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Unveiling the alterations in the frequency-dependent connectivity structure of MEG signals in mild cognitive impairment and Alzheimer’s disease

Rodríguez González, Víctor ; Núñez Novo, Pablo ; Gómez Peña, Carlos ; Hoshi, Hideyuki; Shigihara, Yoshihito; Hornero Sánchez, Roberto ; Poza Crespo, Jesús (2024)
An explainable deep-learning architecture for pediatric sleep apnea identification from overnight airflow and oximetry signals

Jimenez García, Jorge ; García Gadañón, María ; Gutierrez Tobal, Gonzalo César ; Kheirandish Gozal, Leila; Vaquerizo Villar, Fernando ; Álvarez González, Daniel ; Campo Matias, Félix del ; Gozal, David; Hornero Sánchez, Roberto (2024)
An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea

Vaquerizo Villar, Fernando ; Gutierrez Tobal, Gonzalo César ; Calvo, Eva; Álvarez González, 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 Vazquez, Eduardo ; Pérez Velasco, Sergio ; Marcos Martínez, Diego ; Moreno Calderón, Selene ; Hornero Sánchez, Roberto (2023)

Grupo de Ingeniería Biomédica: Envíos recientes

Unveiling the alterations in the frequency-dependent connectivity structure of MEG signals in mild cognitive impairment and Alzheimer’s disease ﻿

An explainable deep-learning architecture for pediatric sleep apnea identification from overnight airflow and oximetry signals ﻿

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 ﻿

Unveiling the alterations in the frequency-dependent connectivity structure of MEG signals in mild cognitive impairment and Alzheimer’s disease

An explainable deep-learning architecture for pediatric sleep apnea identification from overnight airflow and oximetry signals

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