Sleep Electroencephalogram Analysis Based on Symbolic Transfer Entropy

Rui Jun Chang; Yang Liu; Qiu Ping Chen; Jun Wang

doi:10.4028/www.scientific.net/AMR.765-767.2678

Paper Titles

Optimal Spectrum Sensing Interval to Minimize the Transmission Delay for Cognitive Radio
p.2657

Detrended Cross-Correlation Analysis of Epilepsy Electroencephalagram Signals
p.2664

Comprehensive Spectral Analysis of HRV during Sleep and their Application in Sleep Staging
p.2668

Research and Simulation of Ultra Wideband Based on Rake Receiver
p.2673

Sleep Electroencephalogram Analysis Based on Symbolic Transfer Entropy
p.2678

Policy on Downlink Access of Femtocell Based on OFDMA in Dense Employment Residential Environment
p.2682

Galileo E5 Signal Acquisition and Tracking Based on a Wide-Band Customized Universal Peripheral N210 Platform
p.2686

Performance Analysis of 10Gbps Optical Communication System by Simulation
p.2691

An Effective Scheme of M-Ary Spread Spectrum System Based on Orthogonal Spread Spectrum and CPSK
p.2696

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 765-767Sleep Electroencephalogram Analysis Based on...

Sleep Electroencephalogram Analysis Based on Symbolic Transfer Entropy

Abstract:

The quality of sleep has a great relationship with health. The result of sleep stage classification is an important indicator to measure the quality of sleep. It was found that the symbolic transfer entropy about wake and the first stage of non-rapid eye movement sleep reflect on the changes of sleep stage. And it was confirmed by T test and multi-samples experiments. The symbolic transfer entropy can apply into automatic sleep stage classification. By Multi-parameter analysis it could achieve a higher accuracy of sleep stage classification.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 765-767)

Pages:

2678-2681

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.765-767.2678

Citation:

Cite this paper

Online since:

September 2013

Authors:

Rui Jun Chang, Yang Liu, Qiu Ping Chen, Jun Wang

Keywords:

EEG, Sleep Stage Classification, Symbolic Transfer Entropy

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Q.F. Meng, W.D. Zhou, Y.H. Chen, Y.H. Peng, The feature extraction of epileptic EEG signals based on nonlinear prediction, acta phys. sin. 59 (2010), 123-130. （in Chinese）.

Google Scholar

[2] L.L. Zhao, Z.Q. Liang, W.Q. Wu, G.S. Hu, Changes of EEG Correlation Dimensions in Epilepsy after Biofeedback Training, Chin. J. Biomed. Eng. 29 (2010), 71-76, 85. （in Chinese）.

Google Scholar

[3] Q.L. Ma, C.H. Bian, J. Wang, Scaling analysis on electroencephalagram and its application to sleep-staging, 59 (2010) 4480-4484. （in Chinese）.

Google Scholar

[4] T. Schreiber, Measuring information transfer, Phys. Rev. Lett. 85 (2000) 461-464.

Google Scholar

[5] M. Staniek, K. Lehnertz, Symbolic transfer entropy, Phys. Rev. Lett. 100 (2008), 158101.

DOI: 10.1103/physrevlett.100.158101

Google Scholar

[6] E. Roldan, M.R.J. Parrondo, Estimating dissipation from single stationary trajectories, Phys. Rev. Lett. 105 (2010), 150607.

DOI: 10.1103/physrevlett.105.150607

Google Scholar