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An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea

Vaquerizo Villar, Fernando ; Gutiérrez Tobal, Gonzalo César; Calvo, Eva; Álvarez, Daniel; Kheirandish Gozal, Leila; Campo Matias, Félix del ; Hornero Sánchez, Roberto (2023)
Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses

Rodríguez González, Víctor ; Núñez Novo, Pablo ; Gómez Peña, Carlos ; Shigihara, Yoshihito; Hoshi, Hideyuki; Tola Arribas, Miguel Ángel ; Cano, Mónica; Guerrero Peral, Angel Luis ; García Azorín, David; Hornero Sánchez, Roberto ; Poza Crespo, Jesús (2023)
Non-binary m-sequences for more comfortable brain–computer interfaces based on c-VEPs

Martínez Cagigal, Víctor ; Santamaría Vázquez, Eduardo; Pérez Velasco, Sergio; Marcos Martínez, Diego; Moreno Calderón, Selene; Hornero Sánchez, Roberto (2023)
Exploring the alterations in the distribution of neural network weights in dementia due to alzheimer’s disease

Revilla Vallejo, Marcos; Poza Crespo, Jesús ; Gómez Pilar, Javier; Hornero Sánchez, Roberto ; Tola Arribas, Miguel Ángel ; Cano, Mónica; Gómez Peña, Carlos (2021)
ITACA: An open-source framework for Neurofeedback based on Brain-Computer Interfaces

Marcos Martínez, Diego; Santamaría Vázquez, Eduardo; Martínez Cagigal, Víctor ; Pérez Velasco, Sergio; Rodríguez González, Víctor ; Martín Fernández, Ana; Moreno Calderón, Selene; Hornero Sánchez, Roberto (2023)

Grupo de Ingeniería Biomédica: Envíos recientes

An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea ﻿

Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses ﻿

Non-binary m-sequences for more comfortable brain–computer interfaces based on c-VEPs ﻿

Exploring the alterations in the distribution of neural network weights in dementia due to alzheimer’s disease ﻿

ITACA: An open-source framework for Neurofeedback based on Brain-Computer Interfaces ﻿

An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea

Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses

Non-binary m-sequences for more comfortable brain–computer interfaces based on c-VEPs

Exploring the alterations in the distribution of neural network weights in dementia due to alzheimer’s disease

ITACA: An open-source framework for Neurofeedback based on Brain-Computer Interfaces