Single-trial extraction of visual evoked potentials from the brain

Author

Yusoff, Mohd Zuki ; Kamel, Nidal ; Ahmad Fadzil, Mohd Hani

Author_Institution

Electr. & Electron. Eng. Dept., Univ. Teknol. PETRONAS, Tronoh, Malaysia

fYear

2008

fDate

25-29 Aug. 2008

Firstpage

1

Lastpage

5

Abstract

Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-noise ratio (SNR) is generally very low. An eigendecomposition-based subspace approach originally proposed for enhancing speech corrupted by colored noise, has been investigated and tested in the single trial extraction of VEPs. This scheme arbitrarily labeled as an eigen-decomposition (ED) method has been compared with a third-order correlation (TOC) method, using both realistic simulation and real human data. The results produced by the ED algorithm show much cleaner waveforms, and higher degree of consistency in detecting the P100, P200, and P300 peaks.

Keywords

brain; eigenvalues and eigenfunctions; medical signal detection; visual evoked potentials; ED algorithm; P100 peak detection; P200 peak detection; P300 peak detection; colored noise; eigendecomposition-based subspace approach; human brain; signal-to-noise ratio; single-trial extraction; speech enhancement; third-order correlation method; visual evoked potentials; Covariance matrices; Distortion; Eigenvalues and eigenfunctions; Electroencephalography; Signal to noise ratio; Vectors; Eigenvalue decomposition; subspace methods; visual evoked potential latencies;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2008 16th European

Conference_Location

Lausanne

ISSN

2219-5491

Type

conf

Filename

7080496