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Fractal Random Walk and Classification of ECG Signal

초록

영어

This paper presents a new nonlinear method to analyze ventricular arrhythmia(VA) and sinus rhythms(SR). The problem is introduced from the discussion of Fractal Random Walk characteristics of ECG signal. Further, the fractal analysis is used to distinguish ventricular
flutter(VFL), ventricular fibrillation(VF), ventricular tachycardia(VT)) and sinus rhythms(SR) from the raw electrocardiogram(ECG) data. The method has a three step processing. First, calculating the slope of permutation entropy(PE) to detect the onset of ventricular arrhythmia; Second, using regularization dimension(RD) to classify SR, VFL and VT/VF; Finally, according to multifractal spectrum(MS) area to distinguish VT and VF. Four databases are used to detect the method, and the accuracy of every step is 93.33%, 100% and 98%. As a whole, the accuracy of detecting onset of ventricular arrhythmia and confirming which ventricular arrhythmia is, is VFL 93.33%, VT and VF 91.47%.

목차

Abstract
 1. Introduction
 2. The problem introduce
 3. Theory and methods
  3.1. Permutation Entropy
  3.2. Regularization Dimension
  3.3. Multifractal Spectrum
  3.4. Methods
 4. Materials and results
 5. Discussion and conclusion
 6. References

저자정보

  • Daoming Zhang College of Information and Electrical Engineering
  • Guojun Tan College of Information and Electrical Engineering
  • Jifei Hao College of Information and Electrical Engineering

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