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Electroencephalogram Based Biometric System: A Review

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Advances in Communication and Computational Technology (ICACCT 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 668))

Abstract

EEG signals can be preferred as a biometric trait because of their uniqueness, robustness to spoof attacks, and many other advantages as compared to other commonly used identifiers such as finger print, palm print, and face recognition. A complete overview of biometric systems based on EEG signals, their acquisition, pre-processing, feature extraction, and classification at different frequency bands is presented in this paper. Comparison is made between various techniques and their efficiencies used in EEG-based biometric systems. Different signal acquisition methods (resting state, visual stimuli, cognitive activities) used in previous works have been discussed with their pros and cons. Nowaday’s researchers focus on low-cost EEG acquisition systems with a smaller number of electrodes with better accuracy. Databases used in this area are also discussed, some of them are public and some authors acquire their personal data. A table is provided which compares the results of different signal acquisition methods, pre-processing techniques, feature extraction, and classification techniques.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Deenbandhu Chhotu Ram Institute of Science and Technology, Murthal, Haryana, 131039, India

    Kaliraman Bhawna,  Priyanka & Manoj Duhan

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  1. Kaliraman Bhawna
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  2. Priyanka
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  3. Manoj Duhan
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Correspondence to Kaliraman Bhawna .

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Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Maryland Eastern Shore, Princess Anne, MD, USA

    Gurdeep Singh Hura

  2. Department of Master of Computer Applications, National Institute of Technology Kurukshetra, Kurukshetra, Haryana, India

    Ashutosh Kumar Singh

  3. Department of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Melaka, Malaysia

    Lau Siong Hoe

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Bhawna, K., Priyanka, Duhan, M. (2021). Electroencephalogram Based Biometric System: A Review. In: Hura, G.S., Singh, A.K., Siong Hoe, L. (eds) Advances in Communication and Computational Technology. ICACCT 2019. Lecture Notes in Electrical Engineering, vol 668. Springer, Singapore. https://doi.org/10.1007/978-981-15-5341-7_5

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  • DOI: https://doi.org/10.1007/978-981-15-5341-7_5

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