Robust sleep stage classification with single-channel EEG signals using multimodal decomposition and HMM-based refinement

作者：

Highlights：

• Effective representative features for sleep stage classification via multimodal decomposition.

• A novel automatic and rule-free sleep stage refinement algorithm.

• Robust performance for data from various subjects or EEG channels.

• Superior performance compared to state-of-the-art works.

摘要

•Effective representative features for sleep stage classification via multimodal decomposition.•A novel automatic and rule-free sleep stage refinement algorithm.•Robust performance for data from various subjects or EEG channels.•Superior performance compared to state-of-the-art works.

论文关键词：Sleep stage classification,Multimodal decomposition,Rule-free refinement,Hidden Markov model

论文评审过程：Received 3 September 2018, Revised 6 December 2018, Accepted 16 December 2018, Available online 17 December 2018, Version of Record 20 December 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.023