Cargando…
Optimizing Electrode Configurations for Wearable EEG Seizure Detection Using Machine Learning
Epilepsy, a prevalent neurological disorder, profoundly affects patients’ quality of life due to the unpredictable nature of seizures. The development of a reliable and user-friendly wearable EEG system capable of detecting and predicting seizures has the potential to revolutionize epilepsy care. Ho...
Autores principales: | Gelbard-Sagiv, Hagar, Pardo, Snir, Getter, Nir, Guendelman, Miriam, Benninger, Felix, Kraus, Dror, Shriki, Oren, Ben-Sasson, Shay |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346886/ https://www.ncbi.nlm.nih.gov/pubmed/37447653 http://dx.doi.org/10.3390/s23135805 |
Ejemplares similares
-
EEG-Based Prediction of Cognitive Load in Intelligence Tests
por: Friedman, Nir, et al.
Publicado: (2019) -
Perceptual shape sensitivity to upright and inverted faces is reflected in neuronal adaptation
por: Gilaie-Dotan, Sharon, et al.
Publicado: (2010) -
Wearable Reduced-Channel EEG System for Remote Seizure Monitoring
por: Frankel, Mitchell A., et al.
Publicado: (2021) -
Human single neuron activity precedes emergence of conscious perception
por: Gelbard-Sagiv, Hagar, et al.
Publicado: (2018) -
Selection of the optimal channel configuration for implementing wearable EEG devices for the diagnosis of mild cognitive impairment
por: Lee, Kyeonggu, et al.
Publicado: (2022)