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Recent Trends and Open Challenges in EEG Based Brain-Computer Interface Systems

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InECCE2019

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 632))

Abstract

Recent advances in computer hardware and signal processing have made possible the use of electroencephalogram (EEG) for communication between human brain and computers and this technology is known as brain-computer interface (BCI). Locked-in patients have now a way to communicate with the outside world using BCI technology. Nowadays, BCIs are getting popularity among the researchers to control devices using brainwaves especially in providing good assistance to disabled people. Impressive development and integration of both hardware and software in BCI have been carried out in the last two decades. However, some open challenges and limitations have also been exposed in the previous researches. In this paper, we have tried to mention some critical issues of EEG based BCI system including EEG modalities, EEG acquisition, signal processing algorithm and performance evaluation. These issues need to be solved to develop error-free BCI system. In addition, possible solutions and future directions have also been discussed.

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Acknowledgements

The author would like to acknowledge the great supports by the Faculty of Electrical and Electronics Engineering as well as Universiti Malaysia Pahang for providing financial support through research grant, PGRS 190326.

Author information

Authors and Affiliations

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

    Mamunur Rashid, Norizam Sulaiman, Mahfuzah Mustafa, Sabira Khatun & Bifta Sama Bari

  2. Faculty of Mechanical and Manufacturing Engineering, Universiti Malaysia Pahang, 26600, Pekan, Pahang, Malaysia

    Md Jahid Hasan

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  1. Mamunur Rashid
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  2. Norizam Sulaiman
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  3. Mahfuzah Mustafa
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  4. Sabira Khatun
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  5. Bifta Sama Bari
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Editor information

Editors and Affiliations

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

    Ahmad Nor Kasruddin Nasir

  2. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Mohd Ashraf Ahmad

  3. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Muhammad Sharfi Najib

  4. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Yasmin Abdul Wahab

  5. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Nur Aqilah Othman

  6. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Nor Maniha Abd Ghani

  7. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Addie Irawan

  8. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Sabira Khatun

  9. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Raja Mohd Taufika Raja Ismail

  10. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Mohd Mawardi Saari

  11. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Mohd Razali Daud

  12. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

    Ahmad Afif Mohd Faudzi

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Rashid, M., Sulaiman, N., Mustafa, M., Khatun, S., Bari, B.S., Hasan, M.J. (2020). Recent Trends and Open Challenges in EEG Based Brain-Computer Interface Systems. In: Kasruddin Nasir, A.N., et al. InECCE2019. Lecture Notes in Electrical Engineering, vol 632. Springer, Singapore. https://doi.org/10.1007/978-981-15-2317-5_31

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  • DOI: https://doi.org/10.1007/978-981-15-2317-5_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2316-8

  • Online ISBN: 978-981-15-2317-5

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