摘要
睡眠质量关系着身体健康与和工作效率,睡眠分期结果是衡量睡眠质量的重要指标和诊治睡眠障碍性疾病的重要途径。本文采用基于去趋势互相关分析(DCCA)的方法,从MIT-BIH Polysomnographic Database中随机抽取了样本信号,来进行清醒期和非快速眼动(NREM)睡眠Ⅰ期的分期研究。结果表明,清醒期的DCCA指数的平均值小于NREM睡眠Ⅰ期的DCCA指数的平均值。此方法研究睡眠脑电图,对改善睡眠质量或者诊治睡眠障碍性疾病有很大的意义。
The quality of sleep has a great relationship with health and working efficiency. The result of sleep stage classification is an important indicator to measure the quality of sleep, and it is also an important way to diagnose and treat sleep disorders. In this paper, the method of detrended cross correlation analysis （DCCA） was used to analyze sleep stage classification, sleep electroencephalograph signals, which were extracted from the MIT-BIH Polysomnographic Database randomly. The results showed that the average DCCA exponent of the awake period is smaller than that of the first stage of non-rapid eye movement （NREM） sleeps. It is well concluded that the method of studying the sleep electroencephalograph with this method is of great significance to improve the quality of sleep, to diagnose and to treat sleep disorders.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2014年第1期44-47,共4页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(61271082
61201029
61102094)
江苏省自然科学基金资助项目(BK2011759
BK2011565)
关键词
睡眠脑电
睡眠分期
去趋势互相关分析
sleep electroencephalograph
sleep stages
detrended cross correlation analysis
