Automated sleep stage scoring using hybrid rule- and case-based reasoning.
We propose an automated method for sleep stage scoring using hybrid rule- and case-based reasoning. The system first performs rule-based sleep stage scoring, according to the Rechtschaffen and Kale's sleep-scoring rule (1968), and then supplements the scoring with case-based reasoning. This method comprises signal processing unit, rule-based scoring unit, and case-based scoring unit. We applied this methodology to three recordings of normal sleep and three recordings of obstructive sleep apnea (OSA). Average agreement rate in normal recordings was 87.5% and case-based scoring enhanced the agreement rate by 5.6%. This architecture showed several advantages over the other analytical approaches in sleep scoring: high performance on sleep disordered recordings, the explanation facility, and the learning ability. The results suggest that combination of rule-based reasoning and case-based reasoning is promising for an automated sleep scoring and it is also considered to be a good model of the cognitive scoring process.
Park
H J
HJ
Interdisciplinary Program of Medical and Biological Engineering Major, College of Medicine, Seoul National University, Korea.
Oh
J S
JS
Jeong
D U
DU
Park
K S
KS
D003201:Computers; D006801:Humans; D017286:Polysomnography / Q000706:statistics & numerical data*; D012016:Reference Values; D012815:Signal Processing, Computer-Assisted; D020181:Sleep Apnea, Obstructive / Q000503:physiopathology; D012894:Sleep Stages / Q000502:physiology*