Abstract
The purpose of this chapter is to explore the idea of using EEG signals as a biometric modality to recognize individuals. Considered as a variant of Brain Computer Interface (BCI), the concept presented in this chapter deals with a Multi-Channel EEG using Emotiv Epoc system. Mainly, a special interest will be addressed to EEG maps analysis for persons recognition. For this purpose, a generic schema is considered, namely pre-processing, feature extraction, Matching/classification leading to a verification decision.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Berger, H.: Über das elektrenkephalogramm des menschen. Arch. Psychiatr Nervenkr 87, 527–570 (1929)
Berger, H.: Über das Elektrenkephalogramm des Menschen. XIII [The human electroencephalogram]. Archiv für Psychiatrie und Nervenkrankheiten 106, 576–584 (1937)
Szurhaj, W., Lamblin, M.-D., Kaminska, A., Sediri, H.: EEG guidelines in the diagnosis of brain death. Neurophysiol. Clin./Clin. Neurophysiol. 45(1), pp. 97–104, ISSN 0987-7053 (2015)
Jayarathne, I., Cohen, M., Amarakeerthi, S.: Survey of EEG-based biometric authentication. In: 2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST), Taichung, pp. 324–329 (2017)
Basar, E., Düzgün, A.: How is the brain working?: research on brain oscillations and connectivities in a new “take-off” state. Int. J. Psychophysiol. 103, 3–11 (2016)
Bassett, D.S., Gazzaniga, M.S.: Understanding complexity in the human brain. Trends in Cogn. Sci. 15(5), 200–209, ISSN 1364-6613 (2011)
Sebastian023 [CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0)]
Sörnmo, L., Laguna, P.: Chapter 2—the electroencephalogram—a brief background. In: Sörnmo, L., Laguna, P. (eds.) In Biomedical Engineering, Bioelectrical Signal Processing in Cardiac and Neurological Applications, pp. 25–53. Academic Press, ISBN 9780124375529 (2005)
Kerbaj, D., Hassan, W., Nait-Ali, A.: Verifying a personas identity using brain responses to visual stimuli. In: 2017 2nd International Conference on Bio-engineering for Smart Technologies (BioSMART), Paris, pp. 1–6 (2017)
Marks, W.J.,, Laxer, K.D.: Chapter 7—invasive clinical neurophysiology in epilepsy and movement disorders. In: Aminoff, M.J. (eds.) Aminoff’’s electrodiagnosis in clinical neurology (6th edn), pp. 165–185. W.B. Saunders. ISBN 9781455703081 (2012)
https://www.emotiv.com/, (online)
Kang, J.-H., Jo, Y.C., Kim, S.P.: Electroencephalographic feature evaluation for improving personal authentication performance. Neurocomputing, 287, pp. 93–101, ISSN 0925-2312 (2018)
Chauhan, S., Arora, A.S., Kaul, A.: A survey of emerging biometric modalities. Procedia Comput. Sci. 2, 213–218, ISSN 1877-0509. https://doi.org/10.1016/j.procs.2010.11.027 (2010)
Reshmi, K.C., Muhammed, P.I., Priya, V.V., Akhila, V.A.: A novel approach to brain biometric user recognition. Procedia Technol. 25, 240–247, ISSN 2212-0173 (2016)
Eva, O.D., Lazar, A.M.: Comparison of classifiers and statistical analysis for EEG signals used in brain computer interface motor task paradigm. Int. J. Adv. Res. Artif. Intell. (IJARAI), 4(1) (2015)
Voznenko, T.I., Chepin, E.V., Urvanov, G.A.: The control system based on extended BCI for a robotic wheelchair. Procedia Comput. Sci 123, 522–527, ISSN 1877-0509 (2018)
Zhang, X., Yao, L., Sheng, Q., Kanhere, S., Gu, T., Zhang, D.: Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signals. https://doi.org/10.1109/percom.2018.8444575 (2018)
Nait-Ali, A.: Hidden biometrics: towards using biosignals and biomedical images for security applications. In: International Workshop on Systems, Signal Processing and their Applications, WOSSPA, Tipaza, pp. 352–356 (2011)
