A multi-lead ECG classification network system based on modified LADT.
- Author:
Jun FENG
1
;
Yazhu QIU
;
Zhiwen MO
Author Information
1. College of Mathematics and Software Science, Sichuan Normal University, Chengdu 610066, China. fnjun@163.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Databases, Factual;
Electrocardiography;
classification;
Neural Networks (Computer);
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2006;23(5):956-959
- CountryChina
- Language:Chinese
-
Abstract:
An electrocardiogram (ECG) classify system based on the features of the ECG and neural network classification, which is the simulation of the real world situation, was present. First, a modified approach of the linear approximation distance thresholding (LADT) algorithm was studied and the features of the ECG were obtained. Then a neural network which can classify the multi-lead ECG data was trained with these features along the theory of the ECG diagnosis and the situation of ECG diagnosis in practice. Thus take a new idea for the ECG automatic analysis. The algorithm was tested using several ECG signals of MIT-BIH, and the performance was good. The correct rate of the trained wave is 100%, untrained is 78.2%.
