Electrocardiogram analysis using a combination of statistical, geometric, and nonlinear heart rate variability features

Abstract Objective The paper addresses a common and recurring problem of electrocardiogram (ECG) classification based on heart rate variability (HRV) analysis. Current understanding of the limits of HRV analysis in diagnosing different cardiac conditions is not complete. Existing research suggests t...

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Veröffentlicht in:	Artificial intelligence in medicine 2011-03, Vol.51 (3), p.175-186
Hauptverfasser:	Jovic, Alan, Bogunovic, Nikola
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms C4.5 decision tree Classification Data Interpretation, Statistical Decision trees Electrocardiography - methods Heart - physiology Heart disorder classification Heart Rate - physiology Heart rate variability Humans Internal Medicine Learning theory Neural networks Nonlinear analysis Nonlinear Dynamics Nonlinearity Other Radio frequencies Random forest Support vector machines
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