Publikationen in Zusammenarbeit mit Forschern von University of Missouri (41)

2024

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

    Biomedical Signal Processing and Control, Vol. 87

  2. Persistent sleep-disordered breathing independently contributes to metabolic syndrome in prepubertal children

    Pediatric Pulmonology, Vol. 59, Núm. 1, pp. 111-120

2023

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

    Computers in Biology and Medicine, Vol. 165

  2. Editorial: Unraveling sleep and its disorders using novel analytical approaches, volume II

    Frontiers in Neuroscience

  3. Pediatric sleep apnea: Characterization of apneic events and sleep stages using heart rate variability

    Computers in Biology and Medicine, Vol. 154

  4. Validation of a predictive model for obstructive sleep apnea in people with Down syndrome

    American Journal of Medical Genetics, Part A, Vol. 191, Núm. 2, pp. 518-525

2022

  1. A 2D convolutional neural network to detect sleep apnea in children using airflow and oximetry

    Computers in biology and medicine, Vol. 147, pp. 105784

  2. A convolutional neural network to classify sleep stages in pediatric sleep apnea from pulse oximetry signals

    MELECON 2022 - IEEE Mediterranean Electrotechnical Conference, Proceedings

  3. Characterization of Changes in HRV Metrics During Sleep Apnea Episodes in Pediatric Patients

    2022 12th Conference of the European Study Group on Cardiovascular Oscillations, ESGCO 2022

  4. Editorial: Unraveling Sleep and Its Disorders Using Novel Analytical Approaches

    Frontiers in Neuroscience

  5. Heart rate variability as a potential biomarker of pediatric obstructive sleep apnea resolution

    Sleep, Vol. 45, Núm. 2

  6. On gluing semigroups in Nn and the consequences

    Research in Mathematical Sciences, Vol. 9, Núm. 2

  7. Reliability of machine learning to diagnose pediatric obstructive sleep apnea: Systematic review and meta-analysis

    Pediatric Pulmonology, Vol. 57, Núm. 8, pp. 1931-1943

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. Ensemble-learning regression to estimate sleep apnea severity using at-home oximetry in adults

    Applied Soft Computing, Vol. 111

  5. 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

  6. Heart rate variability spectrum characteristics in children with sleep apnea

    Pediatric Research, Vol. 89, Núm. 7, pp. 1771-1779

  7. Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker

    Frontiers in Neuroscience, Vol. 15