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Article: Multi-adaptive filtering technique for surface somatosensory evoked potentials processing

TitleMulti-adaptive filtering technique for surface somatosensory evoked potentials processing
Authors
KeywordsAdaptive noise canceller (ANC)
Adaptive signal enhancer (ASE)
Signal-to-noise ratio (SNR)
Somatosensory evoked potential (SEP)
Issue Date2005
PublisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/locate/medengphy
Citation
Medical Engineering And Physics, 2005, v. 27 n. 3, p. 257-266 How to Cite?
AbstractSomatosensory evoked potential (SEP) testing has been widely applied to diagnosis of various neurological disorders. However, SEP recorded using surface electrodes is buried in noises, which makes the signal-to-noise ratio (SNR) very poor. Conventional averaging method usually requires up to thousands of raw SEP input trials to increase the SNR so that an identifiable waveform can be produced for latency and amplitude measurement. In this study, a multi-adaptive filtering (MAF) technique, emerging from the combination of well-developed adaptive noise canceller and adaptive signal enhancer, is introduced for fast and accurate surface SEP extraction. The MAF technique first processes the raw surface recorded SEP by the Canceller with a reference noise channel of background noise for adaptive subtraction before entering the Enhancer. The MAF was verified by filtering simulated SEP signals in which electroencephalography and Gaussian noise of different SNRs were added. It was found that the MAF could effectively suppress the noise and enhance the SEP components such that the SNR of the SEP is improved. Results showed that MAF with 50 input trials could provide similar performance in SEP detection to those extracted by the conventional averaging method with 1000 trials even at an SNR of -20 dB. © 2004 IPEM. Published by Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/73619
ISSN
2015 Impact Factor: 1.619
2015 SCImago Journal Rankings: 0.784
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLam, BSCen_HK
dc.contributor.authorHu, Yen_HK
dc.contributor.authorLu, WWen_HK
dc.contributor.authorLuk, KDKen_HK
dc.contributor.authorChang, CQen_HK
dc.contributor.authorQiu, Wen_HK
dc.contributor.authorChan, FHYen_HK
dc.date.accessioned2010-09-06T06:53:08Z-
dc.date.available2010-09-06T06:53:08Z-
dc.date.issued2005en_HK
dc.identifier.citationMedical Engineering And Physics, 2005, v. 27 n. 3, p. 257-266en_HK
dc.identifier.issn1350-4533en_HK
dc.identifier.urihttp://hdl.handle.net/10722/73619-
dc.description.abstractSomatosensory evoked potential (SEP) testing has been widely applied to diagnosis of various neurological disorders. However, SEP recorded using surface electrodes is buried in noises, which makes the signal-to-noise ratio (SNR) very poor. Conventional averaging method usually requires up to thousands of raw SEP input trials to increase the SNR so that an identifiable waveform can be produced for latency and amplitude measurement. In this study, a multi-adaptive filtering (MAF) technique, emerging from the combination of well-developed adaptive noise canceller and adaptive signal enhancer, is introduced for fast and accurate surface SEP extraction. The MAF technique first processes the raw surface recorded SEP by the Canceller with a reference noise channel of background noise for adaptive subtraction before entering the Enhancer. The MAF was verified by filtering simulated SEP signals in which electroencephalography and Gaussian noise of different SNRs were added. It was found that the MAF could effectively suppress the noise and enhance the SEP components such that the SNR of the SEP is improved. Results showed that MAF with 50 input trials could provide similar performance in SEP detection to those extracted by the conventional averaging method with 1000 trials even at an SNR of -20 dB. © 2004 IPEM. Published by Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/locate/medengphyen_HK
dc.relation.ispartofMedical Engineering and Physicsen_HK
dc.rightsMedical Engineering & Physics. Copyright © Elsevier Ltd.en_HK
dc.subjectAdaptive noise canceller (ANC)en_HK
dc.subjectAdaptive signal enhancer (ASE)en_HK
dc.subjectSignal-to-noise ratio (SNR)en_HK
dc.subjectSomatosensory evoked potential (SEP)en_HK
dc.subject.meshAlgorithmsen_HK
dc.subject.meshBrain Mapping - methodsen_HK
dc.subject.meshComputer Simulationen_HK
dc.subject.meshDiagnosis, Computer-Assisted - methodsen_HK
dc.subject.meshElectroencephalography - methodsen_HK
dc.subject.meshEvoked Potentials, Somatosensory - physiologyen_HK
dc.subject.meshHumansen_HK
dc.subject.meshModels, Neurologicalen_HK
dc.subject.meshModels, Statisticalen_HK
dc.subject.meshReproducibility of Resultsen_HK
dc.subject.meshSensitivity and Specificityen_HK
dc.subject.meshSignal Processing, Computer-Assisteden_HK
dc.titleMulti-adaptive filtering technique for surface somatosensory evoked potentials processingen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1350-4533&volume=27&spage=257&epage=266&date=2005&atitle=Multi-adaptive+Filtering+Technique+For+Surface+Somatosensory+Evoked+Potentials+Processingen_HK
dc.identifier.emailHu, Y: yhud@hku.hken_HK
dc.identifier.emailLu, WW: wwlu@hku.hken_HK
dc.identifier.emailLuk, KDK: hcm21000@hku.hken_HK
dc.identifier.emailChang, CQ: cqchang@eee.hku.hken_HK
dc.identifier.authorityHu, Y=rp00432en_HK
dc.identifier.authorityLu, WW=rp00411en_HK
dc.identifier.authorityLuk, KDK=rp00333en_HK
dc.identifier.authorityChang, CQ=rp00095en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.medengphy.2004.09.007en_HK
dc.identifier.pmid15694610-
dc.identifier.scopuseid_2-s2.0-13444261938en_HK
dc.identifier.hkuros101871en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-13444261938&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume27en_HK
dc.identifier.issue3en_HK
dc.identifier.spage257en_HK
dc.identifier.epage266en_HK
dc.identifier.isiWOS:000227763700010-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridLam, BSC=36747918300en_HK
dc.identifier.scopusauthoridHu, Y=7407116091en_HK
dc.identifier.scopusauthoridLu, WW=7404215221en_HK
dc.identifier.scopusauthoridLuk, KDK=7201921573en_HK
dc.identifier.scopusauthoridChang, CQ=7407033052en_HK
dc.identifier.scopusauthoridQiu, W=36461603400en_HK
dc.identifier.scopusauthoridChan, FHY=7202586429en_HK

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