Estimation of brainstem auditory evoked potentials using a nonlinear adaptive filtering algorithm

Basit Öğe Kaydı
dc.contributor.authorAcir, Nurettin
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2013
dc.departmentNiğde ÖHÜ
dc.description.abstractIn this study, we introduce a novel nonlinear system not only for tracking of both the latency and amplitude variations in brainstem auditory evoked potential (BAEP), but also for reduction of single-trial numbers in BAEP pattern extraction process. Trial-to-trial variations in auditory evoked potential (AEP) are very important in quantifying dynamical properties of the nervous system and in specifying the group-specific effects in clinical applications. Due to the nonlinear dynamics of the AEP, a nonlinear adaptive filtering technique is considered as a powerful tool for tracking such variations. Therefore, we have designed a wavelet network-based nonlinear adaptive filter (WaNe-NAF) satisfying asymptotic stability in the sense of Lyapunov. The simulation results are verified that the proposed WaNe-NAF can effectively track the trial-to-trial variations. We have also compared the WaNe-NAF with the most widely used ensemble averaging technique using real measured human BAEP data. The WaNe-NAF shows promise for requiring less number of ensembles than conventional ensemble averaging method to attain adequate signal quality. As a result, the proposed filtering system is suggested as a powerful tool in AEP acquisition and processing systems.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [TUBITAK-105E084]
dc.description.sponsorshipThis study has been supported by the Scientific and Technological Research Council of Turkey (TUBITAK) with the project number of TUBITAK-105E084. We also appreciate Dr. Ozcan Ozdamar from University of Miami and his group in Neurosensory Engineering Lab. for obtaining a part of human BAEP data.
dc.identifier.doi10.1007/s00521-012-0886-5
dc.identifier.endpage1209
dc.identifier.issn0941-0643
dc.identifier.issue6
dc.identifier.scopus2-s2.0-84876450228
dc.identifier.scopusqualityQ1
dc.identifier.startpage1201
dc.identifier.urihttps://dx.doi.org/10.1007/s00521-012-0886-5
dc.identifier.urihttps://hdl.handle.net/11480/4407
dc.identifier.volume22
dc.identifier.wosWOS:000318003100018
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAcir, Nurettin
dc.language.isoen
dc.publisherSPRINGER
dc.relation.ispartofNEURAL COMPUTING & APPLICATIONS
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAuditory evoked potential
dc.subjectNonlinear adaptive filtering
dc.subjectWavelet network
dc.subjectLyapunov stability
dc.titleEstimation of brainstem auditory evoked potentials using a nonlinear adaptive filtering algorithm
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu