Published on in Vol 25 (2023)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/40211, first published
.
![Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study](https://asset.jmir.pub/assets/25a6044273d53c092c753b71410f7a35.png 480w,https://asset.jmir.pub/assets/25a6044273d53c092c753b71410f7a35.png 960w,https://asset.jmir.pub/assets/25a6044273d53c092c753b71410f7a35.png 1920w,https://asset.jmir.pub/assets/25a6044273d53c092c753b71410f7a35.png 2500w)
Journals
- Jiang X, Ren Y, Wu H, Li Y, Liu F. Convolutional neural network based on photoplethysmography signals for sleep apnea syndrome detection. Frontiers in Neuroscience 2023;17 View
- Zhang X, Zhang X, Huang Q, Lv Y, Chen F. A review of automated sleep stage based on EEG signals. Biocybernetics and Biomedical Engineering 2024 View