Ecg-based Heart Beat Detection Using Rational Functions
نویسنده
چکیده
The aim of this paper is to present a novel heart beat detection algorithm using rational modelling of ECG signals. The algorithm considers several candidate beat locations. For a given candidate a rational model is fitted to the ECG signal by means of numerical optimization and Fourier partial sums with respect to the Malmquist-Takenaka system. The resultant model parameters are used as a basis of classification. The classification is performed by an SVM classifier, which is trained on annotated ECG records of the PhysioNet database.
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تاریخ انتشار 2016