title: Real time QRS detection based on M-ary likelihood ratio test on the DFT coefficients.
abstract: 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.
authors.affiliation: Department of Signal Theory, Telematics and Communications, CITIC, University of Granada, Granada, Spain.
authors.forename: Juan Manuel
authors.initials: JM
authors.lastname: Górriz
authors.affiliation: Department of Signal Theory, Telematics and Communications, CITIC, University of Granada, Granada, Spain.
authors.forename: Javier
authors.initials: J
authors.lastname: Ramírez
authors.affiliation: Department of Signal Theory, Telematics and Communications, CITIC, University of Granada, Granada, Spain.
authors.forename: Alberto
authors.initials: A
authors.lastname: Olivares
authors.affiliation: Department of Signal Theory, Telematics and Communications, CITIC, University of Granada, Granada, Spain.
authors.forename: Pablo
authors.initials: P
authors.lastname: Padilla
authors.affiliation: Department Computer Architecture and Computer Technology, CITIC, University of Granada, Granada, Spain.
authors.forename: Carlos G
authors.initials: CG
authors.lastname: Puntonet
authors.affiliation: Department of Informatics, University of Almería, Almería, Spain.
authors.forename: Manuel
authors.initials: M
authors.lastname: Cantón
authors.affiliation: Department of Electronic Engineering and Communications, University of Zaragoza, Zaragoza, Spain.
authors.forename: Pablo
authors.initials: P
authors.lastname: Laguna
mesh_terms: D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical