Sleep Stage Detection
Human Sleep Staging into W-N1-N2-N3-REM classes from multiple or single polysomnography signals
Papers
Showing 1–10 of 34 papers
All datasetsSHHSSleep-EDFMASS SS3SHHS (single-channel)DODOSleep-EDFxSleep-EDFx (single-channel)DODHISRUC-SleepMASS (single-channel)MASS SS2Montreal Archive of Sleep Studies
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SynthSleepNet (EEG2+EOG2+EMG1) | Accuracy | 89.89 | — | Unverified |
| 2 | CoRe-Sleep (EEG-EOG) | Accuracy | 89.5 | — | Unverified |
| 3 | SynthSleepNet (EEG1+EOG1+EMG1) | Accuracy | 89.28 | — | Unverified |
| 4 | XSleepNet2 (EEG, EOG, EMG) | Accuracy | 89.1 | — | Unverified |
| 5 | MC2SleepNet 50% Masking (C4-A1 only) | Accuracy | 88.6 | — | Unverified |
| 6 | MC2SleepNet 15% Masking (C4-A1 only) | Accuracy | 88.5 | — | Unverified |
| 7 | SynthSleepNet (EEG1+EOG1) | Accuracy | 88.31 | — | Unverified |
| 8 | CoRe-Sleep (EEG) | Accuracy | 88.2 | — | Unverified |
| 9 | SleePyCo (C4-A1 only) | Accuracy | 87.9 | — | Unverified |
| 10 | NeuroNet (C4-A1 only) | Accuracy | 86.88 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SleePyCo (Fpz-Cz only) | Accuracy | 86.8 | — | Unverified |
| 2 | CatBoost | Accuracy | 86.6 | — | Unverified |
| 3 | XSleepNet (EEG, EOG) | Accuracy | 86.4 | — | Unverified |
| 4 | Linear model | Accuracy | 86.3 | — | Unverified |
| 5 | IITNet CRNN (Fpz-Cz only) | Accuracy | 84 | — | Unverified |
| 6 | DeepSleepNet | Accuracy | 82 | — | Unverified |
| 7 | Multitask 1-max CNN | Accuracy | 81.9 | — | Unverified |
| 8 | Deep CNN with transfer-learning | Accuracy | 81.3 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Deep Sleep Net | Accuracy | 89.1 | — | Unverified |
| 2 | Simple Sleep Net | Accuracy | 88.8 | — | Unverified |
| 3 | CatBoost | Accuracy | 86.7 | — | Unverified |
| 4 | DeepSleepNet | Accuracy | 86.2 | — | Unverified |
| 5 | Linear model | Accuracy | 85.3 | — | Unverified |
| 6 | SPDTransNet | Macro-F1 | 0.81 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MC2SleepNet 50% Masking (C4-A1 only) | Accuracy | 88.6 | — | Unverified |
| 2 | MC2SleepNet 15% Masking (C4-A1 only) | Accuracy | 88.5 | — | Unverified |
| 3 | SleePyCo (C4-A1 only) | Accuracy | 87.9 | — | Unverified |
| 4 | XSleepNet (C4-A1 only) | Accuracy | 87.7 | — | Unverified |
| 5 | NeuroNet (C4-A1 only) | Accuracy | 86.88 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SimpleSleepNet | Accuracy | 88.7 | — | Unverified |
| 2 | DeepSleepNet | Accuracy | 87.5 | — | Unverified |
| 3 | SeqSleepNet | Accuracy | 85.5 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | NeuroNet (Fpz-Cz only) | Accuracy | 85.24 | — | Unverified |
| 2 | SleePyCo (Fpz-Cz only) | Accuracy | 84.6 | — | Unverified |
| 3 | XSleepNet (EEG, EOG) | Accuracy | 84 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | NeuroNet (Fpz-Cz only) | Accuracy | 85.24 | — | Unverified |
| 2 | SleePyCo (Fpz-Cz only) | Accuracy | 84.6 | — | Unverified |
| 3 | XSleepNet (Fpz-Cz only) | Accuracy | 84 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SimpleSleepNet | Accuracy | 89.9 | — | Unverified |
| 2 | DeepSleepNet | Accuracy | 89.6 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SLEEPER-DT | Accuracy | 78.5 | — | Unverified |
| 2 | NeuroNet (C4-A1 only) | Accuracy | 77.05 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SleePyCo (C4-A1 only) | Accuracy | 86.8 | — | Unverified |
| 2 | XSleepNet (C4-A1 only) | Accuracy | 85.2 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | IITNet (F4-EOG [Left] only) | Accuracy | 84.5 | — | Unverified |
| 2 | Multitask 1-max CNN | Accuracy | 78.6 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SleePyCo (C4-A1 only) | Accuracy | 86.8 | — | Unverified |
| 2 | U-time EEG only (4 classes) | Accuracy | 85 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | XSleepNet (EEG, EOG, EMG) | Accuracy | 81.1 | — | Unverified |
| 2 | SleePyCo (C3-A2 only) | Accuracy | 80.9 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SleePyCo (C3-A2 only) | Accuracy | 80.9 | — | Unverified |
| 2 | XSleepNet (C3-A2 only) | Accuracy | 80.3 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SleePyCo (Fpz-Cz only) | Accuracy | 86.8 | — | Unverified |
| 2 | IITNet (Fpz-Cz only) | Accuracy | 83.9 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | NeuroNet (C4-A1 only) | Accuracy | 77.05 | — | Unverified |