: 2017 : EEG-Based Biometrics: Challenges and Applications
Call For Papers
Special Issue on EEG-Based Biometrics: Challenges and Applications
Computational Intelligence and Neuroscience, IF=1.215 (Clarivate Analytics Web of Science)
Biometrics is aimed at recognizing individuals based on physical, physiological, or behavioural characteristics of a human body such as fingerprint, gait, voice, iris, and gaze. Currently, the state-of-the art methods for biometric authentication are being incorporated in various access control and personal identity management applications. While the hand-based biometrics (including fingerprint) have been the most often used technology so far, there is growing evidence that electroencephalogram (EEG) signals collected during a perception or mental task can be used for reliable person recognition. However, the domain of EEG-based biometry still faces the problems of improving the accuracy, robustness, security, privacy, and ergonomics of EEG-based biometric systems and substantial efforts are needed towards developing efficient sets of stimuli (visual or auditory) that can be used of person identification in Brain-Computer Interface (BCI) systems and applications.
There are still many challenging problems involved in improving the accuracy, efficiency, and usability of EEG-based biometric systems and problems related to designing, developing, and deploying new security-related BCI applications, for example, for personal authentication on mobile devices, VR (Virtual Reality) headsets, and Internet.
This special issue aims to introduce the recent progress of EEG-based biometrics and addresses the challenges in developing EEG-based biometry systems for various practical applications, while proposing new ideas and directions for future development.
Potential topics include but are not limited to the following:
Data preprocessing, feature extraction, recognition, and matching for EEG-based biometric systems
Signal processing and machine learning techniques for EEG-based biometrics
EEG biometric based passwords and encryption
Cancellable EEG biometrics
Multimodal (EEG, EMG, ECG, and other biosignals) biometrics
Pattern recognition for biometrics
Performance and accuracy evaluation of EEG-based biometric systems
Protocols, standards, and interfaces for EEG biometrics
Security and privacy of biometric EEG data
Information fusion for biometrics involving EEG data
EEG biometrics for VR applications
Stimuli sets for EEG-based biometrics
Passive BCI technology
Authors can submit their manuscripts through the Manuscript Tracking System at https://mts.hindawi.com/submit/journals/cin/eebb/.
Manuscript Due: 2017-12-29
First Round of Reviews: 2018-03-23
Publication Date: 2018-05-18
Lead Guest Editor
Victor Hugo C. De Albuquerque, Universidade de Fortaleza, Fortaleza, Brazil
Robertas Damaševičius, Kaunas University of Technology, Kaunas, Lithuania
João M. R. S. Tavares, University of Porto, Porto, Portugal
Plácido R. Pinheiro, University of Fortaleza, Fortaleza, Brazil