Abstract

This study presents an analysis on Visual Evoked Potentials (VEPs) recorded mainly from the occipital area of the brain. Accumulation of segmented windows (time locked averaging), Coiflet wavelet decomposition with dyadic filter bank and Principle Component Analysis (PCA) of three stages were utilized in order to decompose the recorded VEPs signal, to improve the Signal to Noise Ratio (SNR) and to reveal statistical information. The results shown that the wavelet transformation offer a significant SNR improvement at around four times compared to PCA as long as the shape of the original signal is retained. These techniques show significant advantages of decomposing the EEG signals into its details frequency bands.

Keywords:

Electroencephalogram, principle component analysis, signal to noise ratio, visual evoked potentials, wavelet transforms,

References

1. Basar, E., 1980. EEG-brain Dynamics: Relation Between EEG and Brain Evoked Potentials. Biomedical Press, Elsevier-North-Holland.
   
2. Bertrand, O., J. Bohorquez and J. Pernier, 1994. Time-frequency digital filtering based on an invertible wavelet transform: an application to evoked potentials. IEEE T. Bio-Med. Eng., 41: 77-88.
   CrossRef    
3. Chui, C.K., 1993. An Introduction to Wavelets. Vol. 1, Academic Press, Boston.
   
4. Cohen, A., I. Daubechies and J.C. Feauveau, 1992. Biorthogonal bases of compactly supported wavelets. Commun. Pure Appl. Math., 45: 485-560.
   CrossRef    
5. Demiralp, T., A. Ademoglu, M. Schürmann, C. Basar-Eroglu and E. Basar, 1999. Detection of P300 waves in single trials by the Wavelet Transform (WT). Brain Lang., 66: 108-128.
   CrossRef    PMid:10080867    
6. Dong, K. and Z. Luo, 2012. A method of denoising multi-channel EEG signals fast based on PCA and DEBSS algorithm. Proceeding of the International Conference on Computer Science and Electronics Engineering (ICCSEE, 2012), pp: 322-326.
   
7. Donoho, D.L., 1995. De-noising by soft-thresholding. IEEE T. Inform. Theory, 41: 613-627.
   CrossRef    
8. Galloway, N., 1990. Human brain electrophysiology: Evoked potentials and evoked magnetic fields in science and medicine. Brit. J. Ophthalmol., 74: 255.
   CrossRef    PMCid:PMC1042082    
9. Ghosh-Dastidar, S., H. Adeli and N. Dadmehr, 2008. Principal component analysis-enhanced cosine radial basis function neural network for robust epilepsy and seizure detection. IEEE T. Bio-Med. Eng., 55: 512-518.
   
10. Grossmann, A. and J. Morlet, 1984. Decomposition of hardy functions into square integrable wavelets of constant shape. SIAM J. Math. Anal., 15: 723-736.
    CrossRef    
11. Gurley, K., T. Kijewski and A. Kareem, 2003. First-and higher-order correlation detection using wavelet transforms. J. Eng. Mech., 129: 188-201.
    CrossRef    
12. Hassoney, A.F., A.K. Ismail and H. Hamza, 2012. Orthogonal and biorthogonal wavelet analysis of visual evoked potentials. Int. J. Comput. Appl., 60: 50-52.
    
13. Mizota, A., N. Asaumi, M. Takasoh and E. Adachi-Usami, 2007. Pattern visual evoked potentials in Japanese patients with multiple sclerosis without history of visual pathway involvement. Doc. Ophthalmol., 115: 105-109.
    CrossRef    PMid:17549532    
14. Mohd Tumari, S., R. Sudirman, A. Ahmad and A. Al-Haddad, 2012. Study of normal children electroencephalography signals using wavelet transformation. Procceding of the IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES, 2012), pp: 896-900.
    CrossRef    
15. Odom, J.V., M. Bach, M. Brigell, G.E. Holder, D.L. McCulloch and A.P. Tormene, 2010. ISCEV standard for clinical visual evoked potentials (2009 update). Doc. Ophthalmol., 120: 111-119.
    CrossRef    PMid:19826847    
16. Palaniappan, R., S. Anandan and P. Raveendran, 2002. Two level PCA to reduce noise and EEG from evoked potential signals. Proceeding of the 7th International Conference on Control, Automation, Robotics and Vision (ICARCV’ 2002), 3: 1688-1693.
    CrossRef    
17. Quian Quiroga, R., 2000. Obtaining single stimulus evoked potentials with wavelet denoising. Physica D, 145: 278-292.
    CrossRef    
18. Quian Quiroga, R., O.W. Sakowitz, E. Basar and M. Schürmann, 2001. Wavelet transform in the analysis of the frequency composition of evoked potentials. Brain Res. Protoc., 8: 16-24.
    CrossRef    
19. Quiroga, R.Q., E. Basar, M. Schürmann and M.S. Urmann, 2000. Phase-locking of event-related alpha oscillations. Proceeding of the Workshop on Chaos in Brain, pp: 301-304.
    CrossRef    
20. Schiff, S.J., A. Aldroubi, M. Unser and S. Sato, 1994. Fast wavelet transformation of EEG. Electroen. Clin. Neuro., 91: 442-455.
    CrossRef    
21. Sharmilakanna, P. and R. Palaniappan, 2005. EEG artifact reduction in VEP using 2-stage PCA and N4 analysis of alcoholics. Proceeding of the 3rd International Conference on Intelligent Sensing and Information Processing (ICISIP’ 2005), pp: 1-7.
    
22. Turker, H., M. Terzi, O. Bayrak, N. Cengiz, M. Onar and O. Us, 2008. Visual evoked potentials in differential diagnosis of multiple sclerosis and neurobehcet's disease. Tohoku J. Exp. Med., 216: 109-116.
    CrossRef    PMid:18832792    
23. Unser, M., A. Aldroubi and M. Eden, 1992. On the asymptotic convergence of B-spline wavelets to Gabor functions. IEEE T. Inform. Theory, 38(2): 864-872.
    CrossRef    
24. Zhang, X. and D.C. Hood, 2004. A principal component analysis of multifocal pattern reversal VEP. J. Vision, 4(1): 32-43.
    CrossRef    PMid:14995897    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.