教授 博士生导师 硕士生导师
性别: 男
毕业院校: 大连理工大学
学位: 博士
所在单位: 生物医学工程学院
学科: 信号与信息处理. 生物医学工程
办公地点: 大连理工大学创新园大厦
联系方式: 电子邮箱:qiutsh@dlut.edu.cn; 电话:15898159801
电子邮箱: qiutsh@dlut.edu.cn
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论文类型: 期刊论文
发表时间: 2012-04-01
发表刊物: INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
收录刊物: SCIE、EI
卷号: 22
期号: 4
ISSN号: 0218-1274
关键字: Electroencephalogram (EEG); sleep stages; multifractional process; Hurst parameter; local Holder exponent
摘要: Electroencephalogram (EEG), the measures and records of the electrical activity of the brain, exhibits evidently nonlinear, nonstationary, chaotic and complex dynamic properties. Based on these properties, many nonlinear dynamical analysis techniques have emerged, and much valuable information has been extracted from complex EEG signals using these nonlinear analysis techniques. Among these techniques, the Hurst exponent estimation was widely used to characterize the fractional or scaling property of the EEG signals. However, the constant Hurst exponent H cannot capture the detailed information of dynamic EEG signals. In this research, the multifractional property of the normal human sleep EEG signals is investigated and characterized using local Holder exponent H(t). The comparison of the analysis results for human sleep EEG signals in different stages using constant Hurst exponent H and the local Holder exponent H(t) are summarized with tables and figures in the paper. The results of the analysis show that local Holder exponent provides a novel and valid tool for dynamic assessment of brain activities in different sleep stages.