Characterization and Classification of Electrophysiological Signals Represented as Visibility Graphs Using the Maxclique Graph

Characterization and Classification of Electrophysiological Signals Represented as Visibility Graphs Using the Maxclique Graph

Detection, characterization and classification of patterns within time series from electrophysiological signals have been a challenge for neuroscientists due to their complexity and variability. Here, we aimed to use graph theory to characterize and classify waveforms within biological signals using...

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Bibliographic Details
Main Authors: Erika Elizabeth Rodriguez-Torres, Ulises Paredes-Hernandez, Enrique Vazquez-Mendoza, Margarita Tetlalmatzi-Montiel, Consuelo Morgado-Valle, Luis Beltran-Parrazal, Rafael Villarroel-Flores
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-04-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
visibility graphs
graph theory
maxcliques
electrophysiological signals
deep learning
pre-Bötzinger complex
Online Access:https://www.frontiersin.org/article/10.3389/fbioe.2020.00324/full

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https://www.frontiersin.org/article/10.3389/fbioe.2020.00324/full

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