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PubMed · 17121330

[A multi-lead ECG classification network system based on modified LADT].

Jun Feng·Yazhu Qiu·Zhiwen Mo
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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%.

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AlgorithmsDatabases, FactualElectrocardiographyNeural Networks, ComputerSignal Processing, Computer-AssistedJournal ArticleResearch Support, Non-U.S. Gov't

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BibTeXRIS

Jun Feng, Yazhu Qiu, Zhiwen Mo. 2006. [A multi-lead ECG classification network system based on modified LADT].. https://pubmed.ncbi.nlm.nih.gov/17121330/

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