WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402
Volume 13, 2016
Detection Ventricular Tachycardia and Fibrillation Using the Lempel-Ziv Complexity and Wavelet Transform
Authors: , , ,
Abstract: Detection of ventricular tachycardia (VT) and ventricular fibrillation (VF) is crucial for the success of saving the patient’s life. The complexity of the heart signals has changed significantly when the heart state switches. In this study we proposed a novel method for detection of ventricular fibrillation (VF) and ventricular tachycardia (VT), based upon the Lempel-Ziv complexity and Wavelet transform. With Mallat’s pyramidal algorithms, first decomposed electrocardiogram (ECG) signals and reconstructed it into approximate and detail coefficients. Then the complexity of each scale was used as a feature to be sent to SVM classifiers. Furthermore, other classification VT and VF methods were used. The experimental results showed the proposed method could successfully distinguish VF from VT with the highest accuracy up to 99.50%.
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Keywords: Ventricular Fibrillation, Ventricular Tachycardia, the Lempel–Ziv Complexity, Mallat’s Pyramidal Algorithms
Pages: 118-125
WSEAS Transactions on Information Science and Applications, ISSN / E-ISSN: 1790-0832 / 2224-3402, Volume 13, 2016, Art. #12