面向载人航天的低负荷睡眠质量评估方法的研究  

Sleep Stages classification based on electrooculogram and electromyogram toward manned spaceflight

作　　者：李延军[1] 宫国强[1] 张煜[1] 尹增愿 单聪淼 Li Yanjun;Gong Guoqiang;Zhang Yu;Yin Zengyuan;Shan Congmiao(China Astronauts Research and Training Center,Beijing 100094,China)

机构地区：[1]中国航天员科研训练中心,北京100094

出　　处：《航天医学与医学工程》2024年第5期282-288,共7页Space Medicine & Medical Engineering

基　　金：中国载人航天工程。

摘　　要：目的探索一种不采集脑电信号的航天员在轨睡眠质量评估方法,从而简化卫生学处理并降低睡眠监测负荷。方法使用AASM标准的ISRUC-Sleep公开数据库,训练集(n=20)与测试集完全独立。测试集包括两个子集:睡眠障碍组(n=10)、健康组(n=10)。分类特征包括两路眼电不同频带的能量、均方根、相关系数、锁相值,以及一路肌电信号的分形维及均方根、肌电包络的均值、最大值、均方根。分别使用线性支持向量机、随机森林分类模型实施觉醒、快速眼动睡眠、浅睡、深睡四分类,将6路脑电、2路眼电与1路肌电的睡眠分期结果作为本算法精度的参照。结果使用眼电(44个特征)、肌电(6个特征)共50个归一化特征,随机森林、线性支持向量机对睡眠障碍组分类的kappa系数均为0.75;对健康组分类的kappa系数依次为0.73、0.70。作为参照,使用脑电(90个特征)、眼电(44个特征)、肌电(6个特征)共140个归一化特征,随机森林、线性支持向量机对睡眠障碍组分类的kappa系数依次为0.78、0.79;对健康组分类的kappa系数依次为0.74、0.76。结论基于2路眼电与1路肌电的睡眠分期精度比较接近金标准——含脑电监测的睡眠分期结果,可用于航天员在轨睡眠质量的评估。Objective In order to simplify the hygiene processing and reduce the load of sleep monitoring,a method of sleep quality assessment on orbit without EEG is explored.Methods Using the open database ISRUC-Sleep with AASM standard,the training set(n=20)and the test set(sleep disorder group(n=10)and health group(n=10))are completely independent.The electrooculogram(EOG)features include the energy,the root mean square,correlation coefficients and phase-locked values between different frequency bands of two-channel EOG.The electromyogram(EMG)features include fractal dimension,root mean square,the mean value,the maximum value and the root mean square of EMG envelope.Linear support vector machine(LSVM)and random forest(RF)were used to classify wakefulness,REM sleep,light sleep and deep sleep.The accuracy was compared with the results that derived from sixchannel electroencephalogram(EEG),two-channel EOG and one-channel EMG.Results Using 50 normalized features of EOG(44 features)and EMG(6 features),for sleep disorder group,kappa coefficients were both 0.75 by RF and by LSVM;for healthy group,the kappa coefficients were 0.73 by RF and 0.70 by LSVM.As a reference for AASM standard,using 140 normalized features of EEG(90 features),EOG(44 features)and EMG(6 features),for sleep disorder group,kappa coefficients were 0.78 by RF and 0.79 by LSVM;for healthy group,kappa coefficients were 0.74 by RF and 0.76 by LSVM.Conclusion The accuracy of sleep scoring from two-channel EOG and one-channel EMG is comparable with that of the gold standard,and can be applied to evaluate the sleep quality during manned spaceflight.

关 键 词：自动睡眠分类 睡眠分期 眼电 肌电 睡眠质量 载人航天 

分 类 号：G63[文化科学—教育学]