Descriptive statistical analysis based on patients’ EEG energy in coma and quasi-brain-death state

  • Yao Miao Saitama Institute of Technology, Fusaiji 1690, Fukaya, Saitama
  • Jianting Cao
Keywords: Descriptive statistical analysis, EEG energy, Brain death


In this paper, measure of descriptive statistical analysis based on EEG (electroencephalography)  energy was proposed to evaluate coma and quasi-brain-death patients’ EEG. Firstly, 36 cases of EEG (coma: 19; quasi-brain-death: 17) were analyzed. Specifically, 60s EEG data of each case were randomly selected and processed to get energy data by Dynamic 2T-EMD (turning tangent empirical mode decomposition), then energy data for 36 cases of EEG obtained were grouped and analyzed by using descriptive statistical analysis, and finally results were displayed by visual method. Results show significantly that energy for coma patients’ EEG is higher than that for quasi-brain-death patients’ EEG. And the EEG energy data set for quasi-brain-death is relatively more concentrate.


[1] Cao J.: “Analysis of the quasi-brain-death determination EEG data based on a robust ICA approach”. Lecture Notes of in Artificial Intelligence, Springer, pp. 1240-1247, 2006.
[2] Z. Chen, J. Cao, Y. Cao, et al.: “Qualitative evaluation and quantitative EEG analysis in brain death diagnosis for adults: An empirical study”, Cognitive Neurodynamics, Springer, Vol. 2, No. 3, pp. 257-271, 2008.
[3] N. Huang, Z. Shen, S. Long, M. Wu, H. Shih, Q. Zheng, N. Yen, C. Tung, and H. Liu: “The empirical mode decomposition and Hilbert spectrum for non-linear and non-stationary time series analysis”, Proceedings of the Royal Society of London, A 454, pp. 903-995, 1998.
[4] Q. Shi, J. Cao, T. Tanaka, R. Wang, and H. Zhu.: “EEG data analysis based on EMD for coma and quasi-brain-death patient”, Journal of Experimental and Theoretical Artificial Intelligence, Vol. 23, No. 1, pp. 97-110, 2011.
[5] Yao Miao, Dongsheng Wang, Gaochao Cui, Li Zhu and Jianting Cao: “Analyzing patients’ EEG energy for brain death determination based on Dynamic 2T-EMD”. International Journal of Computers & Technology. Vol. 16, pp. 717-720 (2017).
[6] Julien Fleureau, Jean-Claude Nunes, Amar Kachenoura, Laurent Albera, and Lotfi Senhadji: “Turning Tangent Empirical Mode Decomposition: A Framework for Mono- and Multivariate Signals”, IEEE Trans Signal Process, Vol. 59, No. 3, pp. 1309-1316, 2011.
[7] Cao J., Chen Z.: “Advanced EEG signal processing in brain death diagnosis”, In: Signal Processing Techniques for Knowledge Extraction and Information Fusion, Springer, pp. 275-298, 2008.
[8] Mann, Prem S.: Introductory Statistics (2nd ed.), Wiley, ISBN 0-471-31009-3, 1995.
How to Cite
Miao, Y., & Cao, J. (2018). Descriptive statistical analysis based on patients’ EEG energy in coma and quasi-brain-death state. INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 17(1), 7140-7145.