Cargando…
Compressibility of High-Density EEG Signals in Stroke Patients
Stroke is a critical event that causes the disruption of neural connections. There is increasing evidence that the brain tries to reorganize itself and to replace the damaged circuits, by establishing compensatory pathways. Intra- and extra-cellular currents are involved in the communication between...
Autores principales: | Mammone, Nadia, De Salvo, Simona, Ieracitano, Cosimo, Marino, Silvia, Cartella, Emanuele, Bramanti, Alessia, Giorgianni, Roberto, Morabito, Francesco C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308673/ https://www.ncbi.nlm.nih.gov/pubmed/30477168 http://dx.doi.org/10.3390/s18124107 |
Ejemplares similares
-
Permutation Entropy-Based Interpretability of Convolutional Neural Network Models for Interictal EEG Discrimination of Subjects with Epileptic Seizures vs. Psychogenic Non-Epileptic Seizures
por: Lo Giudice, Michele, et al.
Publicado: (2022) -
A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls
por: Varone, Giuseppe, et al.
Publicado: (2021) -
Information Theoretic-Based Interpretation of a Deep Neural Network Approach in Diagnosing Psychogenic Non-Epileptic Seizures
por: Gasparini, Sara, et al.
Publicado: (2018) -
Neurophysiological assessment in a patient affected by Marfan syndrome
por: Cartella, Emanuele, et al.
Publicado: (2020) -
Quantitative assessment of Parkinsonian tremor by using biosensor device
por: Marino, Silvia, et al.
Publicado: (2019)