Scalogram based prediction model for respiratory disorders using optimized convolutional neural networks

作者：

Highlights：

• TF representation analysis using EMD for normal, crackles,wheezes and rhonchi types of respiratory sounds is proposed.

• Classification of IMF based scalogram images using Alexnet Convolutional Neural Network(CNN) architecture is carried out.

• Enhancement in accuracy compared to existing wavelet approach is achieved.

• Comparison with different optimization algorithms is examined.

摘要

•TF representation analysis using EMD for normal, crackles,wheezes and rhonchi types of respiratory sounds is proposed.•Classification of IMF based scalogram images using Alexnet Convolutional Neural Network(CNN) architecture is carried out.•Enhancement in accuracy compared to existing wavelet approach is achieved.•Comparison with different optimization algorithms is examined.

论文关键词：Lung sounds,Scalogram,Empirical mode decomposition,Convolutional neural networks,Deep spectrum features,Optimizers

论文评审过程：Received 23 June 2019, Revised 16 January 2020, Accepted 17 January 2020, Available online 20 January 2020, Version of Record 2 February 2020.

论文官网地址：https://doi.org/10.1016/j.artmed.2020.101809