• DocumentCode
    683776
  • Title

    Complexity analysis of electroencephalogram signal based on Jensen-Shannon divergence

  • Author

    Lingjun Gong ; Jun Wang

  • Author_Institution
    Coll. of Telecomm & Inf. Eng, Nanjing Univ. of Posts & Telecomm, Nanjing, China
  • fYear
    2013
  • fDate
    16-18 Dec. 2013
  • Firstpage
    219
  • Lastpage
    223
  • Abstract
    In this paper, complexity measure based on Jensen-Shannon Divergence was used to compute statistical complexity of the electroencephalogram signals, which include the electroencephalogram of younger and elder subjects from Nanjing General Hospital of Nanjing Military Command. The results show that two groups of signals have different statistical complexity measures. The electroencephalogram of elder subjects has the higher statistical complexity. The independent samples T test indicated that above-mentioned analysis could disclose significant differences among these two signals´ complexity. It is demonstrated that statistical complexity based on Jensen-Shannon Divergence could effectively distinguish the electroencephalogram in 2 various age groups.
  • Keywords
    computational complexity; electroencephalography; medical signal processing; statistical analysis; Jensen-Shannon divergence; Nanjing General Hospital; Nanjing Military Command; complexity analysis; electroencephalogram signals; independent sample T test; signal complexity; signal groups; statistical complexity measures; Algorithm design and analysis; Complexity theory; Dynamic range; Electroencephalography; Probability distribution; Standards; Jensen-Shannon Divergence; complexity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2013 6th International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-2760-9
  • Type

    conf

  • DOI
    10.1109/BMEI.2013.6746937
  • Filename
    6746937