Sleep Staging From the EEG Signal Using Multifractal Detrended Fluctuation Analysis

摘要：

　　The quality of sleep is closely related to human health.Accurate monitoring of sleep quality can play an effective supervisory role in helping people improve the quality of sleep.The analysis of the electroencephalogram (EEG) can yield much useful information about sleep stage.In the present study,the MF-DFA algorithm was applied to stage the different sleep states.The two key parameters in MF-DFA algorithm the segmented length s and the order q of fluctuation function were determined by the sleep EEG data in MIT-BIH polysomnography database,and verified by the experiment.The results demonstrated that the h(q) with q=0,1,2 and s=10~100 can distinguish the wake,shallow sleep and deep sleep states in MIT-BIH database accurately,and can reflect the process of sleep state better.

关键词： sleep DFA MF-DAF fluctuation function

作者: Zhiyong Liu Jinwei Sun

作者单位: School of Electrical Engineering and Automatic Harbin Institute of Technology Harbin, China

会议类型: 国际会议

会议名称: 2015 Fifth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2015)(第五届仪器测量、计算机通信与控制国际会议)

会议地点: 秦皇岛

会议语种:英文

页码: 63-68

在线出版日期: 2015-09-18（万方平台首次上网日期，不代表论文的发表时间）