Institutional Repository
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Time-frequency analysis methods to quantify the time-varying microstructure of sleep EEG spindles: possibility for dementia biomarkers?

Zervakis Michail, Sakkalis, Vangelis, Economou, Nicolas 1953-1993, Ktonas, P. Y, Soldatos, Christos, Xanthopoulos, Petros, Paparrigopoulos, T, Golemati, S, Ortigueira, Manuel Duarte, Tsekou H., Bonakis A., Theodoropoulos P., Vassilopoulos D., Papageorgiou S. G.

Simple record


URIhttp://purl.tuc.gr/dl/dias/B9C0A173-8271-43DD-9EAB-6246DC3EFA2A-
Identifierhttps://doi.org/10.1016/j.jneumeth.2009.09.001-
Identifierhttps://www.sciencedirect.com/science/article/pii/S0165027009004920?via%3Dihub-
Languageen-
Extent10 pagesen
TitleTime-frequency analysis methods to quantify the time-varying microstructure of sleep EEG spindles: possibility for dementia biomarkers?en
CreatorZervakis Michailen
CreatorΖερβακης Μιχαηλel
CreatorSakkalis, Vangelisen
CreatorEconomou, Nicolas 1953-1993en
CreatorKtonas, P. Yen
CreatorSoldatos, Christosen
CreatorXanthopoulos, Petrosen
CreatorPaparrigopoulos, Ten
CreatorGolemati, Sen
CreatorOrtigueira, Manuel Duarteen
CreatorTsekou H.en
CreatorBonakis A.en
CreatorTheodoropoulos P.en
CreatorVassilopoulos D.en
CreatorPapageorgiou S. G.en
PublisherElsevieren
Content SummaryThe time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies and can be quantified with a number of techniques. In this paper, real and simulated sleep spindles were regarded as AM/FM signals modeled by six parameters that define the instantaneous envelope (IE) and instantaneous frequency (IF) waveforms for a sleep spindle. These parameters were estimated using four different methods, namely the Hilbert transform (HT), complex demodulation (CD), matching pursuit (MP) and wavelet transform (WT). The average error in estimating these parameters was lowest for HT, higher but still less than 10% for CD and MP, and highest (greater than 10%) for WT. The signal distortion induced by the use of a given method was greatest in the case of HT and MP. These two techniques would necessitate the removal of about 0.4 s from the spindle data, which is an important limitation for the case of spindles with duration less than 1 s. Although the CD method may lead to a higher error than HT and MP, it requires a removal of only about 0.23 s of data. An application of this sleep spindle parameterization via the CD method is proposed, in search of efficient EEG-based biomarkers in dementia. Preliminary results indicate that the proposed parameterization may be promising, since it can quantify specific differences in IE and IF characteristics between sleep spindles from dementia subjects and those from aged controls.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-26-
Date of Publication2009-
SubjectBasic medical sciencesen
SubjectBasic sciences, Medicalen
SubjectBiomedical sciencesen
SubjectHealth sciencesen
SubjectPreclinical sciencesen
SubjectSciences, Medicalen
Subjectmedical sciencesen
Subjectbasic medical sciencesen
Subjectbasic sciences medicalen
Subjectbiomedical sciencesen
Subjecthealth sciencesen
Subjectpreclinical sciencesen
Subjectsciences medicalen
SubjectSleep spindlesen
SubjectAM/FM signalsen
SubjectInstantaneous envelopeen
SubjectInstantaneous frequencyen
SubjectBiomarkersen
SubjectDementiaen
Bibliographic CitationP. Y. Ktonas, S. Golemati, P. Xanthopoulos, V. Sakkalis, M. D. Ortigueira, H. Tsekou, M. Zervakis, T. Paparrigopoulos, A. Bonakis, N. T. Economou, P. Theodoropoulos, S. G. Papageorgiou, D. Vassilopoulos and C. R. Soldatos ,"Time–frequency analysis methods to quantify the time-varying microstructure of sleep EEG spindles: possibility for dementia biomarkers?," J. of Neur. Methods, vol. 185, no. 1, pp. 133–142, Dec. 2009. doi: 10.1016/j.jneumeth.2009.09.001en

Services

Statistics