Identification and Diagnosis of Cardiovascular Diseases Using A Backpropagation Neural Network Combined With A Weight Tuning Using Logistic Regression

Volume 20 No 13 (2022)

Pravin B Desai, Dr Yuvraj K Kanse, Dr Chandrashekhar, Mahesh B Neelagar

DOI: 10.14704/nq.2022.20.13.NQ88110

Abstract

A typical obstacle in obtaining high-accuracy arrhythmia classification models using artificial neural networks is a lack of adequate training samples of various ECG signals. To address this issue, this study proposes a unique technique based on a feed forward back propagation neural network with a weight updation coefficient based on logistic regression. The results reveal that the weight adaptation technique improves the performance of all classification networks. The suggested approach is useful in classifying various arrhythmias.

Keywords

Artificial Neural Network, ANN, ECG, Arrhythmia, Electrocardiography, Discrete Wavelet Transform

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