Á. Huerta

Application of Deep Learning for Quality Assessment of Atrial Fibrillation ECG Recordings

P. Langley, J. J. Rieta, R. Alcaraz, 2020, 2020 Computing in Cardiology.

A Deep Learning Solution for Automatized Interpretation of 12-Lead ECGs

J. J. Rieta, R. Alcaraz, A. Martínez-Rodrigo, 2020, Computers in cardiology.

Detection of Negative Stress through Spectral Features of Electroencephalographic Recordings and a Convolutional Neural Network

Raúl Alcaraz, Arturo Martínez-Rodrigo, Beatriz García-Martínez, 2021, Sensors.

ECG Quality Assessment via Deep Learning and Data Augmentation

J. J. Rieta, R. Alcaraz, A. Martínez-Rodrigo, 2021, 2021 Computing in Cardiology (CinC).

Comparison of Supervised Learning Algorithms for Quality Assessment of Wearable Electrocardiograms With Paroxysmal Atrial Fibrillation

J. J. Rieta, R. Alcaraz, Á. Huerta, 2023, IEEE Access.

Single-lead electrocardiogram quality assessment in the context of paroxysmal atrial fibrillation through phase space plots

J. J. Rieta, R. Alcaraz, A. Martínez-Rodrigo, 2024, Biomedical Signal Processing and Control.

Quality Assessment of Very Long-Term ECG Recordings Using a Convolutional Neural Network

J.J. Rieta, A. Huerta, A. Martínez-Rodrigo, 2019, 2019 E-Health and Bioengineering Conference (EHB).