The proposed cubic spline-based method enables fully automated ECG signal processing and wave identification without human intervention.
May support automated ECG workflows; leaves open prospective validation before clinical use.
A method is presented for an analysis of the ECG. Using cubic spline techniques we proceed first to a smoothing of the signal and then to the elimination of baseline drift. The properties of the calculated derivatives are used to establish criteria for the identification of the ECG waves and the measurement of their essential parameters. The complete procedure can be carried out by a computer, without human intervention. The results of this fully automatic procedure can be used directly as a means of classifying the ECG.
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Caroubalos et al. (1988) studied this question.
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