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Authors: Paolo Paradisi 1 ; Marco Righi 2 and Umberto Barcaro 3

Affiliations: 1 Istituto di Scienza e Tecnologie dell'Informazione ``A. Faedo'' (ISTI-CNR) and Basque Center of Applied Mathematics (BCAM), Italy ; 2 Istituto di Scienza e Tecnologie dell'Informatica ``A. Faedo'' (ISTI-CNR), Italy ; 3 Università di Pisa, Italy

ISBN: 978-989-758-197-7

ISSN: 2184-321X

Keyword(s): Biomedical Signal Processing, Electroencephalogram, Brain Events, Fractal Intermittency, Threshold Analysis, Pattern Recognition, Complex Systems.

Related Ontology Subjects/Areas/Topics: Biosignal Acquisition, Analysis and Processing ; Human-Computer Interaction ; Methodologies and Methods ; Physiological Computing Systems

Abstract: In the last years, the complexity paradigm is gaining momentum in many research fields where large multidimensional datasets are made available by the advancements in instrumental technology. A complex system is a multi-component system with a large number of units characterized by cooperative behavior and, consequently, emergence of well-defined self-organized structures, such as communities in a complex network. The self-organizing behavior of the brain neural network is probably the most important prototype of complexity and is studied by means of physiological signals such as the ElectroEncephaloGram (EEG). Physiological signals are typically intermittent, i.e., display non-smooth rapid variations or crucial events (e.g., cusps or abrupt jumps) that occur randomly in time, or whose frequency changes randomly. In this work, we introduce a complexity-based approach to the analysis and modeling of physiological data that is focused on the characterization of intermittent events. Rece nt findings about self-similar or fractal intermittency in human EEG are reviewed. The definition of brain event is a crucial aspect of this approach that is discussed in the last part of the paper, where we also propose and discuss a first version of a general-purpose event detection algorithm for EEG signals. (More)

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Paper citation in several formats:
Paradisi, P.; Righi, M. and Barcaro, U. (2016). The Challenge of Brain Complexity - A Brief Discussion about a Fractal Intermittency-based Approach.In Proceedings of the 3rd International Conference on Physiological Computing Systems - Volume 1: PhyCS, ISBN 978-989-758-197-7, ISSN 2184-321X, pages 123-129. DOI: 10.5220/0005998601230129

@conference{phycs16,
author={Paolo Paradisi. and Marco Righi. and Umberto Barcaro.},
title={The Challenge of Brain Complexity - A Brief Discussion about a Fractal Intermittency-based Approach},
booktitle={Proceedings of the 3rd International Conference on Physiological Computing Systems - Volume 1: PhyCS,},
year={2016},
pages={123-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005998601230129},
isbn={978-989-758-197-7},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Physiological Computing Systems - Volume 1: PhyCS,
TI - The Challenge of Brain Complexity - A Brief Discussion about a Fractal Intermittency-based Approach
SN - 978-989-758-197-7
AU - Paradisi, P.
AU - Righi, M.
AU - Barcaro, U.
PY - 2016
SP - 123
EP - 129
DO - 10.5220/0005998601230129

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