Novel Method for Deriving Vectorcardiographic Leads Based on Artificial Neural Networks
نویسندگان
چکیده
Many methods for deriving vectorcardiographic (VCG) leads from 12-lead electrocardiogram (ECG) were published. All of them are based on a linear transformation. Differences are only in coefficients of transformation matrixes which are designed based on a model or on linear regression methods. This paper presents and assesses a new nonlinear transformation method based on artificial neural networks (ANNs) which offer better accuracy of the transformation. Derived VCG leads were compared with directly measured Frank leads for a group of 283 records from the PTB database. Methods based on ANNs achieve significantly lower MSE in all leads and significantly higher correlation coefficient in Z lead compared with both Kors and inverse Dower method.
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