EEG biometric identification: repeatability and influence of movement-related EEG

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00194645" target="_blank" >RIV/68407700:21230/12:00194645 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
EEG biometric identification: repeatability and influence of movement-related EEG
Original language description
This paper describes use of EEG signal as biometric characteristic for person identification. We focus on the problem of repeatability of the identification process, and influence of the movement-related EEG on results of identification. Used database ofEEG signals consists of two sessions, obtained approximately one year apart. We use frequency-Zooming Auto-Regression modeling and Mahalanobis distance-based classifier for classification of EEG segments, which leads to subject identification with success rate for single session identification up to 98%. When the earlier session is used for classifier training and the later session for testing, the highest success rate with our identification algorithm is 87.1%. Experiments show that use of the movement-related EEG leads to better identification results.
Czech name
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Czech description
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Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2012 International Conference on Applied Electronics
ISBN
978-80-261-0038-6
ISSN
1803-7232
e-ISSN
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Number of pages
4
Pages from-to
147-150
Publisher name
University of West Bohemia
Place of publication
Pilsen
Event location
Plzeň
Event date
Sep 6, 2012
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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