Parameter Extraction for Automatic Analysis of ECG Traces
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The present paper aims at introducing original techniques of linear digital filtering (traditional and optimal ones) for the automatic processing of ECG traces. Innovative feature extraction methods are also described in the area of parametric identification (feasible both using stochastic and deterministic signals) and of spectral estimate (Maximum Entropy Spectrum, Pisarenko Harmonic Deconvolution and Prony method). Results are shown in the field of automatic measurements of P, QRS, T waves and of heart rate variability on the basis of the time series constituted by the R-R intervals. The obtained parametrizations are discussed together with interesting applications foreseen in the future by the further development of methodological and technological means towards the implementation of new equipment for diagnosis and patient monitoring.
KeywordsHeart Rate Variability Digital Filter Spectral Estimation Parameter Extraction Amplitude Histogram
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