensional Electrode Montages Intersubject Variability Medical Signal Processing Motor Imagery Prosthetics And Other Practical Application Psychophysiological State Scalp Sensorimotor Oscillations Signal Classification Signal Processing And Detection User InterFace Wavelet Coherence Analysis |
Content Type | Text |
Resource Type | Article |
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