Prediction of ECG Signal Based on TS Fuzzy Model of Phase Space Reconstruction
Fang Pei Su, Hongsheng Dong · 2019
ECG is an important gist for the diagnosis of heart disease, it is significant for heart disease warning in advance and ECG data repairing to predict ECG signal accurately. In this paper, the chaotic characteristics of ECG signal have been analyzed, and the ECG signal prediction based on the combination of the phase space reconstruct of ECG signal and the TS fuzzy model is proposed. The simulation experiment dealing with the typical nonlinear MG time series and the ECG data of MIT-BIH standard database shows that, and compared with other prediction algorithms, the proposed method achieves a better prediction performance, and which provides a new method for the processing of ECG data and the diagnosis of heart diseases.