Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10351477 | Computers in Biology and Medicine | 2013 | 9 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Ebadollah Kheirati Roonizi, Reza Sameni,