Paper Info
Title
A Study of Sleep Stages Threshold Based on Multiscale Fuzzy Entropy.
Abstract
The classification of sleep stages based on EEG signals has become a prerequisite for monitoring sleep quality and diagnosing sleep-related diseases. Many researchers have conducted related research work. But, they often overlook the effect of the extracted characteristics on actual sleep staging results and the interpretation in psychology and clinical medicine. Therefore, this study calculates the value of multiscale fuzzy entropy as evaluation criteria and measures the threshold range of sleep stage based on CEEMDAN algorithm and psychophysics method. The experimental results show that the proposed method can effectively distinguish between different sleep stages by using fuzzy entropy as a measure of sleep staging thresholds. In addition, we designed a set of comparative experiments based on the single-channel EEG sample data and studied the gender factor on sleep stages by comparing sleep entropy thresholds of different genders. It was found that the sleep threshold of female was significantly greater than male.
Year
Venue
Field
2018
ICA3PP
Pattern recognition,Computer science,Fuzzy entropy,Artificial intelligence,Sleep quality,Psychophysics,Electroencephalography,Sleep Stages,Distributed computing
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
1
4
Name
Order
Citations
PageRank
Xuexiao Shao100.68
Bin Hu2778107.21
Yalin Li302.03
Xiangwei Zheng47420.88