| Revue: | Revista mexicana de física |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000447132 |
| ISSN: | 0035-001X |
| Autores: | Guarneros, G1 Pérez, C1 Montiel, A1 Rojas, J.F1 |
| Instituciones: | 1Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias Físico-Matemáticas, Puebla. México |
| Año: | 2021 |
| Periodo: | Mar-Abr |
| Volumen: | 67 |
| Número: | 2 |
| Paginación: | 324-333 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico, descriptivo |
| Resumen en inglés | In the study of problems related to epilepsy, analyzing electroencephalographic data is of much importance help to, e.g., diagnose and to diminish errors in surgery. In this work, we present an analysis via the construction of Feigenbaum graphs by using real electroencephalographic signals data sets and calculating characteristic network (graph) quantities, such as average clustering, degree distribution, and average shortest path length. By using this method, we manage to characterize two different data sets from each other, from data sets corresponding to focal and non-focal neuronal activity both recorded out of an epileptic seizure. This method makes it possible to identify sets of data from epileptic focal zones, and we suggest that this approach could be used to aid physicians in diagnosing epilepsy from electroencephalographic data and in the exact establishment of the epileptic focal region for surgery |
| Disciplinas: | Física y astronomía |
| Palabras clave: | Física, Electroencefalograma, Epilepsia, Métodos de estadística física, Gráficas de Feigenbaum, Gráficas de visibilidad |
| Keyword: | Physics, Electroencephalogram, Epilepsy, Statistical physics methods, Feigenbaum graphs, Visibility graph |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
