A New Hybrid Method for EOG Artifact Rejection from EEG Signal Using CCA and RLS

Tavakoli Najafabadi, Maryam; Abootalebi, Vahid; Shayegh, Farzaneh

doi:10.22041/ijbme.2017.45141.1135

Document Type : Full Research Paper

Authors

¹ MSC graduated, Electrical Engineering Department, Yazd University, Yazd, Iran

² Associate Professor, Electrical Engineering Department, Yazd University, Yazd, Iran

³ Assistant Professor, Engineering Department, Payamnoor University, Esfahan, Iran

https://doi.org/10.22041/ijbme.2017.45141.1135

Abstract

The purpose of this article is to evaluate the efficiency of Canonical Correlation Analysis- Recursive Least Square (CCA-RLS)hybridmethod in ElectroOcluGram (EOG) artifact removal from ElectroEncephaloGram (EEG) signal and compare it with Independent Component Analysis (ICA), Canonical Correlation Analysis (CCA), Recursive Least Square (RLS)methods and ICA-RLS hybrid method. After decomposition of the noisy signal by CCA, the noisy components aredetected based ontheir kurtosis, and are filtered by RLS. As the result,the enhanced signal is reconstructed by mixing the original noise-free components and filtered components. In order to compare the methods quantitatively, two evaluation criteria, namely Mean Square Error (MSE) and Signal to Noise Ratio (SNR) are used.The MSE and SNR average values were calculated for five subject in four different channels. EEG data are taken from BCI2008. According to the results,the combination of CCA-RLS method has better performance compareto the other methods used in this paper.

Keywords

Main Subjects

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing

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Iranian Journal of Biomedical Engineering

A New Hybrid Method for EOG Artifact Rejection from EEG Signal Using CCA and RLS

References

References

Volume 10, Issue 1
May 2016
Pages 1-10

A New Hybrid Method for EOG Artifact Rejection from EEG Signal Using CCA and RLS

References

References

Volume 10, Issue 1May 2016Pages 1-10

Volume 10, Issue 1
May 2016
Pages 1-10