A Heart Sound Classification Method Based on Residual Block and Attention Mechanism

The automatic diagnosis of heart sounds is particularly important for cardiologists. However, the existing diagnostic methods still have a large space to be improved, In this paper, we proposed a novel method for heart sound classification. Our method consists of two stages. In the first stage, we preprocessed the heart sound signal, including two steps of denoising and downsampling, to reduce the noise and decrease the complexity of processing. In the second stage, we classify the processed signal, including framing and input network, and finally output three types of results. Our method was validated on the CirCor DigiScope Phonocardiogram Dataset. The result shows the F1 score reached 0.922 and is better compared to other networks’ results.