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
in Chinese
| 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%.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Physiology
/
Sleep Stages
/
Signal Processing, Computer-Assisted
/
Pattern Recognition, Automated
/
Classification
/
Entropy
/
Electroencephalography
/
Methods
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2009
Type:
Article
Similar
MEDLINE
...
LILACS
LIS