2004 | OriginalPaper | Buchkapitel
PCA Representation of ECG Signal as a Useful Tool for Detection of Premature Ventricular Beats in 3-Channel Holter Recording by Neural Network and Support Vector Machine Classifier
verfasst von : Stanisław Jankowski, Jacek J. Dusza, Mariusz Wierzbowski, Artur Oręziak
Erschienen in: Biological and Medical Data Analysis
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In the paper classification method of compressed ECG signal was presented. Classification of single heartbeats was performed by neural networks and support vector machine. Parameterization of ECG signal was realized by principal component analysis (PCA). For every heartbeat only two descriptors have been used. The results of real Holter signal were presented in tables and as plots in planespherical coordinates. The efficiency of classification is near to 99%.