Title :
Subspace based spectral subtraction approach for Visual Evoked Potential extraction
Author :
Yanti, Duma Kristina ; Yusoff, Mohd Zuki
Author_Institution :
Electr. & Electron. Eng., Univ. Teknol. Petronas, Tronoh, Malaysia
Abstract :
This paper presents the extraction of Visual Evoked Potential (VEP) signal from a noisy observation Electroencephalogram (EEG) signal. Subspace method has been used to extract VEP, mostly in the time domain. The author proposes to use subspace based method in the frequency domain for VEP signal estimation. In making use of the subspace method, spectral subtraction approach is utilized. Noise estimate is performed by subspace method in the time domain and subtracts the estimated noise in the frequency domain. Magnitude spectral subtraction is chosen to subtract the noise from the noisy signal. The results show that although the method needs to be developed further, this method can be used in the estimation of VEP signal.
Keywords :
electroencephalography; medical signal processing; visual evoked potentials; EEG; VEP signal; electroencephalogram signal; magnitude spectral subtraction; noise estimate; noisy observation; subspace based spectral subtraction approach; subspace method; time domain; visual evoked potential extraction; Eigenvalues and eigenfunctions; Electric potential; Estimation; Noise; Noise measurement; Time domain analysis; Visualization; Susbpace; Visual Evoked Potential; eigenvalue decomposition; noisy environment; spectral subtraction;
Conference_Titel :
Intelligent and Advanced Systems (ICIAS), 2012 4th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-1968-4
DOI :
10.1109/ICIAS.2012.6306102