A single-channel EEG based automatic sleep stage classification method leveraging deep one-dimensional convolutional neural network and hidden Markov model

• Published in: Biomedical signal processing and control Vol. 68; p. 102581
• Main Authors: Yang, Bufang, Zhu, Xilin, Liu, Yitian, Liu, Hongxing
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2021
• Subjects: Convolutional neural network; Electroencephalogram; Hidden Markov model; Sleep stage classification; Subject-independent testing; Subject-independent testing; Hidden Markov model; Sleep stage classification; Electroencephalogram; Convolutional neural network

•Our proposed 1D-CNN-HMM model combines 1D-CNN and HMM. 1D-CNN could extract features from raw EEG to perform epoch-wise classification, and HMM works as post-processing step to correct unreasonable sleep stage transitions.•We have demonstrated that HMM refinement is effective for 1D-CNN, and HMM im...