Universidad de Zaragoza Repository

Resumen: This paper shows an adaptive statistical test for QRS detection of electrocardiography (ECG) signals. The method is based on a M-ary generalized likelihood ratio test (LRT) defined over a multiple observation window in the Fourier domain. The motivations for proposing another detection algorithm based on maximum a posteriori (MAP) estimation are found in the high complexity of the signal model proposed in previous approaches which i) makes them computationally unfeasible or not intended for real time applications such as intensive care monitoring and (ii) in which the parameter selection conditions the overall performance. In this sense, we propose an alternative model based on the independent Gaussian properties of the Discrete Fourier Transform (DFT) coefficients, which allows to define a simplified MAP probability function. In addition, the proposed approach defines an adaptive MAP statistical test in which a global hypothesis is defined on particular hypotheses of the multiple observation window. In this sense, the observation interval is modeled as a discontinuous transmission discrete-time stochastic process avoiding the inclusion of parameters that constraint the morphology of the QRS complexes.
Idioma: Inglés
DOI: 10.1371/journal.pone.0110629
Año: 2014
Publicado en: PLoS One 9, 10 (2014), e110629 [12pp]
ISSN: 1932-6203
Factor impacto JCR: 3.234 (2014)
Categ. JCR: MULTIDISCIPLINARY SCIENCES rank: 8 / 56 = 0.143 (2014) - Q1 - T1
Financiación: info:eu-repo/grantAgreement/ES/MICINN/TEC2012-34306
Tipo y forma: Article (Published version)
Área (Departamento): Teoría de la Señal y Comunicaciones (Departamento de Ingeniería Electrónica y Comunicaciones)

You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

Exportado de SIDERAL (2016-12-14-14:51:35)


Visitas y descargas

Este artículo se encuentra en las siguientes colecciones:
Articles > Artículos por área > Teoría de la Señal y Comunicaciones