T wave dynamic modeling and multi channel estimation fusion method

Abstract

The invention discloses a T wave dynamic modeling and multi channel estimation fusion method. Aiming to solve the problems of T wave asymmetry, beat-to-beat dynamic change, myoelectricity pulses in highly dynamic monitoring environment and electrode pulse noise interference, a T wave state space model adaptive to the beat-to-beat dynamic estimation is provided, on the basis of extended Kalman filter, a multi-channel T wave estimation fusion frame is established, T wave parameters with eight independent channels are combined, and T wave robustness estimation in strong noise background can be implemented. The method has the advantages that the sectional characteristics of electrocardiosignals are utilized completely, an analysis module adaptive to asymmetrical T wave estimation is established, the T wave analysis presentation is utilized, the T wave data with eight independent channels are fused completely, the robustness of the T wave beat-to-beat dynamic estimation is improved, and necessary theoretical and technical basis is provided for beat-to-beat detection and estimation of T wave alternating signals in the highly dynamic monitoring environment.

Description

technical field [0001] The invention relates to the technical field of biomedical signal processing, in particular to a method for dynamic modeling and multi-channel fusion estimation of electrocardiogram T waves, especially for the T wave estimation problem of exercise electrocardiograms. Background technique [0002] The phenomenon of T wave alternation is manifested by the alternation of T wave waveforms in the ECG in the order of "ABABAB...", which has very important clinical significance for the recognition and prediction of sudden cardiac death. Most of the existing T wave alternation analysis systems can only qualitatively give the average alternation value within the analysis period, and cannot realize quantitative beat-to-beat TWA detection. [0003] The modeling and estimation of T wave is the premise and foundation of the quantitative analysis of T wave alternation, and it is one of the key issues restricting the quantitative analysis of T wave alternation. As a ...

AI Technical Summary

Problems solved by technology

However, the existing modeling methods generally use a single Gaussian kernel function to model the PQRST wave of the ECG signal. The single Gaussian kernel function cannot effectively characterize the asymmetry of the T wave. When there is a large change, the error of T wave estimation is large, which seriously affects the analysis performance of T wave alternation

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