Cargando…
Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using k-NN Classifier
Electroencephalographic signal is a representative signal that contains information about brain activity, which is used for the detection of epilepsy since epileptic seizures are caused by a disturbance in the electrophysiological activity of the brain. The prediction of epileptic seizure usually re...
Autores principales: | Hasan, Md. Kamrul, Ahamed, Md. Asif, Ahmad, Mohiuddin, Rashid, M. A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5574243/ https://www.ncbi.nlm.nih.gov/pubmed/28894351 http://dx.doi.org/10.1155/2017/6848014 |
Ejemplares similares
-
Optimized Seizure Detection Algorithm: A Fast Approach for Onset of Epileptic in EEG Signals Using GT Discriminant Analysis and K-NN Classifier
por: Rezaee, Kh., et al.
Publicado: (2016) -
Ensemble Classifier for Epileptic Seizure Detection for Imperfect EEG Data
por: Abualsaud, Khalid, et al.
Publicado: (2015) -
Epileptic seizure detection with deep EEG features by convolutional neural network and shallow classifiers
por: Zeng, Wei, et al.
Publicado: (2023) -
Fuzzy k-NN Based Classifiers for Time Series with Soft Labels
por: Wagner, Nicolas, et al.
Publicado: (2020) -
A DM-ELM based classifier for EEG brain signal classification for epileptic seizure detection
por: Mishra, Shruti, et al.
Publicado: (2022)