DocumentCode :
1797674
Title :
Investigating the impacts of epilepsy on EEG-based person identification systems
Author :
Dinh Phung ; Dat Tran ; Wanli Ma ; Phuoc Nguyen ; Tien Pham
Author_Institution :
Fac. of Educ. Sci. Technol. & Math., Univ. of Canberra, Canberra, ACT, Australia
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
3644
Lastpage :
3648
Abstract :
Person identification using electroencephalogram (EEG) as biometric has been widely used since it is capable of achieving high identification rate. Epilepsy is one of the brain disorders that involves in the EEG signal and hence it may have impact on EEG-based person identification systems. However, this issue has not been investigated. In this paper, we perform person identification on two groups of subjects, normal and epileptic to investigate the impact of epilepsy on the identification rate. Autoregressive model (AR) and Approximate entropy (ApEn) are employed to extract features from these two groups. Experimental results show that epilepsy actually have impacts depending on feature extraction method used in the system.
Keywords :
autoregressive processes; electroencephalography; entropy; feature extraction; medical signal processing; AR; ApEn; EEG-based person identification systems; approximate entropy; autoregressive model; brain disorders; electroencephalogram; epilepsy; feature extraction; Brain modeling; Chaos; Electroencephalography; Entropy; Epilepsy; Feature extraction; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
Type :
conf
DOI :
10.1109/IJCNN.2014.6889567
Filename :
6889567
Link To Document :
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