Phase Space Reconstruction Approach for Ventricular Arrhythmias Characterization
Authors
Abstract
Ventricular arrhythmias, especially tachycardia and fibrillation are one of the maincauses of sudden cardiac death. Therefore, the development of methodologies,
enable to detect their occurrence and to characterize their time evolution,
is of fundamental importance.
This work proposes a non-linear dynamic signal processing approach to address the problem.
Based on the phase space reconstruction of the electrocardiogram (ECG), some features are extracted for each ECG time window. Features from current and previous time windows
are provided to a dynamic neural network classifier, enabling arrhythmias detection and evolution trends assessment.
Sensitivity and specificity values, evaluated from public MIT-BIH databases,
show the effectiveness of the proposed strategy.
Conference
EMBC, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August 2008PDF File
Cited by
Year 2013 : 1 citations
Balasundaram, K., et al. "A classification scheme for ventricular arrhythmias using wavelets analysis." Medical & biological engineering & computing (2013): 1-12.
Year 2012 : 1 citations
Balasundaram, Krishnanand. "Analysis Of Electrocardiograms During Human Ventricular Arrhythmias For Optimizing Treatment Options." (2012)