Publicaciones en las que colabora con Veronica Barroso Garcia (39)

2023

  1. Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals

    Diagnostics, Vol. 13, Núm. 20

2022

  1. Airflow Analysis in the Context of Sleep Apnea

    Advances in experimental medicine and biology, Vol. 1384, pp. 241-253

  2. Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea

    Advances in experimental medicine and biology, Vol. 1384, pp. 131-146

2021

  1. A Convolutional Neural Network Architecture to Enhance Oximetry Ability to Diagnose Pediatric Obstructive Sleep Apnea

    IEEE Journal of Biomedical and Health Informatics, Vol. 25, Núm. 8, pp. 2906-2916

  2. Bispectral analysis of heart rate variability to characterize and help diagnose pediatric sleep apnea

    Entropy, Vol. 23, Núm. 8

  3. Bispectral analysis of overnight airflow to improve the pediatric sleep apnea diagnosis

    Computers in Biology and Medicine, Vol. 129

  4. Erratum to: Martín-montero et al. bispectral analysis of heart rate variability to characterize and help diagnose pediatric sleep apnea. entropy 2021, 23, 1016

    Entropy

  5. Wavelet analysis of overnight airflow to detect obstructive sleep apnea in children

    Sensors, Vol. 21, Núm. 4, pp. 1-19

2020

  1. A machine learning-based test for adult sleep apnoea screening at home using oximetry and airflow

    Scientific Reports, Vol. 10, Núm. 1

  2. Análisis del flujo aéreo nocturno mediante wavelets para la ayuda en el diagnóstico de la apnea del sueño infantil

    XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica. CASEIB 2020: Libro de actas

  3. Assessment of nocturnal autonomic cardiac imbalance in positional obstructive sleep apnea. A multiscale nonlinear approach

    Entropy, Vol. 22, Núm. 12, pp. 1-17

  4. Characterization of the dynamic behavior of neural activity in Alzheimer's disease: Exploring the non-stationarity and recurrence structure of EEG resting-state activity

    Journal of Neural Engineering, Vol. 17, Núm. 1

  5. Modelo de deep learning basado en la arquitectura Inception para el diagnóstico de la apnea del sueño infantil mediante la señal de oximetría .

    XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica. CASEIB 2020: Libro de actas

  6. Usefulness of recurrence plots from airflow recordings to aid in paediatric sleep apnoea diagnosis

    Computer Methods and Programs in Biomedicine, Vol. 183

2019

  1. Characterization of EEG Resting-state Activity in Alzheimer's Disease by Means of Recurrence Plot Analyses

    Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

  2. Convolutional Neural Networks to Detect Pediatric Apnea-Hypopnea Events from Oximetry

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, Vol. 2019, pp. 3555-3558

  3. Evaluación de la información espectral de las señales de flujo aéreo y saturación de oxígeno en sangre para la ayuda al diagnóstico de la apnea del sueño infantil

    Hacia una salud personalizada y universal. XXXVII Congreso Anual de la Sociedad Española de Ingeniería Biomédica: Actas del Congreso CASEIB 2019

  4. Influence of chronic obstructive pulmonary disease and moderate-to-severe sleep apnoea in overnight cardiac autonomic modulation: Time, frequency and non-linear analyses

    Entropy, Vol. 21, Núm. 4

  5. Usefulness of Spectral Analysis of Respiratory Rate Variability to Help in Pediatric Sleep Apnea-Hypopnea Syndrome Diagnosis

    Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

  6. Utilidad de nuevas bandas espectrales en la señal de HRV para ayudar en el diagnóstico de la apnea del sueño infantil

    Hacia una salud personalizada y universal. XXXVII Congreso Anual de la Sociedad Española de Ingeniería Biomédica: Actas del Congreso CASEIB 2019