A hybrid RABWC-STF method for eye-blink removal from EEG

Author

Yi, Jun ; Su, Fei ; Cai, Anni

Author_Institution

Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2010

fDate

10-13 Oct. 2010

Firstpage

4288

Lastpage

4294

Abstract

In this paper, a hybrid method of the Robust Adaptive Beamforming based on Worst-case Performance Optimization (RABWC) and Space-Time-Frequency (STF) model is utilized for the eye-blink removal. RABWC is utilized to extract electrooculogram (EOG) signal and the STF model to provide an estimation of the steering vector corresponding to EOG for RABWC. Benefiting from the solution uniqueness of PARAFAC and the robustness of RABWC, this method can obtain a robust result without imposing irrational constraints.

Keywords

array signal processing; electro-oculography; electroencephalography; medical signal processing; optimisation; EEG; PARAFAC; electrooculogram signal; eye blink removal; hybrid RABWC-STF method; robust adaptive beamforming; space time frequency model; worst case performance optimization; Adaptation model; Brain modeling; Electrooculography; Facsimile; Robustness; Surgery; electrooculogram (EOG); eye-blink removal; parallel factor analysis; robust adaptive beamforming; space-time-frequency model;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on

Conference_Location

Istanbul

ISSN

1062-922X

Print_ISBN

978-1-4244-6586-6

Type

conf

DOI

10.1109/ICSMC.2010.5642393

Filename

5642393