Authors:
            
                    André Zúquete
                    
                        
                    
                    ; 
                
                    Bruno Quintela
                    
                        
                    
                     and
                
                    João Paulo Silva Cunha
                    
                        
                    
                    
                
        
        
            Affiliation:
            
                    
                        
                    
                    University of Aveiro, Portugal
                
        
        
        
        
        
             Keyword(s):
            Biometric authentication, Electroencephalograms, Visual evoked potentials.
        
        
            
                Related
                    Ontology
                    Subjects/Areas/Topics:
                
                        Applications
                    ; 
                        Biomedical Engineering
                    ; 
                        Biomedical Signal Processing
                    ; 
                        Biometrics
                    ; 
                        Biometrics and Pattern Recognition
                    ; 
                        Multimedia
                    ; 
                        Multimedia Signal Processing
                    ; 
                        Pattern Recognition
                    ; 
                        Telecommunications
                    
            
        
        
            
                Abstract: 
                This paper studies the suitability of brain activity, namely electroencephalogram signals, as raw material for conducting biometric authentication of individuals. Brain responses were extracted with visual stimulation, leading to biological brain responses known as Visual Evoked Potentials.
We evaluated a novel method, using only 8 occipital electrodes and the energy of differential EEG signals, to extract information about the subjects for further use as their biometric features.  To classify the features obtained from each individual, we used a one-class classifier per subject and we tested four types of classifiers: K-Nearest Neighbor, Support Vector Data Description and two other classifiers resulting from the combination of the two ones previously mentioned. After testing these four classifiers with features of 70 subjects, the results showed that visual evoked potentials are suitable for an accurate biometric authentication.