TWNSleepNet: An Automatic Sleep Staging Model Based on Causal Expansion Convolutional and Residual Networks
Author:
Affiliation:
1. Chengdu University of Information Technology,School of Computer Science,Chengdu,China
2. University of Electronic Science and Technology of China,School of Life Science and Technology,Chengdu,China
Funder
Chengdu University
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10206048/10206041/10206186.pdf?arnumber=10206186
Reference13 articles.
1. Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders
2. DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG
3. SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach
4. Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG
5. A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects.
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