Classification of Normal, Ictal and Inter-ictal EEG via Direct Quadrature and Random Forest Tree

This paper presents an accurate nonlinear classification method that can help physicians diagnose seizure in electroencephalographic (EEG) signal characterized by a disturbance in temporal and spectral content. This is accomplished by applying four steps. First, different EEG signals containing heal...

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Detalles Bibliográficos
Autores principales: Abdulhay, Enas, Alafeef, Maha, Abdelhay, Arwa, Al-Bashir, Areen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2017
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840222/
https://www.ncbi.nlm.nih.gov/pubmed/29541014
http://dx.doi.org/10.1007/s40846-017-0239-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840222/
https://www.ncbi.nlm.nih.gov/pubmed/29541014
http://dx.doi.org/10.1007/s40846-017-0239-z

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