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Journal of Sensors
Volume 2016 (2016), Article ID 1831742, 9 pages
Research Article

Identity Recognition Using Biological Electroencephalogram Sensors

1College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, China
2School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
3Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA

Received 30 June 2016; Accepted 19 September 2016

Academic Editor: Fei Yu

Copyright © 2016 Wei Liang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Brain wave signal is a bioelectric phenomenon reflecting activities in human brain. In this paper, we firstly introduce brain wave-based identity recognition techniques and the state-of-the-art work. We then analyze important features of brain wave and present challenges confronted by its applications. Further, we evaluate the security and practicality of using brain wave in identity recognition and anticounterfeiting authentication and describe use cases of several machine learning methods in brain wave signal processing. Afterwards, we survey the critical issues of characteristic extraction, classification, and selection involved in brain wave signal processing. Finally, we propose several brain wave-based identity recognition techniques for further studies and conclude this paper.