Simple Algorithms and Architectures for B-spline Interpolation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Curve and surface fitting with splines
Curve and surface fitting with splines
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
Multichannel ECG and noise modeling: application to maternal and fetal ECG signals
EURASIP Journal on Applied Signal Processing
Fast degree elevation and knot insertion for B-spline curves
Computer Aided Geometric Design
B-spline signal processing. I. Theory
IEEE Transactions on Signal Processing
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In this paper a general framework is presented for morphological modeling of cardiac signals from a signal decomposition perspective. General properties of a desired morphological model are presented and special cases of the model are studied in detail. The presented approach is studied for modeling the morphology of electrocardiogram (ECG) signals. Specifically, three types of ECG modeling techniques, including polynomial spline models, sinusoidal model and a model previously presented by McSharry et al., are studied within this framework. The proposed method is applied to datasets from the PhysioNet ECG database for compression and modeling of normal and abnormal ECG signals. Quantitative and qualitative results of these applications are also presented and discussed.