摘要
睡眠过程中的脑电信号时间序列具有复杂的波动性特点,为了研究不同睡眠时期脑电信号的分形特征,运用多重分形去势波动分析的方法对5例受试者的整夜睡眠脑电信号进行了分析.计算结果表明,睡眠脑电序列具有长程相关性,而且是多重分形过程.不同的睡眠时期广义赫斯特指数不同,随时间尺度的增加而增大,变化趋势一致.醒期的脑电信号广义赫斯特指数最大,REM期介于睡眠一期和二期之间,其他各期随睡眠的加深逐渐增大.为睡眠脑电信号动力学机理的进一步研究提供了坚实的实证基础.
The time series of sleep electroencephalogram （EEG） has complicated undulatory property. To study the fractal characteristic at various sleep stages, one night sleep EEG signals collected from 5 subjects were analyzed by means of multifractal detrended fluctuation analysis （MF-DFA） method. The result shows that the sleep EEG series has the multifractal features as well as long range correlation. The values of generalized Hurst exponents vary at different sleep stages, but gradually increase in the same trends with the time scales expanding. The value of generalized Hurst exponents at wake stage reaches the maximum in one night sleep, and gradually increases with the deepening of sleep, while the value at REM stage is between that of stage 1 and stage 2. These results provide solid empirical base for further research of the dynamic mechanism of sleep EEG signal.
出处
《天津大学学报》
EI
CAS
CSCD
北大核心
2008年第10期1148-1151,共4页
Journal of Tianjin University(Science and Technology)
基金
天津市科技发展计划资助项目(043102111)
关键词
睡眠脑电
多重分形去势波动分析
长程相关
广义赫斯特指数
sleep electroencephalogram
multifractal detrended fluctuation analysis
long range correlation
generalized Hurst exponents
