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Auditory Evoked Potential (AEP) Based Brain-Computer Interface (BCI) Technology: A Short Review

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Advances in Robotics, Automation and Data Analytics (iCITES 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1350))

Abstract

Auditory evoked potential (AEP) is a sort of electroencephalographic (EEG) signal elicited by an acoustic stimulus from the brain scalp. An intelligent auditory perception level system helps the auditory system to analyze and assess its functional integrity. Initially, the AEP signals are utilized in accurate and fast hearing threshold level detection in early stage. However, this emerging psychological modality expands it applications like other EEG control signals. Recently, AEP responses are initiated into the brain-computer technology (BCI) technology. This paper presents a short review on AEP based BCI technology. First, a concise overview of AEP signal and its analysis procedure are discussed. Then the existing AEP based studies are reviewed and their summary in terms of data description, feature extraction, classification methods and performance are tabulated. Finally, the issues of the recent AEP signal analysis have been addressed and potential ways are suggested to alleviate existing problems. Finally, the issues to the existing AEP based BCI technology are presented, and the possible solutions are also recommended.

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Acknowledgment

This research is supported by Universiti Malaysia Pahang, Malaysia with the research grant RDU180396.

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Authors and Affiliations

  1. Faculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang, 26600, Pekan, Pahang, Malaysia

    Md Nahidul Islam, Norizam Sulaiman, Bifta Sama Bari, Mamunur Rashid & Mahfuzah Mustafa

Authors
  1. Md Nahidul Islam
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  2. Norizam Sulaiman
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  3. Bifta Sama Bari
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  4. Mamunur Rashid
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  5. Mahfuzah Mustafa
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Corresponding author

Correspondence to Md Nahidul Islam .

Editor information

Editors and Affiliations

  1. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Jessnor Arif Mat Jizat

  2. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Ismail Mohd Khairuddin

  3. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Mohd Azraai Mohd Razman

  4. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Ahmad Fakhri Ab. Nasir

  5. College of Engineering, Universiti Malaysia Pahang, Gambang, Malaysia

    Mohamad Shaiful Abdul Karim

  6. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Abdul Aziz Jaafar

  7. UCSI University, Kuala Lumpur, Malaysia

    Lim Wei Hong

  8. Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, Pekan, Malaysia

    Anwar P. P. Abdul Majeed

  9. University of York, York, UK

    Pengcheng Liu

  10. School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Hyun Myung

  11. Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Han-Lim Choi

  12. Department of Information Engineering, University of Padua, Padova, Italy

    Gian-Antonio Susto

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Islam, M.N., Sulaiman, N., Bari, B.S., Rashid, M., Mustafa, M. (2021). Auditory Evoked Potential (AEP) Based Brain-Computer Interface (BCI) Technology: A Short Review. In: Mat Jizat, J.A., et al. Advances in Robotics, Automation and Data Analytics. iCITES 2020. Advances in Intelligent Systems and Computing, vol 1350. Springer, Cham. https://doi.org/10.1007/978-3-030-70917-4_26

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