Phase Space Reconstruction Approach for Ventricular Arrhythmias Characterization



Ventricular arrhythmias, especially tachycardia and fibrillation are one of the main
causes 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.


EMBC, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August 2008

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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)