Rodrigues, R.N., Ling, L.L., Govindaraju, V.: Robustness of multimodal biometric methods against spoof attacks. J. Vis. Lang. Comput. 20, 169–179 (2009)
Rao, T.K., Lakshmi, M.R., Prasad, T.: An exploration on brain computer interface and its recent trends. Int. J. Adv. Res. Artif. Intell. 1, 17 (2012) https://doi.org/10.14569/ijarai.2012.010804
Sweeney, K.T., Ward, T.E., McLoone, S.F.: Artifact removal in physiological signals—practices and possibilities. IEEE Trans. Inf Technol. Biomed. 16(3), 488–500 (2012)
Kumar, P.S., Arumuganathan, R., Sivakumar, K., Vimal, C.: Removal of artifacts from EEG signals using adaptive filter through wavelet transform. In: 2008 9th International Conference on Signal Processing, Beijing, pp. 2138–2141 (2008)
Kumar, P.S., Arumuganathan, R., Vimal, C.: Wavelet based ocular artifact removal from EEG signals using ARMA method and adaptive filtering. In: Proceedings—2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009, vol. 3 (2009). https://doi.org/10.1109/icicisys.2009.5358090
Croft, R.J., Barry, R.J.: Removal of ocular artifacts from the EEG: a review. J. Clin. Neurophysiol. 30, 5–19 (2000)
Daly, I., Billinger, M., Scherer, R., Mueller-Putz, G.: On the automated removal of artifacts related to head movement from the EEG. IEEE Trans. Neural Syst. Rehabil. Eng. 21(3), 427–434 (2013)
Ngoc, P.P., Hai, V.D., Bach, N.C., Van Binh, P.: EEG signal analysis and artifact removal by wavelet transform. In: Toi, V., Lien Phuong, T. (eds.) 5th International Conference on Biomedical Engineering in Vietnam. IFMBE Proceedings, vol. 46. Springer, Cham (2015)
Edla, D.R., Ansari, M.F., Chaundhary, N., Dodila, S.: Classification of facial expressions from EEG signals using wavelet packet transform and SVM for wheelchair control operations. Procedia Comput. Sci. 132, 1467–1476, ISSN 1877-0509 (2018)
Puce, A., Hämäläinen, M.S.: A review of issues related to data acquisition and analysis in EEG/MEG studies. Brain Sci. 7(6), 58 (2017)
Voznenko, T.I., Dyumin, A.A., Aksenova, E.V., Gridnev, A.A., Delov, V.A.: The experimental study of ‘Unwanted Music’ noise pollution influence on command recognition by brain-computer interface. Procedia Comput. Sci. 123, 528–533, ISSN 1877-0509 (2018)
Zhou, S., Allison, B.Z., Kübler, A., Cichocki, A., Wang, X., Jin, J.: Effects of background music on objective and subjective performance measures in an auditory BCI. Front. Comput. Neurosci. 10, 105 (2016). https://doi.org/10.3389/fncom.2016.00105
Motamedi-Fakhr, Shayan, Moshrefi-Torbati, M., Hill, Martyn, Hill, Catherine, White, Paul: Signal processing techniques applied to human sleep EEG signals—a review. Biomed. Signal Process. Control 10, 21–33 (2014). https://doi.org/10.1016/j.bspc.2013.12.003
Chuang, J., Nguyen, H., Wang, C., Johnson, B.: I think, therefore I am: usability and security of authentication using brainwaves. In: International Conference on Financial Cryptography and Data Security, pp. 1–16. Springer (2013)
Jayarathne, I., Cohen, M., Amarakeerthi, S.: BrainID: development of an EEG-based biometric authentication system. In: 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, pp. 1–6 (2016)
Ngoc P.P., Hai, V.D., Bach N.C., Van Binh, P.: EEG signal analysis and artifact removal by wavelet transform. In: Toi, V., Lien Phuong, T. (eds) 5th International Conference on Biomedical Engineering in Vietnam. IFMBE Proceedings, vol. 46. Springer, Cham (2015)
Hazarika, N., Chen, J.Z., Tsoi, A.C., Sergejew, A.: Classification of EEG signals using the wavelet transform. In: Proceedings of 13th International Conference on Digital Signal Processing, Santorini, Greece, vol. 1, pp. 89–92. https://doi.org/10.1109/icdsp.1997.627975 (1997)
