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복합 신경회로망 및 규칙 기반 전문가 추론을 이용한 수면 단계설정의 자동화

Other Titles
 Automatic sleep stage scoring using hybrid neural network and rule-based expert reasoning 
Authors
 박해정  ;  박광석  ;  정도언 
Citation
 Journal of Korean Society of Medical Informatics (대한의료정보학회지), Vol.6(1) : 79-86, 2000 
Journal Title
 Journal of Korean Society of Medical Informatics (대한의료정보학회지) 
ISSN
 1225-8903 
Issue Date
2000
MeSH
Classification ; Electroencephalography ; Electrooculography ; Expert Systems ; Humans ; Intelligence ; Sleep Stages*
Keywords
Sleep scoring ; Rule-Based Reasong ; Neural Network
Abstract
In order to increase the performance of automatic sleep stage scoring, we propose a hybrid neural-network and rule-based expert system taking advantages of each system. The suggesting hybrid system comprises signal cleaning. feature extraction, event detection, rule-based sleep scoring and neural network classification. We selected segment based EEG features. the state of EOG. and EMG tone as a major feature set. With the extracted features, the rule-based expert system classities the sleep stages by symbolic reasoning. The scoring process of rule-based expert system comprises the single epoch reasoning based on the typical events and the multi-epoch adjusting when no events are detected. If the decision of rule-based expert system is uncertain, then these features are fed into the neural network. We used a two hidden layer feed forward network using error hack propagation algorithm. The agreement rate between human scorer and automatic algorithm were evaluated. The neural network supplements the shortcomings of rule-based system by dealing with exceptions of rules. The result shows that the compuational ol computational and symbolic intelligence is promising approach sleep signal anal) sis.
DOI
10.4258/jksmi.2000.6.1.79
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실) > 1. Journal Papers
Yonsei Authors
Park, Hae Jeong(박해정) ORCID logo https://orcid.org/0000-0002-4633-0756
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/172286
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