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Calibration of Low Density EEG Sensor Arrays for Brain Source Localization

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Neural Information Processing (ICONIP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7663))

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Abstract

This paper investigates the performance of calibration techniques on synthetic Electroencephalography (EEG) data. Brain source localization was performed using an iterative algorithm. A transfer-function-based calibration technique was developed. This technique can be applied in two forms: external calibration and autocalibration. For a low density EEG array system, it was shown that the proposed calibration technique can offer improved performance relative to previously published work.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, American University of Sharjah, UAE

    Tahereh Zarghami, Hasan S. Mir & Hasan Al-Nashash

Authors
  1. Tahereh Zarghami
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  2. Hasan S. Mir
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  3. Hasan Al-Nashash
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Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Education City, P.O. Box 23874, Doha, Qatar

    Tingwen Huang

  2. Department of Control Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, Hubei, China

    Zhigang Zeng

  3. College of Computer Science, Chongqing University, 174 Shazhengjie Street, 400044, Chongqing, China

    Chuandong Li

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Chi Sing Leung

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© 2012 Springer-Verlag Berlin Heidelberg

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Zarghami, T., Mir, H.S., Al-Nashash, H. (2012). Calibration of Low Density EEG Sensor Arrays for Brain Source Localization. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34475-6_40

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  • DOI: https://doi.org/10.1007/978-3-642-34475-6_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34474-9

  • Online ISBN: 978-3-642-34475-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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