Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7790
Full metadata record
DC FieldValueLanguage
dc.contributor.authorCvetkovic, Dean-
dc.contributor.authorÜbeyli, Elif Derya-
dc.contributor.authorCosic, Irena-
dc.date.accessioned2021-09-11T15:59:50Z-
dc.date.available2021-09-11T15:59:50Z-
dc.date.issued2008en_US
dc.identifier.issn1051-2004-
dc.identifier.urihttps://doi.org/10.1016/j.dsp.2007.05.009-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/7790-
dc.description.abstractThis paper presents the expefimental pilot study to investigate the effects of pulsed electromagnetic field (PEMF) at extremely low frequency (ELF) in response to photoplethysmographic (PPG), electrocardiographic (ECG), electroencephalographic (EEG) activity. The assessment of wavelet transform (WT) as a feature extraction method was used in representing the electrophysiological signals. Considering that classification is often more accurate when the pattern is simplified through representation by important features, the feature extraction and selection play an important role in classifying systems such as neural networks. The PPG, ECG, EEG signals were decomposed into time-frequency representations using discrete wavelet transform (DWT) and the statistical features were calculated to depict their distribution. Our pilot study investigation for any possible electrophysiological activity alterations due to ELF PEMF exposure, was evaluated by the efficiency of DWT as a feature extraction method in representing the signals. As a result, this feature extraction has been justified as a feasible method. (c) 2007 Elsevier Inc. All rights reserved.en_US
dc.language.isoenen_US
dc.publisherAcademic Press Inc Elsevier Scienceen_US
dc.relation.ispartofDigital Signal Processingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectfeature extractionen_US
dc.subjectPPGen_US
dc.subjectECGen_US
dc.subjectEMGen_US
dc.subjectdiscrete wavelet transformen_US
dc.subjectPEMFen_US
dc.subjectELFen_US
dc.subjectbioeffectsen_US
dc.titleWavelet transform feature extraction from human PPG, ECG, and EEG signal responses to ELF PEMF exposures: A pilot studyen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.volume18en_US
dc.identifier.issue5en_US
dc.identifier.startpage861en_US
dc.identifier.endpage874en_US
dc.authorid0000-0002-4218-7390-
dc.identifier.wosWOS:000258035400015en_US
dc.identifier.scopus2-s2.0-47049090821en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.identifier.doi10.1016/j.dsp.2007.05.009-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

145
checked on Mar 23, 2024

WEB OF SCIENCETM
Citations

143
checked on Mar 9, 2024

Page view(s)

48
checked on Mar 25, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.