Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/90508
標題: Characterizing sleep stages by fractal analysis on electroencephalograph
用碎形分析腦波來判別睡眠狀態
作者: Cheng-Shun Hung
洪證順
關鍵字: 
no
引用: [1] A. Rechtschaffen and A. Kales, A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects, U.S. Department of Health, National Institutes of Health Publication No. 204 (1968). [2] M. Schwaibold, R. Harms, B. Scholler, I. Pinnow, W. Cassel, T. Penzel, H. F. Becker, and A. Bolz, Knowledge-Based Automatic Sleep-Stage Recognition – Reduction in the Interpretation Variability, Somnologie 7: 59-65 (2003). [3] H. Preißl, W. Lutzenberger, F. Pulvermüller, and N. Birbaumer, Fractal dimensions of short EEG time series in humans, Neuroscience 225, 77-80 (1997). [4] J.Z. Liu, Q. Yang, B. Yao, R.W. Brown, and G.H. Yue, Linear correlation between fractal dimension of EEG signal and handgrip force, Biologic Cyberne 93, 131-140 (2005). [5] S. Georgiev, Z. Minchev, C. Christova, and D. Philipova, EEG Fractal dimension measurement before and after human auditory stimulation, BIO automation 12, 70-81 (2009). [6] http://www.physionet.org/ [7] S.-S. Liaw and F.-Y. Chiu, Fractal dimensions of time sequences, Physica A388, 3100 (2009). [8] S.-S. Liaw, F.-Y. Chiu, C.-Y. Wang, and Y.-H. Shiau, Fractal analysis of stock index and electrocardiograph, Chinese Journal of Physics 48, 814 (2010).
摘要: 人在睡眠時,腦部會經歷幾個不同的睡眠狀態。我們蒐集睡眠腦波,利用碎形分析法(mIRMD 法)進行分析,找出各個睡眠狀態的碎形維度特徵。我們計算 4~14Hz 區間的碎形維度 D,發現睡眠狀態的維度值有 DR (快速動眼期)>DL (淺眠期)>DD (深眠期)的關係。之後分析 14~32Hz 區間,發現狀態 R 的碎形維度,在 4~14Hz 區間會大於 14~32Hz 區間。根據這幾個發現,我們做了一套判斷睡眠狀態的方法,其正確率目前可達約 80%。
In sleep, the brain goes through several different sleep stages. To investigate the fractal dimension in each sleep stage, we analyze sleep EEG by the modified Inverse Random Midpoint Displacement (mIRMD) method. We calculate fractal dimensions of different sleep stages in frequency range of 4~14Hz, and find that they have largest values in REM stage, median in light sleep, and smallest in deep sleep. We also find that, in REM stage, the fractal dimension in 4~14Hz is larger than that in 14~32Hz. With these findings, we can determine sleep stages simply based on the fractal dimensions of sleep EEG with 80% accuracy when results are compared to those determined by the standard R&K criteria.
URI: http://hdl.handle.net/11455/90508
文章公開時間: 2015-07-16
Appears in Collections:物理學系所

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