ECG compression method using Lorentzian functions model

Authors:
Abdelaziz Ouamri;Amine Naït-Ali
Affiliations:
Université des Sciences et de la Technologie d'Oran, Département Electronique, Laboratoire LSI, BP 1505, Oran El'Mnouar, 31 Oran, Algeria;Université Paris 12, LISSI EA 3956, 61 avenue du Général de Gaulle, 94010 Créteil, France
Venue:
Digital Signal Processing
Year:
2007

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Abstract

An ECG compression algorithm using a combination of Lorentzian functions model is proposed in this paper. In order to estimate the parameters of the Lorentzian functions, the discrete Fourier transform (DFT) is first applied to a mean removed ECG signal from which only the most significant DFT coefficients are retained. The obtained coefficients are, then modeled as the sum of a given number of superimposed exponentially damped sinusoids (EDS), commonly identified by their amplitudes, real damping factors, frequencies and initial phases. Finally, these EDS parameters are estimated, using SVD method, then coded. The algorithm has been tested for its coding efficiency and reconstruction capability by applying it to several popular, benchmark ECG signals. Encouraging results have been obtained.