title: [A multi-lead ECG classification network system based on modified LADT].
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%.
authors.affiliation: College of Mathematics and Software Science, Sichuan Normal University, Chengdu 610066, China. fnjun@163.com
authors.forename: Jun
authors.initials: J
authors.lastname: Feng
authors.forename: Yazhu
authors.initials: Y
authors.lastname: Qiu
authors.forename: Zhiwen
authors.initials: Z
authors.lastname: Mo
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D004562:Electrocardiography / Q000145:classification*; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted