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Study of Various Automatic EEG Artifact Removal Techniques

Anshul Khatter
2017 International Journal for Research in Applied Science and Engineering Technology  
Finding the artifacts and eliminating them from real EEG signal by the use of competent algorithm assists researchers and doctors.  ...  There is maximum probability of artifact with EEG signal because of physical and experimental problems therefore artifact elimination is a central issue during encephalogram recordings.  ...  The removal of artifact from EEGs is of significant for each the automatic and visual study of EEG signals.  ... 
doi:10.22214/ijraset.2017.10149 fatcat:5j2p3jfmobf4tpckcxm5oodzem

Real-time EEG artifact correction during fMRI using ICA

Ahmad Mayeli, Vadim Zotev, Hazem Refai, Jerzy Bodurka
2016 Journal of Neuroscience Methods  
BCG and imaging artifacts appear in the EEG signal as a result of the sighttp://dx.  ...  results for further applications of real-time multimodal EEG-fMRI. a b s t r a c t Background: Simultaneous acquisition of EEG and fMRI data results in EEG signal contamination by imaging (MR) and ballistocardiogram  ...  Department of Defense grant W81XWH-12-1-0607.  ... 
doi:10.1016/j.jneumeth.2016.09.012 pmid:27697458 fatcat:g52v6mxi7vavhasnytryi3jkqe

Computerized processing of EEG–EOG–EMG artifacts for multi-centric studies in EEG oscillations and event-related potentials

D Moretti
2003 International Journal of Psychophysiology  
for a cognitive-motor paradigm, the detection of involuntary mirror movements, and the detection of EEG artifacts.  ...  In particular, our software package includes (semi)automatic procedures for (i) EOG artifact detection and correction, (ii) EMG analysis, (iii) EEG artifact analysis, (iv) optimization of the ratio between  ...  Fabrizio Eusebi, Chairman of the Biophysics Group of Interest of the Department of Human Physiology and Pharmacology-University of Rome 'La Sapienza'-for his continuous support.  ... 
doi:10.1016/s0167-8760(02)00153-8 pmid:12663065 fatcat:d7qi3pe5dfgl3gro5opbkn6wbq

Real-time MR artifacts filtering during continuous EEG/fMRI acquisition

G. Garreffa, M. Carnı̀, G. Gualniera, G.B. Ricci, L. Bozzao, D. De Carli, P. Morasso, P. Pantano, C. Colonnese, V. Roma, B Maraviglia
2003 Magnetic Resonance Imaging  
In this work, we present a new method to perform simultaneous EEG/fMRI study with real-time artifacts filtering characterized by a procedure based on a preliminary analytical study of EPI sequence parameters-related  ...  The purpose of this study was the development of a real-time filtering procedure of MRI artifacts in order to monitor the EEG activity during continuous EEG/fMRI acquisition.  ...  Acknowledgments The authors acknowledge the support of Walter Nucciarelli at the Department of Neurologic Sciences, University of Rome, La Sapienza, Italy.  ... 
doi:10.1016/j.mri.2003.08.019 pmid:14725925 fatcat:e7l7cbadzvawjdpy5y4ajnyrae

Generalized EEG-FMRI spectral and spatiospectral heuristic models

Rene Labounek, David Janecek, Radek Marecek, Martin Lamos, Tomas Slavicek, Michal Mikl, Jaromir Bastinec, Petr Bednarik, David Bridwell, Milan Brazdil, Jiri Jan
2016 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)  
The aim of the current study is visualization of task-related variability in EEG-fMRI data, performed as a blind-search analysis without stimulus timings, using a methodology that is based on Kilner's  ...  We also introduce preliminary results implementing the heuristic analysis with spatiospectral EEG components, where the filter response has two dimensions and depends on frequency and channels.  ...  From this point of view, EEG-fMRI fusion based on EEG spectra has a great potential for automatic detection of epileptogenous focus.  ... 
doi:10.1109/isbi.2016.7493379 dblp:conf/isbi/LabounekJMLSMBB16 fatcat:znbgkdi2cnay3k6iemmdexszta

Eye Blink Artifact Detection with Novel Optimized Multi-dimensional Electroencephalogram Features

Jianhui Wang, Jiuwen Cao, Dinghan Hu, Tiejia Jiang, Feng Gao
2021 IEEE transactions on neural systems and rehabilitation engineering  
In this paper, we develop a novel eye blink artifact detection algorithm based on optimally selected multi-dimensional EEG features.  ...  Accurate eye blink artifact detection is essential for electroencephalogram (EEG) analysis and auxiliary analysis of nervous system diseases, especially in the presence of the frontal epileptiform discharges  ...  Fig. 3 . 3 Slope sequences and filtered signals by SNEO on the monotonic increasing EEGs of the CHZU database. 11: end if 12: end for Fig. 4 . 4 Comparisons of (a) MSMIs and (b) MSSNs obtained from  ... 
doi:10.1109/tnsre.2021.3099232 fatcat:7ax4au6anfgkje47dqjaj5tibu

Towards Semi-Automatic Artifact Rejection for the Improvement of Alzheimer's Disease Screening from EEG Signals

Jordi Solé-Casals, François-Benoît Vialatte
2015 Sensors  
We investigate the possibility to automatically clean a database of EEG recordings taken from patients suffering from Alzheimer's disease and healthy age-matched controls.  ...  A large number of studies have analyzed measurable changes that Alzheimer's disease causes on electroencephalography (EEG).  ...  F-BV had theoretical contributions on the analysis, reviewed the draft of the paper, prepared the illustrations and the equations, and adapted the manuscript to the journal template.  ... 
doi:10.3390/s150817963 pmid:26213933 pmcid:PMC4570302 fatcat:nvi3hrxpjrdnnmnp6aghzl2cky

EMG and EOG artifacts in brain computer interface systems: A survey

Mehrdad Fatourechi, Ali Bashashati, Rabab K. Ward, Gary E. Birch
2007 Clinical Neurophysiology  
This study reveals weaknesses in BCI studies related to reporting the methods of handling EMG and EOG artifacts.  ...  As the lack of dealing with artifacts may result in the deterioration of the performance of a particular BCI system during practical applications, it is necessary to develop automatic methods to handle  ...  Jaimie Borissoff, Craig Wilson and Gordon Handford for their valuable comments on this paper.  ... 
doi:10.1016/j.clinph.2006.10.019 pmid:17169606 fatcat:plkcp6pbvfegxdqvmguehxcqqa

A multistage, multimethod approach for automatic detection and classification of epileptiform EEG

He Sheng Liu, Tong Zhang, Fu Sheng Yang
2002 IEEE Transactions on Biomedical Engineering  
The present study proposes a robust system that combines multiple signal-processing methods in a multistage scheme, integrating adaptive filtering, wavelet transform, artificial neural network, and expert  ...  A nonlinear filter for separation of nonstationary and stationary EEG components is also developed in this paper.  ...  Fig. 1 . 1 Block diagram of the automatic detecting system. Fig. 2 . 2 Filter separates the stationary and nonstationary components of EEG signal.  ... 
doi:10.1109/tbme.2002.805477 pmid:12549737 fatcat:pu2g4znrvfb33h2vea7cpfkine

Detection of eye blink artifacts from single prefrontal channel electroencephalogram

Won-Du Chang, Ho-Seung Cha, Kiwoong Kim, Chang-Hwan Im
2016 Computer Methods and Programs in Biomedicine  
In this paper, a novel method to detect eye blink artifacts from a single-channel frontal EEG signal was proposed by combining digital filters with a rule-based decision system, and its performance was  ...  Electrooculogram (EOG) Artifact detection Eye blink a b s t r a c t Eye blinks are one of the most influential artifact sources in electroencephalogram (EEG) recorded from frontal channels, and thereby  ...  EEG signals of 24 participants recorded at the Fp2 channel are plotted sequentially (the first signal is from participant 1, and the bottom one is from participant 24), and the detected artifact ranges  ... 
doi:10.1016/j.cmpb.2015.10.011 pmid:26560852 fatcat:twz3lvdo2zgufjvyktfumhlcmy

