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Usefulness of discrete wavelet transform in the analysis of oximetry signals to assist in childhood sleep apnea-hypopnea syndrome diagnosis.

, , , , , , , , и . EMBC, стр. 3753-3756. IEEE, (2017)

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Jutta Del Campo

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Genárìo Barbosa Campos

 

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Analysis and classification of oximetry recordings to predict obstructive sleep apnea severity in children., , , , , , , , и . EMBC, стр. 4540-4543. IEEE, (2015)Exploring the spectral information of airflow recordings to help in pediatric Obstructive Sleep Apnea-Hypopnea Syndrome diagnosis., , , , , и . EMBC, стр. 2298-2301. IEEE, (2014)Usefulness of discrete wavelet transform in the analysis of oximetry signals to assist in childhood sleep apnea-hypopnea syndrome diagnosis., , , , , , , , и . EMBC, стр. 3753-3756. IEEE, (2017)Utility of AdaBoost to Detect Sleep Apnea-Hypopnea Syndrome From Single-Channel Airflow., , , и . IEEE Trans. Biomed. Eng., 63 (3): 636-646 (2016)Automated Prediction of the Apnea-Hypopnea Index from Nocturnal Oximetry Recordings., , , , и . IEEE Trans. Biomed. Eng., 59 (1): 141-149 (2012)Diagnosis of pediatric obstructive sleep apnea: Preliminary findings using automatic analysis of airflow and oximetry recordings obtained at patients' home., , , , , и . Biomed. Signal Process. Control., (2015)Radial basis function classifiers to help in the diagnosis of the obstructive sleep apnoea syndrome from nocturnal oximetry., , , , , и . Medical Biol. Eng. Comput., 46 (4): 323-332 (2008)Machine learning for nocturnal diagnosis of chronic obstructive pulmonary disease using digital oximetry biomarkers., , , и . CoRR, (2020)An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea., , , , , , , и . Comput. Biol. Medicine, (октября 2023)Assessment of Airflow and Oximetry Signals to Detect Pediatric Sleep Apnea-Hypopnea Syndrome Using AdaBoost., , , , , , , , и . Entropy, 22 (6): 670 (2020)