Design of BP neural network based on multi-parametes for VF detection

VernacularTitle:用于室颤节律辨识的多参数融合BP神经网络设计
Author: Ming YU ; Feng CHEN ; Guang ZHANG ; Biao GU ; Liangzhe LI ; Chunchen WANG ; Dan WANG ; Taihu WU
Publication Type:Journal Article
Keywords: electrocardiogram; ventricular fibrillation; BP neural network; multi-parameter fusion identification
From: Military Medical Sciences 2016;40(10):829-832,838
CountryChina
Language:Chinese
Abstract: Objective To develop a BP neural network to differentiate between ventricular fibrillation( VF) and non-VF rhythms.Methods Eighteen metrics were extracted from the ECG signals.Each of these metrics respectively characterized each aspect of the signals, such as morphology, gaussianity, spectra, variability, and complexity.These metrics were regarded as the input vector of the BP neural network.After training, a classifier used for VF and non-VF rhythm classification was obtained.Results and Conclusion The constructed BP neural network was tested with the databases of VFDB and CUDB, and the accuracy was 98.61%and 95.37%, respectively.