Estimation of Visual Evoked Potentials using a Signal Subspace Approach

Yusoff, Mohd Zuki and Kamel , Nidal and Ahmad Fadzil, Mohd Hani (2007) Estimation of Visual Evoked Potentials using a Signal Subspace Approach. In: International Conference on Intelligent and Advanced Systems 2007 (ICIAS 2007), November 25-28, 2007, Kuala Lumpur Convention Centre, Kuala Lumpur, Malaysia.

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Extraction of visual evoked potentials (VEPs) from the human brain is generally very difficult due to its poor signal-to-noise ratio (SNR) property. A signal subspace technique is presented to estimate VEPs hidden inside highly colored electroencephalogram EEG) noise. This method is borrowed and modified from signal subspace techniques originally used for enhancing speech corrupted by colored noise. The signal subspace is estimated by applying eigenvalue decomposition on the approximated signal covariance matrix. The signal subspace based algorithm is able to satisfactorily extract the P100, P200 and P300 peak latencies from artificially generated noisy VEPs. The simulation results show that the estimator maintains an average success rate of 87 % with an average percentage error of less than 9 %, when subjected to SNR from 0 dB to -10 dB.

Item Type:Conference or Workshop Item (Speech)
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
ID Code:3890
Deposited By: Dr Mohd Zuki Yusoff
Deposited On:10 Jan 2011 10:11
Last Modified:10 Jan 2011 10:11

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