Human brain distinctiveness based on EEG spectral coherence connectivity
| Autor: | La Rocca, D., Campisi, P., Vegso, B., Cserti, P., Kozmann, G., Babiloni, Fabio, DE VICO FALLANI, Fabrizio, Fabrizio De Vico Fallani |
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| Přispěvatelé: | Digital Signal Processing multimedia & Optical Communications lab, Università degli Studi Roma Tre = Roma Tre University (ROMA TRE), Dept. Electrical Engineering and Information Systems, Faculty of Information Technology, University of Pannonia, Dept. Human Physiology, Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi Roma Tre, Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), LA ROCCA, Daria, Campisi, Patrizio, Vegso, B, Cserti, P, Kozmann, G, Babiloni, F, De Vico Fallani, F., De Vico Fallani, Fabrizio |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
FOS: Computer and information sciences
Biometrics [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing Speech recognition Biomedical Engineering Machine Learning (stat.ML) Electroencephalography [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] Statistics - Machine Learning medicine Feature (machine learning) Humans EEG Resting state [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing Spectral coherence medicine.diagnostic_test Resting state fMRI [SCCO.NEUR]Cognitive science/Neuroscience [SCCO.NEUR] Cognitive science/Neuroscience Match score fusion Spectral density Brain Signal Processing Computer-Assisted [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG] Human brain electroencephalography (eeg) medicine.anatomical_structure Frontal lobe Biometric Identification Quantitative Biology - Neurons and Cognition FOS: Biological sciences Optimal distinctiveness theory Neurons and Cognition (q-bio.NC) resting state match score fusion spectral coherence biometrics Psychology [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Human |
| Zdroj: | IEEE Transactions on Biomedical Engineering IEEE Transactions on Biomedical Engineering, 2014, to be published. ⟨10.1109/TBME.2014.2317881⟩ IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2014, to be published. ⟨10.1109/TBME.2014.2317881⟩ |
| ISSN: | 0018-9294 |
| DOI: | 10.1109/TBME.2014.2317881⟩ |
| Popis: | The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of current analysis rely on the extraction of features characterizing the activity of single brain regions, like power-spectrum estimates, thus neglecting possible temporal dependencies between the generated EEG signals. However, important physiological information can be extracted from the way different brain regions are functionally coupled. In this study, we propose a novel approach that fuses spectral coherencebased connectivity between different brain regions as a possibly viable biometric feature. The proposed approach is tested on a large dataset of subjects (N=108) during eyes-closed (EC) and eyes-open (EO) resting state conditions. The obtained recognition performances show that using brain connectivity leads to higher distinctiveness with respect to power-spectrum measurements, in both the experimental conditions. Notably, a 100% recognition accuracy is obtained in EC and EO when integrating functional connectivity between regions in the frontal lobe, while a lower 97.41% is obtained in EC (96.26% in EO) when fusing power spectrum information from centro-parietal regions. Taken together, these results suggest that functional connectivity patterns represent effective features for improving EEG-based biometric systems. Comment: Key words: EEG, Resting state, Biometrics, Spectral coherence, Match score fusion |
| Databáze: | OpenAIRE |
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