File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Detection of dynamic rhythms of electroencephalography by using wavelet packets decomposition

TitleDetection of dynamic rhythms of electroencephalography by using wavelet packets decomposition
Authors
KeywordsMedical sciences
Computer applications
Issue Date2001
PublisherIEEE.
Citation
The 23rd IEEE Engineering in Medicine and Biology Society Conference Proceedings, Istanbul, Turkey, 25-28 October 2001, v. 2, p. 1865-1868 How to Cite?
AbstractWavelet packet decomposition is used to investigate the time-varying characteristics of clinical EEG signals. On the basis of the nonstationary nature of clinical EEG rhythms, wavelet packet analysis is employed for designing filters with different frequency characteristics to detect 4 kinds of EEG rhythms. The coefficients of wavelet transformation corresponding to the rhythms are used to form the dynamic brain electrical activity mapping (DBEAM). In order to understand the dynamic rhythms of the EEG, some clinical EEG are analyzed and compared. It is indicated from the experimental results that the dynamic characteristics of clinical brain electrical activities can be provided in terms of wavelet packet decomposition.
Persistent Identifierhttp://hdl.handle.net/10722/46321
ISSN
2020 SCImago Journal Rankings: 0.282

 

DC FieldValueLanguage
dc.contributor.authorShen, MFen_HK
dc.contributor.authorSun, Len_HK
dc.contributor.authorChan, FHYen_HK
dc.date.accessioned2007-10-30T06:47:17Z-
dc.date.available2007-10-30T06:47:17Z-
dc.date.issued2001en_HK
dc.identifier.citationThe 23rd IEEE Engineering in Medicine and Biology Society Conference Proceedings, Istanbul, Turkey, 25-28 October 2001, v. 2, p. 1865-1868en_HK
dc.identifier.issn1557-170Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/46321-
dc.description.abstractWavelet packet decomposition is used to investigate the time-varying characteristics of clinical EEG signals. On the basis of the nonstationary nature of clinical EEG rhythms, wavelet packet analysis is employed for designing filters with different frequency characteristics to detect 4 kinds of EEG rhythms. The coefficients of wavelet transformation corresponding to the rhythms are used to form the dynamic brain electrical activity mapping (DBEAM). In order to understand the dynamic rhythms of the EEG, some clinical EEG are analyzed and compared. It is indicated from the experimental results that the dynamic characteristics of clinical brain electrical activities can be provided in terms of wavelet packet decomposition.en_HK
dc.format.extent459434 bytes-
dc.format.extent13817 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rights©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectMedical sciencesen_HK
dc.subjectComputer applicationsen_HK
dc.titleDetection of dynamic rhythms of electroencephalography by using wavelet packets decompositionen_HK
dc.typeConference_Paperen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/IEMBS.2001.1020588-
dc.identifier.scopuseid_2-s2.0-61549107288-
dc.identifier.hkuros72153-
dc.identifier.issnl1557-170X-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats