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Article: Single-trial detection of somatosensory evoked potentials by probabilistic independent component analysis and wavelet filtering

TitleSingle-trial detection of somatosensory evoked potentials by probabilistic independent component analysis and wavelet filtering
Authors
KeywordsEvent-related potentials (ERPs)
Probabilistic independent component analysis (PICA)
Single-trial analysis
Somatosensory evoked potentials (SEPs)
Wavelet filtering
Issue Date2011
PublisherElsevier Ireland Ltd. The Journal's web site is located at http://www.elsevier.com/locate/clinph
Citation
Clinical Neurophysiology, 2011, v. 122 n. 7, p. 1429-1439 How to Cite?
AbstractObjective: To develop an effective approach for enhancing the signal-to-noise ratio (SNR) and identifying single-trial short-latency somatosensory evoked potentials (SEPs) from multi-channel electroencephalography (EEG). Methods: 128-channel SEPs elicited by electrical stimuli of the left posterior tibial nerve were recorded from 11 healthy subjects. Probabilistic independent component analysis (PICA) was used as a spatial filter to isolate SEP-related independent components (ICs), and wavelet filtering was used as a time-frequency filter to further enhance the SNR of single-trial SEPs. Results: SEP-related ICs, identified using PICA, showed typical patterns of cortical SEP complex (P39-N50-P60) and scalp topography (centrally distributed with the spatial peak located near vertex). In addition, wavelet filtering significantly enhanced the SNR of single-trial SEPs (p= 0.001). Conclusions: Combining PICA and wavelet filtering offers a space-time-frequency filter that can be used to enhance the SNR of single-trial SEPs greatly, thus providing a reliable estimation of single-trial SEPs. Significance: This method can be used to detect single-trial SEPs and other types of evoked potentials (EPs) in various sensory modalities, thus facilitating the exploration of single-trial dynamics between EPs, behavioural variables (e.g., intensity of perception), as well as abnormalities in intraoperative neurophysiological monitoring. © 2011 International Federation of Clinical Neurophysiology.
DescriptionComment in Clin Neurophysiol. 2011 Jul;122(7):1280-1281
Persistent Identifierhttp://hdl.handle.net/10722/135313
ISSN
2015 Impact Factor: 3.426
2015 SCImago Journal Rankings: 1.581
ISI Accession Number ID
Funding AgencyGrant Number
Lee Wing Tat Medical Research Fund
HKU CRCG
Research Grants Council of the Hong Kong SAR, ChinaGRF HKU 7130/06E
GRF 712408E
Hong Kong ITF Tier 3ITS/149/08
Funding Information:

L.H. is supported by the Lee Wing Tat Medical Research Fund. Z.G.Z. is partially supported by the HKU CRCG Small Project Funding. Y.H. is partially supported by research grants from the Research Grants Council of the Hong Kong SAR, China (GRF HKU 7130/06E, and GRF 712408E) and from Hong Kong ITF Tier 3(ITS/149/08). All authors have no conflict of interest.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorHu, Len_HK
dc.contributor.authorZhang, ZGen_HK
dc.contributor.authorHung, YSen_HK
dc.contributor.authorLuk, KDKen_HK
dc.contributor.authorIannetti, GDen_HK
dc.contributor.authorHu, Yen_HK
dc.date.accessioned2011-07-27T01:33:14Z-
dc.date.available2011-07-27T01:33:14Z-
dc.date.issued2011en_HK
dc.identifier.citationClinical Neurophysiology, 2011, v. 122 n. 7, p. 1429-1439en_HK
dc.identifier.issn1388-2457en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135313-
dc.descriptionComment in Clin Neurophysiol. 2011 Jul;122(7):1280-1281-
dc.description.abstractObjective: To develop an effective approach for enhancing the signal-to-noise ratio (SNR) and identifying single-trial short-latency somatosensory evoked potentials (SEPs) from multi-channel electroencephalography (EEG). Methods: 128-channel SEPs elicited by electrical stimuli of the left posterior tibial nerve were recorded from 11 healthy subjects. Probabilistic independent component analysis (PICA) was used as a spatial filter to isolate SEP-related independent components (ICs), and wavelet filtering was used as a time-frequency filter to further enhance the SNR of single-trial SEPs. Results: SEP-related ICs, identified using PICA, showed typical patterns of cortical SEP complex (P39-N50-P60) and scalp topography (centrally distributed with the spatial peak located near vertex). In addition, wavelet filtering significantly enhanced the SNR of single-trial SEPs (p= 0.001). Conclusions: Combining PICA and wavelet filtering offers a space-time-frequency filter that can be used to enhance the SNR of single-trial SEPs greatly, thus providing a reliable estimation of single-trial SEPs. Significance: This method can be used to detect single-trial SEPs and other types of evoked potentials (EPs) in various sensory modalities, thus facilitating the exploration of single-trial dynamics between EPs, behavioural variables (e.g., intensity of perception), as well as abnormalities in intraoperative neurophysiological monitoring. © 2011 International Federation of Clinical Neurophysiology.en_HK
dc.languageengen_US
dc.publisherElsevier Ireland Ltd. The Journal's web site is located at http://www.elsevier.com/locate/clinphen_HK
dc.relation.ispartofClinical Neurophysiologyen_HK
dc.subjectEvent-related potentials (ERPs)en_HK
dc.subjectProbabilistic independent component analysis (PICA)en_HK
dc.subjectSingle-trial analysisen_HK
dc.subjectSomatosensory evoked potentials (SEPs)en_HK
dc.subjectWavelet filteringen_HK
dc.subject.meshData Interpretation, Statistical-
dc.subject.meshElectroencephalography - statistics and numerical data-
dc.subject.meshEvoked Potentials, Somatosensory - physiology-
dc.subject.meshPhotic Stimulation-
dc.subject.meshWavelet Analysis-
dc.titleSingle-trial detection of somatosensory evoked potentials by probabilistic independent component analysis and wavelet filteringen_HK
dc.typeArticleen_HK
dc.identifier.emailZhang, ZG:zgzhang@eee.hku.hken_HK
dc.identifier.emailHung, YS:yshung@eee.hku.hken_HK
dc.identifier.emailLuk, KDK:hcm21000@hku.hken_HK
dc.identifier.emailHu, Y:yhud@hku.hken_HK
dc.identifier.authorityZhang, ZG=rp01565en_HK
dc.identifier.authorityHung, YS=rp00220en_HK
dc.identifier.authorityLuk, KDK=rp00333en_HK
dc.identifier.authorityHu, Y=rp00432en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.clinph.2010.12.052en_HK
dc.identifier.pmid21296019-
dc.identifier.scopuseid_2-s2.0-79957593107en_HK
dc.identifier.hkuros189057en_US
dc.identifier.hkuros207317-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79957593107&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume122en_HK
dc.identifier.issue7en_HK
dc.identifier.spage1429en_HK
dc.identifier.epage1439en_HK
dc.identifier.eissn1872-8952-
dc.identifier.isiWOS:000291102300024-
dc.publisher.placeIrelanden_HK
dc.relation.projectHardware oriented processor for evoked potential fast extraction and auto-detection-
dc.identifier.scopusauthoridHu, L=34770075600en_HK
dc.identifier.scopusauthoridZhang, ZG=8597618700en_HK
dc.identifier.scopusauthoridHung, YS=8091656200en_HK
dc.identifier.scopusauthoridLuk, KDK=7201921573en_HK
dc.identifier.scopusauthoridIannetti, GD=7005461102en_HK
dc.identifier.scopusauthoridHu, Y=7407116091en_HK
dc.identifier.citeulike8800089-

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