Suppression of Eye-Blink Associated Artifact Using Single Channel EEG Data by Combining Cross-Correlation With Empirical Mode Decomposition

2016 ◽  
Vol 16 (18) ◽  
pp. 6947-6954 ◽  
Author(s):  
Rajesh Patel ◽  
Madhukar PandurangRao Janawadkar ◽  
Senthilnathan Sengottuvel ◽  
Katholil Gireesan ◽  
Thimmakudy Sambasiva Radhakrishnan
Keyword(s):  
Empirical Mode Decomposition ◽  
Cross Correlation ◽  
Single Channel ◽  
Eye Blink ◽  
Mode Decomposition ◽  
Eeg Data

scholarly journals Eye Blink Artefact Removal of Single Frontal EEG Channel Algorithm using Ensemble Empirical Mode Decomposition and Outlier Detection

2021 ◽  
Vol 17 (6) ◽  
pp. 731-741
Author(s):  
Mohd Nurul Al Hafiz Sha'abani ◽  
Norfaiza Fuad ◽  
Norezmi Jamal
Keyword(s):  
Outlier Detection ◽  
Empirical Mode Decomposition ◽  
Single Channel ◽  
Wiener Filter ◽  
Ensemble Empirical Mode Decomposition ◽  
Detection Technique ◽  
Eeg Signal ◽  
Eye Blink ◽  
Mode Decomposition ◽  
Artefact Removal

Recently, the emergence of various applications to use EEG has evolved the EEG device to become wearable with fewer electrodes. Unfortunately, the process of removing artefact becomes challenging since the conventional method requires an additional artefact reference channel or multichannel recording to be working. By focusing on frontal EEG channel recording, this paper proposed an alternative single-channel eye blink artefact removal method based on the ensemble empirical mode decomposition and outlier detection technique. The method removes the segment of the potential eyeblinks artefact on the residual of a pre-determined level of decomposition. An outlier detection technique is introduced to identify the peak of the eyeblink based on the extreme value of the residual signal. The results showed that the corrected EEG signal achieved high correlation, low RMSE and have small differences in PSD when compared to the reference clean EEG. Comparing with an adaptive Wiener filter technique, the corrected EEG signal by the proposed method had better signal-to-artefact ratio.

Identification and Cancellation of Pseudo Mode Function in EMD based on Energy Conservation

2016 ◽  
Vol 08 (01) ◽  
pp. 1650001 ◽  
Author(s):  
Dishan Huang ◽  
Xianglong Kong ◽  
Yibing Xia
Keyword(s):  
Experimental Data ◽  
Energy Conservation ◽  
Empirical Mode Decomposition ◽  
Cross Correlation ◽  
Sampling Rate ◽  
Processing Technique ◽  
Post Processing ◽  
Mode Function ◽  
Mode Decomposition ◽  
Signal Mode

This paper introduces an effective method to identify and cancel a pseudo mode function in empirical mode decomposition (EMD) under the condition of insufficient sampling rate. The contents of this paper have three aspects: First, basic properties of the pseudo mode are accurately revealed. Second, a post-processing technique for EMD is developed. This new technique, called as mode function cancellation, can identify and kick out the pseudo mode from the decomposition results, and correct the decomposition error in the intrinsic mode function. As a result, it can help us to improve the decomposition’s accuracy. Finally, for a mixing mode, the energy of pseudo mode function is proposed on the cross-correlation at time zero, and it can be used to measure the ratio of signal mode to pseudo mode. Examples and experimental data are illustrated to prove the validity of the presented approach. The research results show that this approach can improve EMD performance while a pseudo mode occurs in the decomposition.

scholarly journals Ensemble Empirical Mode Decomposition Analysis of EEG Data Collected during a Contour Integration Task

PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0119489 ◽  
Author(s):  
Karema Al-Subari ◽  
Saad Al-Baddai ◽  
Ana Maria Tomé ◽  
Gregor Volberg ◽  
Rainer Hammwöhner ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Decomposition Analysis ◽  
Ensemble Empirical Mode Decomposition ◽  
Contour Integration ◽  
Mode Decomposition ◽  
Eeg Data
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