Table of Contents Author Guidelines Submit a Manuscript
Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 618743, 6 pages
http://dx.doi.org/10.1155/2013/618743
Research Article

Analyzing EEG of Quasi-Brain-Death Based on Dynamic Sample Entropy Measures

1East China University of Science and Technology, Meilong Road 130, Shanghai 200237, China
2Saitama Institute of Technology, 1690 Fusaiji, Fukaya-shi, Saitama 369-0293, Japan
3Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan

Received 22 August 2013; Revised 27 November 2013; Accepted 27 November 2013

Academic Editor: Jinde Cao

Copyright © 2013 Li Ni et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Z. Chen, J. Cao, Y. Cao et al., “An empirical EEG analysis in brain death diagnosis for adults,” Cognitive Neurodynamics, vol. 2, no. 3, pp. 257–271, 2008. View at Publisher · View at Google Scholar · View at Scopus
  2. J. Cao, “Analysis of the quasi-brain-death EEG data based on a robust ICA approach,” Cognitive Neurodynamics, vol. 4253, pp. 1240–1247, 2006. View at Google Scholar · View at Scopus
  3. Q. Shi, W. Zhou, J. Cao, T. Tanaka, and R. Wang, “Brain-computer interface system using approximate entropy and EMD techniques,” Cognitive Neurodynamics, vol. 6146, no. 2, pp. 204–212, 2010. View at Google Scholar
  4. K. Yang, J. Cao, R.-B. Wang, and H.-L. Zhu, “Analyzing EEG of quasi-brain-death based on dynamic approximate entropy measures,” Chinese Journal of Biomedical Engineering, vol. 30, no. 1, pp. 27–33, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. J. Cao and Z. Chen, “Advanced EEG signal processing in brain death diagnosis,” in Signal Processing Techniques for Knowledge Extraction and Information Fusion, pp. 275–297, Springer, 2008. View at Google Scholar
  6. L. Li, Y. Saito, D. Looney et al., “Data fusion via fission for the analysis of brain death,” in Evoving Intelligent Systems: Methodology and Applications, pp. 279–320, Springer, 2010. View at Google Scholar
  7. E. F. M. Wijdicks, “Brain death worldwide: accepted fact but no global consensus in diagnostic criteria,” Neurology, vol. 58, no. 1, pp. 20–25, 2002. View at Google Scholar · View at Scopus
  8. T. Zhang and K. Xu, “Multifractal analysis of intracranial EEG in epilepticus rats,” Lecture Notes in Computer Science, vol. 7062, no. 1, pp. 345–351, 2011. View at Google Scholar
  9. R. M. Taylor, “Reexamining the definition and criteria of death,” Seminars in Neurology, vol. 17, no. 3, pp. 265–270, 1997. View at Google Scholar · View at Scopus
  10. M. Hu and H. Liang, “Adaptive multiscale entropy analysis of multivariate neural data,” IEEE Transactions on Biomedical Engineering, vol. 59, no. 1, pp. 12–15, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. S. M. Pincus, “Approximate entropy as a measure of system complexity,” Proceedings of the National Academy of Sciences of the United States of America, vol. 88, no. 6, pp. 2297–2301, 1991. View at Google Scholar · View at Scopus
  12. J. S. Richman and J. R. Moorman, “Physiological time-series analysis using approximate and sample entropy,” American Journal of Physiology: Heart and Circulatory Physiology, vol. 278, no. 6, pp. H2039–H2049, 2000. View at Google Scholar · View at Scopus