Title :
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
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;
Conference_Titel :
Signal Processing Conference, 2008 16th European
Conference_Location :
Lausanne
