Automatic Eye-Blink Artifact Removal Method Based on EMD-CCA
This research proposes a new hybrid algorithm for automatic removal of eye blink artifact from EEG data based on empirical mode decomposition (EMD) and canonical correlation analysis (CCA).The validity and efficiency of the proposed algorithm is evaluated using correlation coefficient and signal-toartifact ratio (SAR) and the proposed algorithm is also compared with other popular eye blink artifact removal techniques (CCA,ICA,EMD-ICA) on simulated EEG data of two channels.From the simulation results,the average correlation coefficients for the EEG channels are obtained as 0.908 and 0.864 respectively.The SAR of the EEG signal also improved from 2.2 dB to 6.0 dB after correction using our proposed method.Compared to other eye blink artifact removal techniques,our proposed method has two benefits.Firstly,no visual inspection is required to detect the eye blink artifact components.Secondly,computational assessment of corrected EEG waveforms reveals that the proposed algorithm retrieves the EEG data by removing the eye blink artifacts reliably.
Eye Blink artifacts removal Electroencephalography (EEG) Empirical mode decomposition (EMD) Canonical Correlation Analysis(CCA) Signal-to-artifact ratio (SAR) Correlation Coefficient
Mumtaz Hussain Soomro Nasreen Badruddin Mohd Zuki Yusoff Munsif Ali Jatoi
Department of Electrical and Electronic Engineering, Universiti Teknologi Petronas, 31750 Tronoh, Perak, Malaysia
国际会议
2013 ICME International Conference on Complex Medical Engineering(2013 ICME复合医学工程国际会议)
北京
英文
186-190
2013-05-25（万方平台首次上网日期，不代表论文的发表时间）