• Sheng Wu Yi Xue Gong Cheng Xue Za Zhi · Oct 2006

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

    • Jun Feng, Yazhu Qiu, and Zhiwen Mo.
    • College of Mathematics and Software Science, Sichuan Normal University, Chengdu 610066, China. fnjun@163.com
    • Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2006 Oct 1; 23 (5): 956-9.

    AbstractAn 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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