Prediction of ECG Signal Based on TS Fuzzy Model of Phase Space Reconstruction

Fang Su, Hong-Sheng Dong
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引用次数: 5

Abstract

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.
基于相空间重构TS模糊模型的心电信号预测
心电信号是心脏病诊断的重要依据,准确预测心电信号对心脏病预警和心电数据修复具有重要意义。分析了心电信号的混沌特性,提出了基于相空间重构和TS模糊模型相结合的心电信号预测方法。通过对典型非线性MG时间序列和MIT-BIH标准数据库心电数据的仿真实验表明,与其他预测算法相比,该方法具有更好的预测性能,为心电数据的处理和心脏病的诊断提供了一种新的方法。
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