• 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