Chaotic and nonlinear analysis of ECG signal to detect PVCarrhythmia
عنوان مقاله: Chaotic and nonlinear analysis of ECG signal to detect PVCarrhythmia
شناسه ملی مقاله: AREEI03_010
منتشر شده در سومین کنفرانس پژوهشی های کاربردی در مهندسی برق در سال 1401
شناسه ملی مقاله: AREEI03_010
منتشر شده در سومین کنفرانس پژوهشی های کاربردی در مهندسی برق در سال 1401
مشخصات نویسندگان مقاله:
Seyed Mohammad Hossein Emami - Department of Biomedical Engineering, University of Neyshabur, Neyshabur, Iran
Mahdieh Ghasemi - Department of Biomedical Engineering, University of Neyshabur, Neyshabur, Iran
خلاصه مقاله:
Seyed Mohammad Hossein Emami - Department of Biomedical Engineering, University of Neyshabur, Neyshabur, Iran
Mahdieh Ghasemi - Department of Biomedical Engineering, University of Neyshabur, Neyshabur, Iran
Early diagnosis of heart disease plays an important role in treating the disease and preventing its dangerousconsequences. One of the most common cardiac arrhythmias is premature ventricular contraction (PVC). In thisresearch, using the extraction of chaotic characteristics of the ECG signal, ventricular premature contraction arrhythmiahas been detected. Four important characteristics of chaotic systems used in this article are fractal dimension, Lyapunovexponent, correlation dimension and approximate entropy. Two supervised and unsupervised methods are used to detectarrhythmia. The nearest neighbor method was used as a supervised method for classification and the results were ۹۳.۰۱%accuracy and ۹۰.۰۱% precision. The second method is known as K-Means and was used as an unsupervised method forclustering and the results were ۷۹.۰۶% accuracy and ۷۸.۷۸% precision.
کلمات کلیدی: Electrocardiogram, premature ventricular contraction (PVC), Chaos, KNN, K-Means
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1674063/