OpenCodePapers

sleep-stage-detection-on-shhs

Physiological Signal AnalysisSleep Stage Detection

Results over time

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Leaderboard

Paper	Code	Accuracy	Cohen's Kappa	Macro-F1	ModelName	ReleaseDate
Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework	✓ Link	89.89%	0.860	0.845	SynthSleepNet (EEG2+EOG2+EMG1)	2025-02-18
CoRe-Sleep: A Multimodal Fusion Framework for Time Series Robust to Imperfect Modalities		89.5%	0.853	0.823	CoRe-Sleep (EEG-EOG)	2023-03-27
Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework	✓ Link	89.28%	0.850	0.835	SynthSleepNet (EEG1+EOG1+EMG1)	2025-02-18
		89.1%	0.847	0.823	XSleepNet2 (EEG, EOG, EMG)
MC2SleepNet: Multi-modal Cross-masking with Contrastive Learning for Sleep Stage Classification	✓ Link	88.6%	0.841	0.821	MC2SleepNet 50% Masking (C4-A1 only)	2025-02-13
MC2SleepNet: Multi-modal Cross-masking with Contrastive Learning for Sleep Stage Classification	✓ Link	88.5%	0.840	0.823	MC2SleepNet 15% Masking (C4-A1 only)	2025-02-13
Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework	✓ Link	88.31%	0.840	0.820	SynthSleepNet (EEG1+EOG1)	2025-02-18
		88.2%	0.834	0.808	CoRe-Sleep (EEG)
		87.9%	0.830	0.807	SleePyCo (C4-A1 only)
NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG	✓ Link	86.88%		0.812	NeuroNet (C4-A1 only)	2024-04-10