A study of sleep stage classification based on permutation entropy for electroencephalogram / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 869-872, 2009.
Article
Dans Chinois
| WPRIM
| ID: wpr-294551
ABSTRACT
This paper presents a new method for automatic sleep stage classification which is based on the EEG permutation entropy. The EEG permutation entropy has notable distinction in each stage of sleep and manifests the trend of regular transforming. So it can be used as features of sleep EEG in each stage. Nearest neighbor is employed as the pattern recognition method to classify the stages of sleep. Experiments are conducted on 750 sleep EEG samples and the mean identification rate can be up to 79.6%.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Physiologie
/
Phases du sommeil
/
Traitement du signal assisté par ordinateur
/
Reconnaissance automatique des formes
/
Classification
/
Entropie
/
Électroencéphalographie
/
Méthodes
Limites du sujet:
Humains
langue:
Chinois
Texte intégral:
Journal of Biomedical Engineering
Année:
2009
Type:
Article
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