EEG-Based Neonatal Sleep Stage Classification Using Ensemble Learning

Saadullah Farooq Abbasi, Harun Jamil, Wei Chen
2022 Computers Materials & Continua  
For this reason, an internet of things and ensemblebased automatic sleep stage classification has been proposed in this study. 12 EEG features, from 9 bipolar channels, were used to train and test the  ...  The proposed algorithm can reach a mean kappa of 0.73 and 0.66 for 2-stage and 3-stage (wake, active sleep, and quiet sleep) classification, respectively.  ...  Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/cmc.2022.020318 fatcat:ctspdnxoebbqljrbunodxror6i

An evaluation of automated neonatal seizure detection methods

Stephen Faul, Geraldine Boylan, Sean Connolly, Liam Marnane, Gordon Lightbody
2005 Clinical Neurophysiology  
Methods: One-minute, artifact-free EEG segments consisting of either EEG seizure activity or non-seizure EEG activity were extracted from EEG recordings of 13 neonates.  ...  The overlap of frequency characteristics of seizure and non-seizure EEG, artifacts and natural variances in the neonatal EEG cause a great problem to the seizure detection algorithms.  ...  This filter is used to filter out any non-seizure EEG from the EEG signal.  ... 
doi:10.1016/j.clinph.2005.03.006 pmid:15897008 fatcat:72etdpsrajadtg2hkdlurolp3a

SRI-EEG: State-Based Recurrent Imputation for EEG Artifact Correction

Yimeng Liu, Tobias Höllerer, Misha Sra
2022 Frontiers in Computational Neuroscience  
Our goal is to detect physiological artifacts in EEG signal and automatically replace the detected artifacts with imputed values to enable robust EEG sensing overall requiring significantly reduced manual  ...  From quantitative and qualitative comparisons with six conventional and neural network based approaches, we demonstrate that our method achieves comparable performance to the state-of-the-art methods on  ...  ACKNOWLEDGMENTS We would like to thank Barry Giesbrecht and Tom Bullock for providing and contextualizing the bike dataset and also Yi Ding for valuable discussions.  ... 
doi:10.3389/fncom.2022.803384 pmid:35669387 pmcid:PMC9163298 fatcat:cd2ttsm7tzaxnkdqitq6g7upcm

Automatic detection of fast ripples

Gwénaël Birot, Amar Kachenoura, Laurent Albera, Christian Bénar, Fabrice Wendling
2013 Journal of Neuroscience Methods  
Highlights 1 1) We propose a novel method for automatically detecting fast ripples (FRs, 250-600 Hz) 2 2) The signal energy in low and high frequency bands is used to classify EEG events as FRs, interictal  ...  a new method for automatic detection of fast ripples (FRs) which have been 11 identified as a potential biomarker of epileptogenic processes. 12 Methods: This method is based on a two-stage procedure:  ...  In this paper, we propose a novel detection method for automatically 9 identifying FRs occurring in depth-EEG signals.  ... 
doi:10.1016/j.jneumeth.2012.12.013 pmid:23261773 fatcat:ky3h5ocgyrhl7jtc3zsv3qfqoi

Advanced Methods to Analyse the Complexity of the Brain

Nadia Mammone, Gaoxiang Ouyang, Hamed Azami
2018 Complexity  
"Effect of EOG Signal Filtering on the Removal of Ocular Artifacts and EEG-Based Brain-Computer Interface: A Comprehensive Study" is a paper that addresses the issue of ocular artifacts contaminating EEG  ...  In "Automated Epileptic Seizure Detection in Scalp EEG Based on Spatial-temporal Complexity," a novel method is introduced to define a patient-specific detector based on spatial-temporal complexity analysis  ...  Conflicts of Interest The authors declare that they have no conflicts of interest. Nadia Mammone Gaoxiang Ouyang Hamed Azami  ... 
doi:10.1155/2018/8971891 fatcat:wwibq4jjlzgv5kkokxa6ipzcqm
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