Sleep Staging on Sleep-EDF-SC EEG
78.8Macro F1Sleep Transformer
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Sleep TransformerYear=2022, Technique=transformer, LP=FT, Signals=EEG2022.07 | 78.8 | 84.9 | 0.789 | |
| XSleepnet2Year=2021, Technique=CNN & RNN, LP=LFS, Signals=EEG + EOG2022.07 | 78.7 | 84 | 0.778 | |
| XSleepnet1Year=2020, Technique=CNN & RNN, LP=LFS, Signals=EEG2022.07 | 78.4 | 84 | 0.777 | |
| TinySleepNetYear=2020, Technique=CNN & RNN, LP=LFS, Signals=EEG2022.07 | 78.1 | 83.1 | 0.77 | |
| RobustSleepNetYear=2021, Technique=RNN, LP=FT, Signals=EEG + EOG2022.07 | 77.9 | — | — | |
| IITNetTransfer learning=No2019.07 | 77.7 | 84 | 0.78 | |
| Classical ML PipelineYear=2022, Technique=Catboost, LP=LFS, Signals=EEG + EOG + EMG2022.07 | 77.5 | 83.1 | 0.766 | |
| Classical ML PipelineYear=2022, Technique=Catboost, LP=LFS, Signals=EEG + EOG2022.07 | 77.2 | 83 | 0.763 | |
| Classical ML PipelineYear=2022, Technique=Logistic regr., LP=LFS, Signals=EEG + EOG + EMG2022.07 | 77.1 | 82.1 | 0.756 | |
| DeepSleepNetTransfer learning=No2019.07 | 76.9 | 82 | 0.76 | |
| Classical ML PipelineYear=2022, Technique=Logistic regr., LP=LFS, Signals=EEG + EOG2022.07 | 76.8 | 82 | 0.753 | |
| RobustSleepNetYear=2021, Technique=RNN, LP=LFS, Signals=EEG + EOG2022.07 | 76.3 | — | — | |
| DeepSleepNet-LiteYear=2021, Technique=CNN, LP=LFS, Signals=EEG2022.07 | 75.2 | 80.3 | 0.73 | |
| SeqSleepNet+Transfer learning=Finetuning2019.07 | 75.1 | 81.7 | 0.737 | |
| Sleep TransformerYear=2022, Technique=transformer, LP=LFS, Signals=EEG2022.07 | 74.3 | 81.4 | 0.743 | |
| RobustSleepNetYear=2021, Technique=RNN, LP=DT, Signals=EEG + EOG2022.07 | 73.8 | — | — | |
| SleepEEGNetYear=2019, Technique=CNN & RNN, LP=LFS, Signals=EEG2022.07 | 73.6 | 80 | 0.73 | |
| DeepSleepNet+Transfer learning=Finetuning2019.07 | 73.4 | 79.8 | 0.713 | |
| Decision treesTransfer learning=No2019.07 | — | 93.1 | — |