Paroxysmal atrial fibrillation recognition based on multi-scale Rényi entropy of ECG
| Autor: | Xin Yi, Shi Caicheng, Zhao Yizhang, Li Qin, Mu Yuanhui |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Paroxysmal atrial fibrillation Entropy 0206 medical engineering Biomedical Engineering Biophysics Health Informatics Bioengineering Sympathetic nerve 02 engineering and technology Effective algorithm Biomaterials Rényi entropy Electrocardiography 03 medical and health sciences 0302 clinical medicine Heart Rate Internal medicine Atrial Fibrillation Humans Medicine Heart rate variability Diagnosis Computer-Assisted business.industry Atrial fibrillation Models Theoretical medicine.disease 020601 biomedical engineering Vagus nerve Clinical diagnosis Cardiology business Algorithms 030217 neurology & neurosurgery Information Systems |
| Zdroj: | Technology and Health Care. 25:189-196 |
| ISSN: | 1878-7401 0928-7329 |
| DOI: | 10.3233/thc-171321 |
| Popis: | Background Atrial fibrillation (AF) is a common type of arrhythmia disease, which has a high morbidity and can lead to some serious complications. The ability to detect and in turn prevent AF is extremely significant to the patient and clinician. Objective Using ECG to detect AF and develop a robust and effective algorithm is the primary objective of this study. Methods Some studies show that after AF occurs, the regulatory mechanism of vagus nerve and sympathetic nerve will change. Each R-R interval will be absolutely unequal. After studying the physiological mechanism of AF, we will calculate the Renyi entropy of the wavelet coefficients of heart rate variability (HRV) in order to measure the complexity of PAF signals, as well as extract the multi-scale features of paroxysmal atrial fibrillation (PAF). Results The data used in this study is obtained from MIT-BIH PAF Prediction Challenge Database and the correct rate in classifying PAF patients from normal persons is 92.48%. Conclusions The results of this experiment proved that AF could be detected by using this method and, in turn, provide opinions for clinical diagnosis. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|