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Items: 1 to 20 of 132

1.

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

Mognon A, Jovicich J, Bruzzone L, Buiatti M.

Psychophysiology. 2011 Feb;48(2):229-40. doi: 10.1111/j.1469-8986.2010.01061.x.

PMID:
20636297
2.

Automatic classification of artifactual ICA-components for artifact removal in EEG signals.

Winkler I, Haufe S, Tangermann M.

Behav Brain Funct. 2011 Aug 2;7:30. doi: 10.1186/1744-9081-7-30.

3.

Semi-automatic identification of independent components representing EEG artifact.

Viola FC, Thorne J, Edmonds B, Schneider T, Eichele T, Debener S.

Clin Neurophysiol. 2009 May;120(5):868-77. doi: 10.1016/j.clinph.2009.01.015. Epub 2009 Apr 3.

PMID:
19345611
4.

Removing artefacts from TMS-EEG recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties.

Rogasch NC, Thomson RH, Farzan F, Fitzgibbon BM, Bailey NW, Hernandez-Pavon JC, Daskalakis ZJ, Fitzgerald PB.

Neuroimage. 2014 Nov 1;101:425-39. doi: 10.1016/j.neuroimage.2014.07.037. Epub 2014 Jul 25.

PMID:
25067813
5.

A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classification.

LeVan P, Urrestarazu E, Gotman J.

Clin Neurophysiol. 2006 Apr;117(4):912-27. Epub 2006 Feb 2.

PMID:
16458594
6.

Development, validation, and comparison of ICA-based gradient artifact reduction algorithms for simultaneous EEG-spiral in/out and echo-planar fMRI recordings.

Ryali S, Glover GH, Chang C, Menon V.

Neuroimage. 2009 Nov 1;48(2):348-61. doi: 10.1016/j.neuroimage.2009.06.072. Epub 2009 Jul 4.

7.

Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.

Zou Y, Nathan V, Jafari R.

IEEE J Biomed Health Inform. 2016 Jan;20(1):73-81. doi: 10.1109/JBHI.2014.2370646. Epub 2014 Nov 13.

8.

Automatic removal of eye-movement and blink artifacts from EEG signals.

Gao JF, Yang Y, Lin P, Wang P, Zheng CX.

Brain Topogr. 2010 Mar;23(1):105-14. doi: 10.1007/s10548-009-0131-4. Epub 2009 Dec 29.

PMID:
20039116
9.

EEG artifact elimination by extraction of ICA-component features using image processing algorithms.

Radüntz T, Scouten J, Hochmuth O, Meffert B.

J Neurosci Methods. 2015 Mar 30;243:84-93. doi: 10.1016/j.jneumeth.2015.01.030. Epub 2015 Feb 7.

10.

A novel method for device-related electroencephalography artifact suppression to explore cochlear implant-related cortical changes in single-sided deafness.

Kim K, Punte AK, Mertens G, Van de Heyning P, Park KJ, Choi H, Choi JW, Song JJ.

J Neurosci Methods. 2015 Nov 30;255:22-8. doi: 10.1016/j.jneumeth.2015.07.020. Epub 2015 Jul 29.

PMID:
26231621
11.

Kmeans-ICA based automatic method for ocular artifacts removal in a motorimagery classification.

Bou Assi E, Rihana S, Sawan M.

Conf Proc IEEE Eng Med Biol Soc. 2014;2014:6655-8. doi: 10.1109/EMBC.2014.6945154.

PMID:
25571522
12.

Validation of ICA as a tool to remove eye movement artifacts from EEG/ERP.

Mennes M, Wouters H, Vanrumste B, Lagae L, Stiers P.

Psychophysiology. 2010 Nov;47(6):1142-50. doi: 10.1111/j.1469-8986.2010.01015.x.

PMID:
20409015
13.

Removal of BCG artifacts from EEG recordings inside the MR scanner: a comparison of methodological and validation-related aspects.

Vanderperren K, De Vos M, Ramautar JR, Novitskiy N, Mennes M, Assecondi S, Vanrumste B, Stiers P, Van den Bergh BR, Wagemans J, Lagae L, Sunaert S, Van Huffel S.

Neuroimage. 2010 Apr 15;50(3):920-34. doi: 10.1016/j.neuroimage.2010.01.010. Epub 2010 Jan 11.

PMID:
20074647
14.

On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP.

Winkler I, Debener S, Müller KR, Tangermann M.

Conf Proc IEEE Eng Med Biol Soc. 2015;2015:4101-5. doi: 10.1109/EMBC.2015.7319296.

PMID:
26737196
15.

Automatic removal of the eye blink artifact from EEG using an ICA-based template matching approach.

Li Y, Ma Z, Lu W, Li Y.

Physiol Meas. 2006 Apr;27(4):425-36. Epub 2006 Mar 14.

PMID:
16537983
16.

Time-frequency analysis of resting state and evoked EEG data recorded at higher magnetic fields up to 9.4 T.

Abbasi O, Dammers J, Arrubla J, Warbrick T, Butz M, Neuner I, Shah NJ.

J Neurosci Methods. 2015 Nov 30;255:1-11. doi: 10.1016/j.jneumeth.2015.07.011. Epub 2015 Jul 23.

PMID:
26213220
17.

Validation of the cochlear implant artifact correction tool for auditory electrophysiology.

Miller S, Zhang Y.

Neurosci Lett. 2014 Aug 8;577:51-5. doi: 10.1016/j.neulet.2014.06.007. Epub 2014 Jun 16.

PMID:
24946164
18.

Analysis and visualization of single-trial event-related potentials.

Jung TP, Makeig S, Westerfield M, Townsend J, Courchesne E, Sejnowski TJ.

Hum Brain Mapp. 2001 Nov;14(3):166-85.

PMID:
11559961
19.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information.

Zhang C, Tong L, Zeng Y, Jiang J, Bu H, Yan B, Li J.

Biomed Res Int. 2015;2015:720450. doi: 10.1155/2015/720450. Epub 2015 Aug 25.

20.

Hybrid EEG--Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal.

Mannan MM, Kim S, Jeong MY, Kamran MA.

Sensors (Basel). 2016 Feb 19;16(2):241. doi: 10.3390/s16020241.

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