Fig. 1From: A hybrid self-attention deep learning framework for multivariate sleep stage classificationMain architecture of the HybridAtt model. The goal of HybridAtt is to capture dual correlations of PSG channels and timestamps by calculating the dependencies of their multi-view convolutional representations, in order to improve the performance of sleep stage classification using multivariate PSG recordsBack to article page