Detection of artifacts in the EEG signal with using wavelet transform

Main Article Content

A.A. Popov
A.M. Kanajkin
K.A. Roshchina
O.R. CHertov
V.A. SHashkov

Abstract

The paper considers the task of cleaning up the EEG signal from artifacts. Method for identifying electrooculogram and signal recovery after its removal using discrete wavelet transform of the electroencephalogram is proposed. The developed method showed nice results on examined examples of real signals at localization and removal of artifacts

Article Details

How to Cite
Popov, A. ., Kanajkin, A. ., Roshchina, K. ., CHertov, O. ., & SHashkov, V. . (2011). Detection of artifacts in the EEG signal with using wavelet transform. Electronics and Communications, 16(4), 126–130. https://doi.org/10.20535/2312-1807.2011.16.4.245547
Section
Biomedical devices and systems

References

Zenkov L.R., “Klinicheskaya elektroencefalografiya s elementami epileptologii [Clinical electroencephalography with elements of epileptology]”, Taganrog: Izdatel'stvo TRTU, pp. 358, 1996

Gratton. G, Coles M.G., Donchin E., “A new method for off-line removal of ocular artifact”, Electroencephalography and Clinical Neurophysiology. vol. 55, no. 4, pp. 468-484, 1983 https://doi.org/10.1016/0013-4694(83)90135-9

Woestengurg J.C., Verbaten M.N., Slangen J.L., “The removal of the eye movement artifact from the EEG by regression analysis in the frequency domain”, Biological Physiology, vol. 16, no. 1-2, p. 127-147, 1982 https://doi.org/10.1016/0301-0511(83)90059-5

Lagerlund T.D., Sharbrough F.W., Busacker N.E., “Spatial filtering of multichannel electroencephalographic recordings through principal component analysis by singular value decomposition”, J Clin Neurophysiol. vol. 14, no. 1, pp. 73-82, 1997 doi: 10.1097/00004691-199701000-00007

Delorme A., Makeig S., Sejnowski T., “Automatic artifact rejection for EEG data using high-order statistics and independent component analysis “, Proceedings of the Third International ICA Conference, pp. 9-12, 2001

Comon P., “Independent Component Analysis, A new concept?”, Signal Processing, vol. 36, no. 3, pp. 287-314. doi: 10.1016/0165-1684(94)90029-9

Al'-Kasasbek R.T., SHamasina M.S., Skopin D.E., “Avtomaticheskoe obnaruzhenie artefaktov v elektroencefalograficheskom signale [Automatic detection of artifacts in the electroencephalographic signal]”, Medicinskaya tekhnika, no. 6, pp. 19-26, 2008

Abdullaev N.T., Dyshin O.A., Samedova H.Z. “Primenenie nejronnyh setej dlya vyyavleniya artefaktov elektroencefalograficheskogo signala, predstavlennogo vejvletpaketnym otobrazheniem [The use of neural networks for detecting artifacts of the electroencephalographic signal represented by wavelet packet mapping]”, Medicinskaya tekhnika, no. 4, pp. 42-46, 2009

Krishnaveni V., Jayaraman S., Aravind S., Hariharasudhan V., Ramadoss K. “Automatic Identification and Removal of Ocular Artifacts from EEG using Wavelet Transform”, Measurement Science Review, vol. 6, sec. 2, no. 4, pp. 45-57, 2006

Dobeshi I. “Desyat' lekcij po vejvletam [Ten lectures on wavelets]”,Izhevsk: NIC Regulyarnaya i haoticheskaya dinamika, p.464, 2001.