Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38380
Title: Testing Gaussian-based kernels for modelling T-waves and P-waves in ECG signals
Authors: Dos Santos, E. M. B. E.
Madeiro, J. P. V.
Cortez, P. C.
Felix, J. H. S.
Marques, J. A. L.
Schlindwein, Fernando S.
First Published: 17-Oct-2016
Presented at: XXV Congresso Brasileiro de Engenharia Biomédica – CBEB 2016, Foz do Iguaçu, Brazil
Start Date: 17-Oct-2016
End Date: 20-Oct-2016
Citation: XXV Congresso Brasileiro de Engenharia Biomédica – CBEB 2016, Foz do Iguaçu, Brazil 2016
Abstract: This paper presents a comparative study of segmentation and modelling of P and T waves in electrocardiograms, using three different mathematical models: Gaussian function, a composition of two Gaussian functions and Rayleigh probability density function. In order to evaluate the adaptability and the matching degree between each model and each characteristic wave, we compute the evolution of the corresponding parameters related to the fitted kernels throughout ECG records from the well-known QT database, as well as the normalized least mean square error between each model and the analysed waves. We have found the most accurate results for the kernel derived from the composition of two Gaussian functions, for which the average of normalized relative least mean square errors for T-wave and P-wave were, respectively, 1,56% and 9,13%, considering both available leads from the QT database.
Links: http://www.cbeb.org.br/en/
http://hdl.handle.net/2381/38380
Version: Post-print
Status: Peer-reviewed
Type: Conference Paper
Rights: Creative Commons “Attribution Non-Commercial No Derivatives” licence CC BY-NC-ND, further details of which can be found via the following link: http://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections:Conference Papers & Presentations, Dept. of Engineering

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BannerCBEB2016_GaussianModels.pdfPublished (publisher PDF)676.74 kBAdobe PDFView/Open
Kernels+for+Twave+and+Pwave+Madeiro+CBEB2016_FSS.pdfPost-review (final submitted author manuscript)603.66 kBAdobe PDFView/Open


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