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EOG Artifacts Removal in EEG Measurements for Affective Interaction with Brain Computer Interface

Wen Qi
2012 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing  
Therefore, artifacts removal in the preprocess step is crucial. Electrooculography (EOG) signals are one of the major artifacts that often appear in EEG measurement.  ...  In this paper, we compared two different algorithms (Recursive Least Square (RLS) and Blind Source Separation (BSS)) to investigate their performances on removing EOG artifacts from EEG signals.  ...  RELATED WORK IN EOG ARTIFACTS REMOVAL Various algorithms exist in order to remove EOG artifacts embedded in the EEG measurements.  ... 
doi:10.1109/iih-msp.2012.120 dblp:conf/iih-msp/Qi12 fatcat:7nnm6l2khrb27ifsdbnqeswtli

Integration of EEG source imaging and fMRI during continuous viewing of natural movies

Kevin Whittingstall, Andreas Bartels, Vanessa Singh, Soyoung Kwon, Nikos K. Logothetis
2010 Magnetic Resonance Imaging  
To analyze EEG data in this natural setting, we developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc., in a way unbiased by human  ...  We made sequential fMRI and 64-channel EEG recordings in seven subjects who passively watched 2-min-long segments of a James Bond movie.  ...  EEG Artifact correction Given the specific design of our experiment characterized by the 2-min-long movie stimulus, EEG artifacts (especially eye blinks) posed a serious problem for data interpretation  ... 
doi:10.1016/j.mri.2010.03.042 pmid:20579829 fatcat:qpw7dtwf4rhz7f4r3vgsebijqi

Corneo-retinal-dipole and eyelid-related eye artifacts can be corrected offline and online in electroencephalographic and magnetoencephalographic signals

Reinmar J. Kobler, Andreea I. Sburlea, Catarina Lopes-Dias, Andreas Schwarz, Masayuki Hirata, Gernot R. Müller-Putz
2020 NeuroImage  
Eye movements and blinks contaminate electroencephalographic (EEG) and magnetoencephalographic (MEG) activity.  ...  Residual correlations between the corrected M/EEG channels and the eye artifacts were below 0.1. Error-related and movement-related cortical potentials were attenuated by less than 0.5 μV.  ...  In all experiments, we used sintered Ag/AgCl EEG electrodes and salty gels. They provide good long term recording stability (Tallgren et al., 2005) .  ... 
doi:10.1016/j.neuroimage.2020.117000 pmid:32497788 fatcat:zqamvhdb5ba4vbqvnlz3aeaucm

Improved Cognitive Vigilance Assessment after Artifact Reduction with Wavelet Independent Component Analysis

Nadia Abu Farha, Fares Al-Shargie, Usman Tariq, Hasan Al-Nashash
2022 Sensors  
Independent Component Analysis (ICA) is an effective method and has been extensively used in the suppression of EEG artifacts.  ...  Our classification results showed that in terms of features extraction, the wICA method outperformed the existing ICA method.  ...  In addition, this paper represents the opinions of the authors and does not represent the position or opinion of the American University of Sharjah.  ... 
doi:10.3390/s22083051 pmid:35459033 pmcid:PMC9033092 fatcat:y2ukwlnonzcwrj3rhjexf47eoi

Distributed Signal Processing for Wireless EEG Sensor Networks

Alexander Bertrand
2015 IEEE transactions on neural systems and rehabilitation engineering  
blink artifact removal algorithm.  ...  Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks  ...  Case study: distributed eye blink artifact removal Eye movement or eye blink artifacts are the most common and most pronounced artifacts that appear in EEG recordings (see Fig. 5 ).  ... 
doi:10.1109/tnsre.2015.2418351 pmid:25850092 fatcat:i4hrtd4sjfg75fp3izvmxra3i4

Computational intelligent brain computer interaction and its applications on driving cognition

Chin-Ten Lin, Li-Wei Ko, Tzu-Kuei Shen
2009 IEEE Computational Intelligence Magazine  
cognitive-state monitoring of the driver performing the realistic long-term driving tasks in a simulated realistic-driving environment; and (2) to extract the brain dynamic changes of driver's distraction  ...  In recent years, many computational intelligent technologies were developed for preventing traffic accidents caused by driver's inattention.  ...  This work was in part supported by the Aiming for the Top University Plan of National Chiao Tung University, the Ministry of Education,  ... 
doi:10.1109/mci.2009.934559 fatcat:ilrufdbvbzawdl3qo5cw3oyrru

A Multimodal Approach to Estimating Vigilance Using EEG and Forehead EOG [article]

Wei-Long Zheng, Bao-Liang Lu
2016 arXiv   pre-print
In this paper, we focus on the problem of estimating the vigilance of users using EEG and EOG signals. Approach.  ...  We propose a multimodal approach to estimating vigilance by combining EEG and forehead EOG and incorporating the temporal dependency of vigilance into model training.  ...  Similar to artifact removal using blind signal separation in conventional approaches, the forehead EEG signals are reconstructed with a weight matrix by discarding the EOG components.  ... 
arXiv:1611.08492v1 fatcat:nc24ushc4zfyjk34naih3csl4e

A multimodal approach to estimating vigilance using EEG and forehead EOG

Wei-Long Zheng, Bao-Liang Lu
2017 Journal of Neural Engineering  
In this paper, we focus on the problem of estimating the vigilance of users using EEG and EOG signals. Approach. The PERCLOS index as vigilance annotation is obtained from eye tracking glasses.  ...  We propose a multimodal approach to estimating vigilance by combining EEG and forehead EOG and incorporating the temporal dependency of vigilance into model training.  ...  Acknowledgments This work was supported in part by grants from the National Natural Science  ... 
doi:10.1088/1741-2552/aa5a98 pmid:28102833 fatcat:cllzkrgh25c3zk3moya6cttcru

Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach—Part II: Brain Signals

Radek Martinek, Martina Ladrova, Michaela Sidikova, Rene Jaros, Khosrow Behbehani, Radana Kahankova, Aleksandra Kawala-Sterniuk
2021 Sensors  
As it was mentioned in the previous part of this work (Part I)—the advanced signal processing methods are one of the quickest and the most dynamically developing scientific areas of biomedical engineering  ...  In this paper, which is a Part II work—various innovative methods for the analysis of brain bioelectrical signals were presented and compared.  ...  The application of ICA provided very good results in removing eye-blinking artifacts [101, 156] . Table 1 summarizes the recently used EEG signal processing methods.  ... 
doi:10.3390/s21196343 pmid:34640663 fatcat:mfe4taom5rhfpcp7m744msmgry

Driving fatigue detection with fusion of EEG and forehead EOG

Xue-Qin Huo, Wei-Long Zheng, Bao-Liang Lu
2016 2016 International Joint Conference on Neural Networks (IJCNN)  
PERCLOS (the percentage of eye closure) is calculated by using the eye movement data recorded by eye tracking glasses as the indicator of drivers' fatigue level.  ...  In this paper, we fuse EEG and forehead EOG to detect drivers' fatigue level by using discriminative graph regularized extreme learning machine (GELM).  ...  signals are applied to reduce the noise and remove the artifacts.  ... 
doi:10.1109/ijcnn.2016.7727294 dblp:conf/ijcnn/HuoZL16 fatcat:guenj3qifvcv7hzx2u4qe4ywzm

Eye blink characterization from frontal EEG electrodes using source separation and pattern recognition algorithms

Raphaëlle N. Roy, Sylvie Charbonnier, Stéphane Bonnet
2014 Biomedical Signal Processing and Control  
EEG signals, which are generally corrupted by ocular artifacts, are decomposed into sources by means of a source separation algorithm.  ...  The correlation between the blink parameters extracted from both recording modalities was 0.81 in average.  ...  [24] estimate glance from EEG to allow cursor control by avoiding high-pass frequency filtering which is usually performed on the EOG signal to remove the long-term drift.  ... 
doi:10.1016/j.bspc.2014.08.007 fatcat:rar7klbcmzc4hhdz7yrv7rbv7e

Removal of Movement Artifact From High-Density EEG Recorded During Walking and Running

Joseph T. Gwin, Klaus Gramann, Scott Makeig, Daniel P. Ferris
2010 Journal of Neurophysiology  
Removal of movement artifact from high-density EEG recorded during walking and running. .  ...  In the running condition, gait-related artifact severely compromised the EEG signals: stable average ERP time-courses of IC processes were only detectable after artifact removal.  ...  of ICA-based artifact removal techniques.  ... 
doi:10.1152/jn.00105.2010 pmid:20410364 pmcid:PMC3774587 fatcat:zxw4o4tl2fgxzas4zv6fgp3t7q

Applications of Second Order Blind Identification to High-Density EEG-Based Brain Imaging: A Review [chapter]

Akaysha Tang
2010 Lecture Notes in Computer Science  
in the data domain of human high-density EEG.  ...  widely available EEG recording technique.  ...  , it has become an accepted practice to manually review the entire EEG record channel by channel to identify specific time windows where eye blinks and eye movement have occurred.  ... 
doi:10.1007/978-3-642-13318-3_46 fatcat:pquf5yvc4zacjj2wf45ndysze4

Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

Keum-Shik Hong, Muhammad Jawad Khan
2017 Frontiers in Neurorobotics  
FigURe 5 | Electroencephalography (EEG)-NIRS-based brain-computer interface: the figure shows a method of removal of false-positive motor imagery signals in EEG data using functional near infrared spectroscopy  ...  Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control.  ...  Figure 3 shows the method used to acquire simultaneous EEG and EOG data for analysis. Artifact Removal Eye blink signals influence brain signals by inducing artifacts in the data.  ... 
doi:10.3389/fnbot.2017.00035 pmid:28790910 pmcid:PMC5522881 fatcat:wcg2mc32mvei3mtvsyropxbzim

Deep Learning Approach for Automatic Classification of Ocular and Cardiac Artifacts in MEG Data

Ahmad Hasasneh, Nikolas Kampel, Praveen Sripad, N. Jon Shah, Jürgen Dammers
2018 Journal of Engineering  
The overall accuracy of the model was validated using a cross-validation test and revealed a median accuracy of 94.4%, indicating high reliability of the DCNN-based artifact removal in task and nontask  ...  for auxiliary signal recordings; (3) the flexibility in the model design and training allows for various modalities (MEG/EEG) and various sensor types.  ...  Acknowledgments The authors are grateful to Al-Taawon Institution in Palestine for partially supporting this research project.  ... 
doi:10.1155/2018/1350692 fatcat:tj4ubmzqxrbvdkaa5mtgoj4jue
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