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Dynamic MEMD Associated with Approximate Entropy in Patients’ Consciousness Evaluation

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Neural Information Processing (ICONIP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9947))

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Abstract

Electroencephalography (EEG) based preliminary examination has been widely used in diagnosis of brain diseases. Based on previous studies, clinical brain death determination also can be actualized by analyzing EEG signal of patients. Dynamic Multivariate empirical mode decomposition (D-MEMD) and approximate entropy (ApEn) are two kinds of methods to analyze brain activity status of the patients in different perspectives for brain death determination. In our previous studies, D-MEMD and ApEn methods were always used severally and it cannot analyzing the patients’ brain activity entirety. In this paper, we present a combine analysis method based on D-MEMD and ApEn methods to determine patients’ brain activity level. Moreover, We will analysis three different status EEG data of subjects in normal awake, comatose patients and brain death. The analyzed results illustrate the effectiveness and reliability of the proposed methods.

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Authors and Affiliations

  1. Saitama Institute of Technology, Fusaiji 1690, Fukaya, Saitama, 3690293, Japan

    Gaochao Cui, Qibin Zhao & Jianting Cao

  2. Brain Science Institute, RIKEN, Hirosawa 2-1, Wakoshi, Saitama, 3510198, Japan

    Gaochao Cui, Qibin Zhao, Jianting Cao & Andrzej Cichocki

  3. Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei-shi, Tokyo, 184-8588, Japan

    Toshihisa Tanaka

Authors
  1. Gaochao Cui
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  2. Qibin Zhao
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  3. Toshihisa Tanaka
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  4. Jianting Cao
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  5. Andrzej Cichocki
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Corresponding author

Correspondence to Gaochao Cui .

Editor information

Editors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Akira Hirose

  2. Kobe University, Kobe, Japan

    Seiichi Ozawa

  3. Okinawa Institute of Science and Technology Graduate University, Onna, Japan

    Kenji Doya

  4. Nara Institute of Science and Technology, Ikoma, Japan

    Kazushi Ikeda

  5. Kyungpook National University, Daegu, Korea (Republic of)

    Minho Lee

  6. Chinese Academy of Sciences, Beijing, China

    Derong Liu

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Cui, G., Zhao, Q., Tanaka, T., Cao, J., Cichocki, A. (2016). Dynamic MEMD Associated with Approximate Entropy in Patients’ Consciousness Evaluation. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9947. Springer, Cham. https://doi.org/10.1007/978-3-319-46687-3_15

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  • DOI: https://doi.org/10.1007/978-3-319-46687-3_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46686-6

  • Online ISBN: 978-3-319-46687-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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