A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific
"Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which results from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this infor...
Guardado en:
Autores principales: | Racca, Dora María, Quintero-Rincón, Antonio, Muro, Valeria, D'Giano, Carlos |
---|---|
Formato: | Póster |
Lenguaje: | Inglés |
Publicado: |
2019
|
Materias: | |
Acceso en línea: | http://ri.itba.edu.ar/handle/123456789/1603 |
Aporte de: |
Ejemplares similares
-
Statistical Model-Based Classification to Detect Patient-Specific Spike-and-Wave in EEG Signals
por: Quintero-Rincón, Antonio, et al.
Publicado: (2020) -
Spike-and-wave detection in epileptic signals using cross-correlation and decision trees
por: Quintero-Rincón, Antonio, et al.
Publicado: (2020) -
Study on epileptic seizure detection in EEG signals using largest Lyapunov exponents and logistic regression
por: Quintero-Rincón, Antonio, et al.
Publicado: (2020) -
Fast statistical model-based classification of epileptic EEG signals
por: Quintero-Rincón, Antonio, et al.
Publicado: (2019) -
Study on spike-and-wave detection in epileptic signals using T-location-scale distribution and the K-nearest neighbors classifier
por: Quintero-Rincón, Antonio, et al.
Publicado: (2019)