Investigating the Impacts of Brain Conditions on EEG-Based Person Identification

Dinh PHUNG, Dat TRAN, Wanli MA, Tien PHAM

Research output: A Conference proceeding or a Chapter in BookConference contribution

Abstract

Person identification using electroencephalogram (EEG) as biometric has been widely used since it is capable of achieving high identification rate. Brain conditions such as epilepsy and alcohol are some of problems that cause brain disorders in EEG signals, and hence they may have impacts on EEG-based person identification systems. However, this issue has not been investigated. In this paper, we perform person identification on two datasets, Australian and Alcoholism EEG, then compare the classification rates between epileptic and non-epileptic groups, and between alcoholic and non-alcoholic groups, to investigate the impacts of such brain conditions on the identification rates. Shannon (SEn), Spectral (SpEn), Approximate entropy (ApEn), Sample (SampEn) and Conditional (CEn) entropy are employed to extract features from these two datasets. Experimental results show that both epilepsy and alcohol actually have different impacts depending on feature extraction method used in the system.
Original languageEnglish
Title of host publicationInternational Joint Conference CISIS 2015 and ICEUTE 2015
EditorsAlvaro Herrero, Bruno Baruque, Javier Sedano, Hector Quintian, Emilio Corchado
PublisherSpringer
Pages145-155
Number of pages11
Volume369
ISBN (Electronic)9783319197135
ISBN (Print)9783319197128
DOIs
Publication statusPublished - 27 May 2015
EventThe 8th International Conference on Computational Intelligence in Security for Information Systems - http://cisis.usal.es , Burgos, Spain
Duration: 15 Jun 201517 Jun 2015
http://cisis.usal.es

Publication series

NameAdvances in Intelligent Systems and Computing
Volume369
ISSN (Print)2194-5357

Conference

ConferenceThe 8th International Conference on Computational Intelligence in Security for Information Systems
Abbreviated titleCISIS 2015
CountrySpain
CityBurgos
Period15/06/1517/06/15
Internet address

Fingerprint

Electroencephalography
Brain
Alcohols
Entropy
Biometrics
Feature extraction
Identification (control systems)

Cite this

PHUNG, D., TRAN, D., MA, W., & PHAM, T. (2015). Investigating the Impacts of Brain Conditions on EEG-Based Person Identification. In A. Herrero, B. Baruque, J. Sedano, H. Quintian, & E. Corchado (Eds.), International Joint Conference CISIS 2015 and ICEUTE 2015 (Vol. 369, pp. 145-155). (Advances in Intelligent Systems and Computing; Vol. 369). Springer. https://doi.org/10.1007/978-3-319-19713-5_13
PHUNG, Dinh ; TRAN, Dat ; MA, Wanli ; PHAM, Tien. / Investigating the Impacts of Brain Conditions on EEG-Based Person Identification. International Joint Conference CISIS 2015 and ICEUTE 2015. editor / Alvaro Herrero ; Bruno Baruque ; Javier Sedano ; Hector Quintian ; Emilio Corchado. Vol. 369 Springer, 2015. pp. 145-155 (Advances in Intelligent Systems and Computing).
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abstract = "Person identification using electroencephalogram (EEG) as biometric has been widely used since it is capable of achieving high identification rate. Brain conditions such as epilepsy and alcohol are some of problems that cause brain disorders in EEG signals, and hence they may have impacts on EEG-based person identification systems. However, this issue has not been investigated. In this paper, we perform person identification on two datasets, Australian and Alcoholism EEG, then compare the classification rates between epileptic and non-epileptic groups, and between alcoholic and non-alcoholic groups, to investigate the impacts of such brain conditions on the identification rates. Shannon (SEn), Spectral (SpEn), Approximate entropy (ApEn), Sample (SampEn) and Conditional (CEn) entropy are employed to extract features from these two datasets. Experimental results show that both epilepsy and alcohol actually have different impacts depending on feature extraction method used in the system.",
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PHUNG, D, TRAN, D, MA, W & PHAM, T 2015, Investigating the Impacts of Brain Conditions on EEG-Based Person Identification. in A Herrero, B Baruque, J Sedano, H Quintian & E Corchado (eds), International Joint Conference CISIS 2015 and ICEUTE 2015. vol. 369, Advances in Intelligent Systems and Computing, vol. 369, Springer, pp. 145-155, The 8th International Conference on Computational Intelligence in Security for Information Systems, Burgos, Spain, 15/06/15. https://doi.org/10.1007/978-3-319-19713-5_13

Investigating the Impacts of Brain Conditions on EEG-Based Person Identification. / PHUNG, Dinh; TRAN, Dat; MA, Wanli; PHAM, Tien.

International Joint Conference CISIS 2015 and ICEUTE 2015. ed. / Alvaro Herrero; Bruno Baruque; Javier Sedano; Hector Quintian; Emilio Corchado. Vol. 369 Springer, 2015. p. 145-155 (Advances in Intelligent Systems and Computing; Vol. 369).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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N2 - Person identification using electroencephalogram (EEG) as biometric has been widely used since it is capable of achieving high identification rate. Brain conditions such as epilepsy and alcohol are some of problems that cause brain disorders in EEG signals, and hence they may have impacts on EEG-based person identification systems. However, this issue has not been investigated. In this paper, we perform person identification on two datasets, Australian and Alcoholism EEG, then compare the classification rates between epileptic and non-epileptic groups, and between alcoholic and non-alcoholic groups, to investigate the impacts of such brain conditions on the identification rates. Shannon (SEn), Spectral (SpEn), Approximate entropy (ApEn), Sample (SampEn) and Conditional (CEn) entropy are employed to extract features from these two datasets. Experimental results show that both epilepsy and alcohol actually have different impacts depending on feature extraction method used in the system.

AB - Person identification using electroencephalogram (EEG) as biometric has been widely used since it is capable of achieving high identification rate. Brain conditions such as epilepsy and alcohol are some of problems that cause brain disorders in EEG signals, and hence they may have impacts on EEG-based person identification systems. However, this issue has not been investigated. In this paper, we perform person identification on two datasets, Australian and Alcoholism EEG, then compare the classification rates between epileptic and non-epileptic groups, and between alcoholic and non-alcoholic groups, to investigate the impacts of such brain conditions on the identification rates. Shannon (SEn), Spectral (SpEn), Approximate entropy (ApEn), Sample (SampEn) and Conditional (CEn) entropy are employed to extract features from these two datasets. Experimental results show that both epilepsy and alcohol actually have different impacts depending on feature extraction method used in the system.

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PB - Springer

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PHUNG D, TRAN D, MA W, PHAM T. Investigating the Impacts of Brain Conditions on EEG-Based Person Identification. In Herrero A, Baruque B, Sedano J, Quintian H, Corchado E, editors, International Joint Conference CISIS 2015 and ICEUTE 2015. Vol. 369. Springer. 2015. p. 145-155. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-19713-5_13