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EEG Fingerprints under Naturalistic Viewing Using a Portable Device

The electroencephalogram (EEG) has been proven to be a promising technique for personal identification and verification. Recently, the aperiodic component of the power spectrum was shown to outperform other commonly used EEG features. Beyond that, EEG characteristics may capture relevant features re...

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Autores principales: Fraschini, Matteo, Meli, Miro, Demuru, Matteo, Didaci, Luca, Barberini, Luigi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698321/
https://www.ncbi.nlm.nih.gov/pubmed/33212929
http://dx.doi.org/10.3390/s20226565
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author Fraschini, Matteo
Meli, Miro
Demuru, Matteo
Didaci, Luca
Barberini, Luigi
author_facet Fraschini, Matteo
Meli, Miro
Demuru, Matteo
Didaci, Luca
Barberini, Luigi
author_sort Fraschini, Matteo
collection PubMed
description The electroencephalogram (EEG) has been proven to be a promising technique for personal identification and verification. Recently, the aperiodic component of the power spectrum was shown to outperform other commonly used EEG features. Beyond that, EEG characteristics may capture relevant features related to emotional states. In this work, we aim to understand if the aperiodic component of the power spectrum, as shown for resting-state experimental paradigms, is able to capture EEG-based subject-specific features in a naturalistic stimuli scenario. In order to answer this question, we performed an analysis using two freely available datasets containing EEG recordings from participants during viewing of film clips that aim to trigger different emotional states. Our study confirms that the aperiodic components of the power spectrum, as evaluated in terms of offset and exponent parameters, are able to detect subject-specific features extracted from the scalp EEG. In particular, our results show that the performance of the system was significantly higher for the film clip scenario if compared with resting-state, thus suggesting that under naturalistic stimuli it is even easier to identify a subject. As a consequence, we suggest a paradigm shift, from task-based or resting-state to naturalistic stimuli, when assessing the performance of EEG-based biometric systems.
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spelling pubmed-76983212020-11-29 EEG Fingerprints under Naturalistic Viewing Using a Portable Device Fraschini, Matteo Meli, Miro Demuru, Matteo Didaci, Luca Barberini, Luigi Sensors (Basel) Letter The electroencephalogram (EEG) has been proven to be a promising technique for personal identification and verification. Recently, the aperiodic component of the power spectrum was shown to outperform other commonly used EEG features. Beyond that, EEG characteristics may capture relevant features related to emotional states. In this work, we aim to understand if the aperiodic component of the power spectrum, as shown for resting-state experimental paradigms, is able to capture EEG-based subject-specific features in a naturalistic stimuli scenario. In order to answer this question, we performed an analysis using two freely available datasets containing EEG recordings from participants during viewing of film clips that aim to trigger different emotional states. Our study confirms that the aperiodic components of the power spectrum, as evaluated in terms of offset and exponent parameters, are able to detect subject-specific features extracted from the scalp EEG. In particular, our results show that the performance of the system was significantly higher for the film clip scenario if compared with resting-state, thus suggesting that under naturalistic stimuli it is even easier to identify a subject. As a consequence, we suggest a paradigm shift, from task-based or resting-state to naturalistic stimuli, when assessing the performance of EEG-based biometric systems. MDPI 2020-11-17 /pmc/articles/PMC7698321/ /pubmed/33212929 http://dx.doi.org/10.3390/s20226565 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Letter
Fraschini, Matteo
Meli, Miro
Demuru, Matteo
Didaci, Luca
Barberini, Luigi
EEG Fingerprints under Naturalistic Viewing Using a Portable Device
title EEG Fingerprints under Naturalistic Viewing Using a Portable Device
title_full EEG Fingerprints under Naturalistic Viewing Using a Portable Device
title_fullStr EEG Fingerprints under Naturalistic Viewing Using a Portable Device
title_full_unstemmed EEG Fingerprints under Naturalistic Viewing Using a Portable Device
title_short EEG Fingerprints under Naturalistic Viewing Using a Portable Device
title_sort eeg fingerprints under naturalistic viewing using a portable device
topic Letter
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698321/
https://www.ncbi.nlm.nih.gov/pubmed/33212929
http://dx.doi.org/10.3390/s20226565
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