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

, , , , , , , and . Comput. Biol. Medicine, (October 2023)

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Utility of Approximate Entropy From Overnight Pulse Oximetry Data in the Diagnosis of the Obstructive Sleep Apnea Syndrome., , , , and . IEEE Trans. Biomed. Eng., 54 (1): 107-113 (2007)A Domotic Control System Using Brain-Computer Interface (BCI)., , and . IWANN (1), volume 6691 of Lecture Notes in Computer Science, page 345-352. Springer, (2011)Bispectral analysis of overnight airflow to improve the pediatric sleep apnea diagnosis., , , , , , , and . Comput. Biol. Medicine, (2021)EEG Dataset Collection for Mental Workload Predictions in Flight-Deck Environment., , , , and . Sensors, 24 (4): 1174 (February 2024)Automated detection of obstructive sleep apnoea syndrome from oxygen saturation recordings using linear discriminant analysis., , , , and . Medical Biol. Eng. Comput., 48 (9): 895-902 (2010)A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea., , , , , , , and . EMBC, page 1-4. IEEE, (2023)Adaptive semi-supervised classification to reduce intersession non-stationarity in multiclass motor imagery-based brain-computer interfaces., , , , and . Neurocomputing, (2015)Automated analysis of nocturnal oximetry as screening tool for childhood obstructive sleep apnea-hypopnea syndrome., , , , , , , , and . EMBC, page 2800-2803. IEEE, (2015)Apnea-hypopnea index estimation from spectral analysis of airflow recordings., , , , , and . EMBC, page 3444-3447. IEEE, (2012)Utility of multilayer perceptron neural network classifiers in the diagnosis of the obstructive sleep apnoea syndrome from nocturnal oximetry., , , , , and . Comput. Methods Programs Biomed., 92 (1): 79-89 (2008)