Earticle

초록

영어

Detection of cardiac arrhythmias, particularly ventricular fibrillation (VF), and ventricular tachycardia (VT) have been highly regarded and has done several works in this field. In this study, a method based on the Takagi-Sugeno-Kang (TSK) fuzzy system for ECG arrhythmia detection and classification of normal sinus rhythm (NSR), ventricular fibrillation (VF) and ventricular tachycardia (VT) has been used. ECG arrhythmia signals have been obtained from MIT-BIH database. At the first, preprocessing is performed on the signals to get a signal without any noise. Then two features of ECG signals include an average period T (i.e. the time interval between two R peaks) and amplitude of QRS complex, are used as inputs to fuzzy classifier. The triangular membership functions for converts crisp input values (features of ECG signals) to the fuzzy values are used to provide the fuzzy system. Using genetic algorithms, optimization rules with membership functions by minimizing the error function, and convert them to proper rules and membership functions for classifying arrhythmias do with high accuracy. Finally, we achieved the classification accuracy for normal signals (NSR) 91.66%, for VT signals 92.86% and for VT signals equal to 100%. We obtained the overall accuracy of the classifier 93.33%. Also, sensitivity for NSR signals is equal 92.30%, for VT signals is 93.33% and for VF signals is equal to 100%. Specificity for NSR, VT and VF signals is equal to 94.44%, 93.57% and 100% respectively. The simply of propose method can be considered as its major advantage.

목차

Abstract
 1. Introduction
 2. Review of Previous Research
 3. Introduce arrhythmias using in this classification
 4. Preprocessing and Feature Extraction of ECG Signals
 5. Fuzzy Classifier System Design
 6. Genetic Algorithm to Optimize the Classifier Parameters
 7. Classification of Cardiac Arrhythmias
 8. Result
 9. Conclusion and Discussion
 10. Suggestions and Future Studies
 Acknowledgements
 References

키워드

저자

• Naser Safdarian [ Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University ]
• Keivan Maghooli [ Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University ]
• Nader Jafarnia Dabanloo [ Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605