2019/02/07 by Gabriel Guarneros B., B Gabriel Guarneros, Cristian Pérez A. +8
Biochemistry, Genetics and Molecular Biology · Neuroscience · Physics and Astronomy · #Biological Physics (physics.bio-ph) #EEG and Brain-Computer Interfaces #FOS: Biological sciences #FOS: Physical sciences #Functional Brain Connectivity Studies #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #physics.bio-ph #q-bio.NC
paper · pdf · doi:10.48550/arxiv.1902.02750
arxiv created 2019/02/07 · openalex publication_date 2019/02/07 · arxiv updated 2019/02/08 · openalex created_date 2019/02/21 · openalex updated_date 2026/07/28
Diagnosing epilepsy is a problem of crucial importance. So analysing EEG data is of much importance to help this diagnosis. Assembling the Feigenbaum graphs for EEG signals. And calculating their average clustering, average degree, and average shortest path length. We manage to characterize two different data sets from each other. Each data set consisted of focal and non-focal activity, from where epileptic regions could be identified. This method yields good results for identifying sets of data from epileptic zones. Suggesting our approach could be used to aid physicians with diagnosing epilepsy from EEG data.