ECG Feature Analysis Based on PoincaréPlot and Symbolic Dynamics

作者：Xin Yi; Zhao Yi Zhang; Mu Yuan Hui

来源：Transactions of Beijing Institute of Technology, 2017, 37(10): 1084-1089.

DOI：10.15918/j.tbit1001-0645.2017.10.017

• Accuracy rate
• Atrial fibrillation
• ECG features
• Heart rate variability
• Normal sinus rhythm
• Premature beats
• Shannon entropy
• Symbolic Dynamics

Heart rate variability (HRV) can be used to predict, prevent heart related diseases and do prognosis evaluation. A method was proposed based on Poincaréplot and symbolic dynamics to analyze ECG feature. Firstly, HRV sequence was extracted from the ECG signal, and presented in Poincaréplot. Then, the splashes in different areas of the plot would be numbered and coded. The entropy of the ECG signal, calculated by the probability of each code, was applied to recognize and classify ECG signal as feature. The experiment results show that, the accuracy rates of classification in normal sinus rhythm and atrial fibrillation, normal sinus rhythm and premature beat are 86.67%, 90% respectively, the method can distinguish normal sinus rhythm from arrhythmia effectively.

• 出版日期2017
• 单位北京理工大学