Multi-channel linear descriptors for event-related EEG collected in brain computer interface

Journal of Neural Engineering
Xiao-mei PeiHong-wu Wang

Abstract

By three multi-channel linear descriptors, i.e. spatial complexity (omega), field power (sigma) and frequency of field changes (phi), event-related EEG data within 8-30 Hz were investigated during imagination of left or right hand movement. Studies on the event-related EEG data indicate that a two-channel version of omega, sigma and phi could reflect the antagonistic ERD/ERS patterns over contralateral and ipsilateral areas and also characterize different phases of the changing brain states in the event-related paradigm. Based on the selective two-channel linear descriptors, the left and right hand motor imagery tasks are classified to obtain satisfactory results, which testify the validity of the three linear descriptors omega, sigma and phi for characterizing event-related EEG. The preliminary results show that omega, sigma together with phi have good separability for left and right hand motor imagery tasks, which could be considered for classification of two classes of EEG patterns in the application of brain computer interfaces.

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Citations

Mar 28, 2008·Computational Intelligence and Neuroscience·W L Woon, A Cichocki
May 17, 2011·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·Wutao LouSongzhen Zhao
Jul 9, 2013·Journal of Biosocial Science·Olga MaslovskayaSabu S Padmadas

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Brain-Computer Interface

A brain-computer interface, also known as a brain-machine interface, is a bi-directional communication pathway between an external device and a wired brain. Here is the latest research on this topic.

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