Recognizing Ventricular Tachycardia and Fibrillation with Hurst Index
ZHAO Qing
ZHAO Jie
Abstract：Objective To recognize normal sinus rhythm (NSR), ventricular tachycardia (VT) and ventricular fibrillation (VF) from each other accurately and promptly. Methods A nonlinear descriptor based on multi-scale analysis, Hurst index, as a feature to quantify the nonlinear dynamics behavior of the ECG signal, was quoted in this paper. Results The nonlinear technique, Hurst index was examined and evaluated with ECG signals extracted from MIT-BIH Arrhythmia Database, MIT-BIH Malignant Ventricular Ectopy Database, and CU Ventricular Tachyarrhythmia Database under a specific moving-window length. The experiment showed good performance of this nonlinear descriptor. When the window length was 5 s long, the recognition accuracy for each of NSR, VT and VF was 100%. Besides, the computing speed was much faster than the speed obtained with a traditional non-linear technique, the complexity measure algorithm. Conclusion The Hurst index has a strong potential for life-threatening ventricular arrhythmia recognition in clinical applications.
Keywords：Hurst indexventricular tachycardiaventricular fibrillationmoving window
Publication Date：2008-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 455-460 )