MC2SleepNet: Multi-modal Cross-masking with Contrastive Learning for Sleep Stage Classification

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Benchmark	Model	Rank	Results
sleep-stage-detection-on-shhs	MC2SleepNet 50% Masking (C4-A1 only)	#3	Accuracy: 88.6%Cohen's Kappa: 0.841Macro-F1: 0.821
sleep-stage-detection-on-shhs	MC2SleepNet 15% Masking (C4-A1 only)	#4	Accuracy: 88.5%Cohen's Kappa: 0.840Macro-F1: 0.823
sleep-stage-detection-on-shhs-single-channel	MC2SleepNet 50% Masking (C4-A1 only)	#1	Accuracy: 88.6%Cohen's Kappa: 0.841Macro-F1: 0.821
sleep-stage-detection-on-shhs-single-channel	MC2SleepNet 15% Masking (C4-A1 only)	#2	Accuracy: 88.5%Cohen's Kappa: 0.840Macro-F1: 0.823