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A robust minimum variance beamforming approach for the removal of the eye-blink artifacts from EEGs

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conference contribution
posted on 08.12.2009 by K. Nazarpour, Yodchanan Wongsawat, Saeid Sanei, Soontorn Oraintara, Jonathon Chambers
In this paper a novel scheme for the removal of eye-blink (EB) artifacts from electroencephalogram (EEG) signals based on the robust minimum variance beamformer (RMVB) is proposed. In this method, in order to remove the artifact, the RMVB is provided with a priori information, i.e., an estimation of the steering vector corresponding to the point source EB artifact. The artifact-removed EEGs are subsequently reconstructed by deflation. The a priori knowledge, namely the vector corresponding to the spatial distribution of the EB factor, is identified using a novel space-time-frequency-time/segment (STF-TS) model of EEGs, provided by a four-way parallel factor analysis (PARAFAC) approach. The results demonstrate that the proposed algorithm effectively identifies and removes the EB artifact from raw EEG measurements.

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School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

NAZARPOUR, K., 2007. A robust minimum variance beamforming approach for the removal of the eye-blink artifacts from EEGs. IN: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, (EMBS 2007), Lyon, France, 22-26 Aug., pp. 6211 - 6214

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© IEEE

Version

VoR (Version of Record)

Publication date

2007

Notes

This is a conference paper [© IEEE]. It is also available from: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISBN

9781424407873

ISSN

1557-170X

Language

en

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