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Resting-state EEG: A Study on its non-Stationarity for Biometric Applicaions

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2017

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Gesellschaft für Informatik, Bonn

Zusammenfassung

In the last years, several papers on EEG-based biometric recognition systems have been published. Specifically, most of the proposed contributions focus on brain signals recorded in resting state conditions, with either closed or open eyes. A common assumption is that the acquired signals are quasi-stationarity. In this paper, we investigate such property in terms of discriminative capability, and we analyze whether or not it holds throughout the entire duration of data collected over long periods. An extensive set of experimental tests, conducted over a database comprising signals collected from 50 subjects in three distinct acquisition sessions, shows that the most distinctive information of the brain signals is temporally located at the beginning of each recording.

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Hine, Gabriel Emile; Maiorana, Emanuele; Campisi,Patrizio (2017): Resting-state EEG: A Study on its non-Stationarity for Biometric Applicaions. BIOSIG 2017. Gesellschaft für Informatik, Bonn. PISSN: 1617-5468. ISBN: 978-3-88579-664-0. pp. 15-23. Regular Research Papers. Darmstadt, Germany. 20.-22. September 2017

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