Surrogate Data Method Requires End-Matched Segmentation of Electroencephalographic Signals to Estimate Non-linearity

The aim of the study is to clarify the impact of the strong cyclic signal component on the results of surrogate data method in the case of resting electroencephalographic (EEG) signals. In addition, the impact of segment length is analyzed. Different non-linear measures (fractality, complexity, etc....

Descripción completa

Detalles Bibliográficos
Autores principales: Päeske, Laura, Bachmann, Maie, Põld, Toomas, de Oliveira, Sara Pereira Mendes, Lass, Jaanus, Raik, Jaan, Hinrikus, Hiie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6170787/
https://www.ncbi.nlm.nih.gov/pubmed/30319451
http://dx.doi.org/10.3389/fphys.2018.01350

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6170787/
https://www.ncbi.nlm.nih.gov/pubmed/30319451
http://dx.doi.org/10.3389/fphys.2018.01350

Ejemplares similares