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Biomarker Development on Alcohol Addiction Using EEG

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Neural Information Processing (ICONIP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8226))

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Abstract

Alcohol addiction is harmful to society, economy and personal health. Alcohol addiction treatments intend to help addicted individuals reduce and stop compulsive alcohol use. Using biomarker, the clinicians could determine if drugs are having a desirable effect much earlier and given in correct dose for treatment. This paper will provide an up-to-date review of the state of the art in biomarker development for alcohol addiction treatment using electroencephalography (EEG) including EEG methodologies and their applications.

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Author information

Authors and Affiliations

  1. Center for Intelligent Signal and Imaging Research (CISIR), Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Malaysia

    Pham Lam Vuong, Likun Xia & Aamir Saeed Malik

  2. Department of Psychological Medicine, Faculty of Medicine, University of Malaya, Malaysia

    Rusdi Bin Abd Rashid

Authors
  1. Pham Lam Vuong
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  2. Likun Xia
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  3. Aamir Saeed Malik
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  4. Rusdi Bin Abd Rashid
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Editor information

Editors and Affiliations

  1. Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu, Korea

    Minho Lee

  2. The University of Tokyo, 7-3-1 Hongo, 113-8656, Bunkyo-ku, Tokyo, Japan

    Akira Hirose

  3. Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, Institute of Automation, 100190, Beijing, China

    Zeng-Guang Hou

  4. Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu,, 440-746, Suwon, Korea

    Rhee Man Kil

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© 2013 Springer-Verlag Berlin Heidelberg

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Vuong, P.L., Xia, L., Malik, A.S., Abd Rashid, R.B. (2013). Biomarker Development on Alcohol Addiction Using EEG. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42054-2_26

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  • DOI: https://doi.org/10.1007/978-3-642-42054-2_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42053-5

  • Online ISBN: 978-3-642-42054-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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