Analysis and classification of brain network based on sub-period apnea and sleep stage
ZHAO Jinzhao
LIU Ming
JIANG Xiuquan
SHI Weiyou
LOU Yitai
LENG Jiancai
XU Fangzhou
FENG Chao
YANG Qingbo
TANG Jiyou
LU Shanshan
Abstract：Sleep staging is the basic evaluation of sleep quality.However,sleep apnea(SA)changes the sleep structure of testers,which affects the accurate evaluation of sleep stages.therefore,the accurate detection of SA and sleep stages is very important in the e-valuation of sleep quality.In order to accurately assess sleep stages,we discussed the interaction of functional connections between brain regions by studying the functional connections between brain regions.Using the phase-locked value(PLV)to extract features in sub-periods,and a functional connection network was constructed.Then,the PLV of multiple sub-periods was used for feature fusion,and the classification performance optimization strategy was used for sleep staging.At the same time,the brain network changes of SA and normal breathing were analyzed.The experimental results showed that when the number of sub-periods was 30,the classification result of sleep stage reached 88.87%,and the accuracy of detecting apnea reached 93.7%.The algorithm has good sleep classification and apnea detection performance,and can effectively promote the development and application of EEG sleep classification and apnea detection system.
Keywords：ElectroencephalographySleep stageClassificationBrain functional connectivityPhase-locked valueSleep apnea
Publication Date：2024-02-28
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：6( 40-45 )