Altahat, S., Chetty, G., Tran, D., Ma, W.: Analysing the robust EEG channel set for person authentication. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds.) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science, vol. 9492. Springer, Cham (2015)
Jayarathne, I., Cohen, M. Amarakeerthi, S.: BrainID: development of an EEG-based biometric authentication system. In: 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, pp. 1–6 (2016)
Poulos, M., Rangoussi, M., Alexandris, N.: Neural network based person identification using EEG features. In: 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No. 99CH36258), Phoenix, AZ, USA, vol. 2, pp. 1117–1120 (1999)
Laka, P., Mazurczyk, W.: User perspective and security of a new mobile authentication method. Telecommun. Syst. (2018) https://doi.org/10.1007/s11235-018-0437-1
Blondet, M.V.R., Khalifian, N., Kurtz, K.J., Laszlo, S., Jin, Z.: Brainwaves as authentication method: proving feasibility under two different approaches. In: 2014 40th Annual Northeast Bioengineering Conference (NEBEC), Boston, MA, pp. 1–2. https://doi.org/10.1109/nebec.2014.6972734 (2014)
Pham, T., Ma, W., Tran, D., Nguyen, P., Phung, D.: A study on the feasibility of using EEG signals for authentication purpose. In: Lee, M., Hirose, A., Hou, Z.G., Kil, R.M. (eds.) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol. 8227. Springer, Berlin, Heidelberg (2013)
Jagadiswary, D., Saraswady, D.: Biometric authentication using fused multimodal biometric. Procedia Comput. Sci. 85, 109–116, ISSN 1877-0509 (2016)
Abo-Zahhad, M., Ahmed, S.M., Abbas, S.N.: A new multi-level approach to EEG based human authentication using eye blinking. Pattern Recogn. Lett. 82(2), pp. 216–225, ISSN 0167-8655 (2016)
Wang, M., Abbass, H.A., Hu, J.: Continuous authentication using EEG and face images for trusted autonomous systems. In: 2016 14th Annual Conference on Privacy, Security and Trust (PST), Auckland, 368–375 (2016)
Palaniappan, R.: Electroencephalogram signals from imagined activities: a novel biometric identifier for a small population. In: International Conference on Intelligent Data Engineering and Automated Learning, pp. 604–611. Springer (2006)
Zhang, X., Yao, L., Chen, K., Wang, X., Sheng, Q.Z., Gu, T.: DeepKey: an EEG and gait based dual-authentication system. CoRR abs/1706.01606 (2017): n. pag
Ashby, C., Bhatia, A., Tenore, F., Vogelstein, J.: Low-cost electroencephalogram (EEG) based authentication. In: 2011 5th International IEEE/EMBS Conference on Neural Engineering, Cancun, pp. 442–445 (2011)
Tektaş, F., Yücer, Ş. Kanak, A.: A new approach in border security applications with EEG biometrics. In: 2017 25th Signal Processing and Communications Applications Conference (SIU), Antalya, pp. 1–4 (2017)
Nakamura, T., Goverdovsky, V., Mandic, D.P.: In-ear EEG biometrics for feasible and readily collectable real-world person authentication. IEEE Trans. Inf. Forensics Secur. 13(3), 648–661 (2018)
Singh, B., Mishra, S., Tiwary, U.S.: EEG based biometric identification with reduced number of channels. In: 2015 17th International Conference on Advanced Communication Technology (ICACT), Seoul, pp. 687–691 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Goudiaby, B., Othmani, A., Nait-ali, A. (2020). EEG Biometrics for Person Verification. In: Nait-ali, A. (eds) Hidden Biometrics. Series in BioEngineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-0956-4_3
Download citation
DOI: https://doi.org/10.1007/978-981-13-0956-4_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0955-7
Online ISBN: 978-981-13-0956-4
eBook Packages: EngineeringEngineering (R0)