5 months ago

DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal

Abstract

pytorch

Mentioned in GitHub

Benchmark	Methodology	Metrics
k-complex-detection-on-mass-ss2	DOSED	F1-score (@IoU = 0.3): 0.6
sleep-apnea-detection-on-dreem_nct03657329	DOSED	Accuracy: 81% F1-score (@IoU = 0.3): 0.57 ± 0.23 Mean AHI Error: 4.69 ± 4.25
sleep-arousal-detection-on-mesa	DOSED (3 EEG + 2 EOG)	F1-score (@IoU = 0.3): 0.71
sleep-arousal-detection-on-mesa	DOSED (1 EEG)	F1-score (@IoU = 0.3): 0.61
spindle-detection-on-mass-ss2	DOSED	F1-score (@IoU = 0.3): 0.75
spindle-detection-on-stanford-sleep-cohort	DOSED	F1-score (@IoU = 0.3): 0.48
spindle-detection-on-wisconsin-sleep-cohort	DOSED	F1-score (@IoU = 0.3): 0.46

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