Nanopower Integrated Gaussian Mixture Model Classifier for Epileptic Seizure Prediction

This paper presents a new analog front-end classification system that serves as a wake-up engine for digital back-ends, targeting embedded devices for epileptic seizure prediction. Predicting epileptic seizures is of major importance for the patient’s quality of life as they can lead to paralyzation...

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Detalles Bibliográficos
Autores principales: Alimisis, Vassilis, Gennis, Georgios, Touloupas, Konstantinos, Dimas, Christos, Uzunoglu, Nikolaos, Sotiriadis, Paul P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028754/
https://www.ncbi.nlm.nih.gov/pubmed/35447720
http://dx.doi.org/10.3390/bioengineering9040160

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028754/
https://www.ncbi.nlm.nih.gov/pubmed/35447720
http://dx.doi.org/10.3390/bioengineering9040160

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