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A robust minimum variance beamforming approach for the removal of the eye-blink artifacts from EEGs
conference contribution
posted on 2009-12-08, 17:18 authored by K. Nazarpour, Yodchanan Wongsawat, Saeid Sanei, Soontorn Oraintara, Jonathon ChambersIn 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.
History
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 - 6214Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
2007Notes
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
9781424407873ISSN
1557-170XLanguage
- en