摘要
我们利用不同睡眠期脑电复杂性特征与睡眠深度的关系及多道睡眠图功率谱特征,基于3层BP网络进行了睡眠自动分阶的研究,并提出了能部分反映睡眠质量的睡眠时间、浅睡时间、深睡时间、REM时间、觉睡比、醒转次数等参数。通过6例全睡眠监护实验说明,该方法可为睡眠质量的评价提供途径。
To estimate the sleep quality, a 3-layer BP neural network was studied. The EEG complexlty and the power spectrum of sleep-multigraph served as the input vector of the network . All-night sleep-stage scoring was performed. Then several parameters （sleep period, shallow sleep period, deep sleep perlod, REM period, ratio of the wakeful period and sleep one） were defined to estimate the sleep quality. The experiments revealed that the estimated sleep condition was the same as the subjects＇ impression. The data on six cases of all-night sleep show that this method is available to estimate the sleep quality.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2005年第6期1124-1127,共4页
Journal of Biomedical Engineering
基金
国家博士后科学基金资助项目(2003033515)
关键词
睡眠脑电图
复杂度
多导睡眠图
睡眠质量
Sleep electroencephalograph Complexity Sleep-multigraph Sleep quality
