Fernando Vaquerizo-Villar1, Daniel Álvarez2, Leila Kheirandish-Gozal3, Gonzalo César Gutiérrez-Tobal4, Verónica Barroso-García4, Andrea Crespo2, Félix Del Campo2, David Gozal3, Roberto Hornero5. 1. Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain. Electronic address: fernando.vaquerizo@gib.tel.uva.es. 2. Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain; Servicio de Neumología, Hospital Universitario Rio Hortega, Valladolid, Spain. 3. Dept. of Pediatrics, Pritzker School of Medicine, Biological Sciences Division, The University of Chicago, Chicago, United States of America. 4. Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain. 5. Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain; IMUVA, Instituto de Investigación en Matemáticas, Universidad de Valladolid, Valladolid, Spain.
Abstract
BACKGROUND AND OBJECTIVE: The aim of this study was to assess the utility of bispectrum-based oximetry approaches as a complementary tool to traditional techniques in the screening of pediatric sleep apnea-hypopnea syndrome (SAHS). METHODS: 298 blood oxygen saturation (SpO2) signals from children ranging 0-13 years of age were recorded during overnight polysomnography (PSG). These recordings were divided into three severity groups according to the PSG-derived apnea hypopnea index (AHI): AHI < 5 events per hour (e/h), 5 ≤ AHI < 10 e/h, AHI ≥ 10 e/h. For each pediatric subject, anthropometric variables, 3% oxygen desaturation index (ODI3) and spectral features from power spectral density (PSD) and bispectrum were obtained. Then, the fast correlation-based filter (FCBF) was applied to select a subset of relevant features that may be complementary, excluding those that are redundant. The selected features fed a multiclass multi-layer perceptron (MLP) neural network to build a model to estimate the SAHS severity degrees. RESULTS: An optimum subset with features from all the proposed methodological approaches was obtained: variables from bispectrum, as well as PSD, ODI3, Age, and Sex. In the 3-class classification task, the MLP model trained with these features achieved an accuracy of 76.0% and a Cohen's kappa of 0.56 in an independent test set. Additionally, high accuracies were reached using the AHI cutoffs for diagnosis of moderate (AHI = 5 e/h) and severe (AHI = 10 e/h) SAHS: 81.3% and 85.3%, respectively. These results outperformed the diagnostic ability of a MLP model built without using bispectral features. CONCLUSIONS: Our results suggest that bispectrum provides additional information to anthropometric variables, ODI3 and PSD regarding characterization of changes in the SpO2 signal caused by respiratory events. Thus, oximetry bispectrum can be a useful tool to provide complementary information for screening of moderate-to-severe pediatric SAHS.
BACKGROUND AND OBJECTIVE: The aim of this study was to assess the utility of bispectrum-based oximetry approaches as a complementary tool to traditional techniques in the screening of pediatric sleep apnea-hypopnea syndrome (SAHS). METHODS: 298 blood oxygen saturation (SpO2) signals from children ranging 0-13 years of age were recorded during overnight polysomnography (PSG). These recordings were divided into three severity groups according to the PSG-derived apnea hypopnea index (AHI): AHI < 5 events per hour (e/h), 5 ≤ AHI < 10 e/h, AHI ≥ 10 e/h. For each pediatric subject, anthropometric variables, 3% oxygen desaturation index (ODI3) and spectral features from power spectral density (PSD) and bispectrum were obtained. Then, the fast correlation-based filter (FCBF) was applied to select a subset of relevant features that may be complementary, excluding those that are redundant. The selected features fed a multiclass multi-layer perceptron (MLP) neural network to build a model to estimate the SAHS severity degrees. RESULTS: An optimum subset with features from all the proposed methodological approaches was obtained: variables from bispectrum, as well as PSD, ODI3, Age, and Sex. In the 3-class classification task, the MLP model trained with these features achieved an accuracy of 76.0% and a Cohen's kappa of 0.56 in an independent test set. Additionally, high accuracies were reached using the AHI cutoffs for diagnosis of moderate (AHI = 5 e/h) and severe (AHI = 10 e/h) SAHS: 81.3% and 85.3%, respectively. These results outperformed the diagnostic ability of a MLP model built without using bispectral features. CONCLUSIONS: Our results suggest that bispectrum provides additional information to anthropometric variables, ODI3 and PSD regarding characterization of changes in the SpO2 signal caused by respiratory events. Thus, oximetry bispectrum can be a useful tool to provide complementary information for screening of moderate-to-severe pediatric SAHS.
Authors: Daniel Álvarez; Gonzalo C Gutiérrez-Tobal; Fernando Vaquerizo-Villar; Fernando Moreno; Félix Del Campo; Roberto Hornero Journal: Adv Exp Med Biol Date: 2022 Impact factor: 3.650
Authors: Fernando Vaquerizo-Villar; Daniel Alvarez; Leila Kheirandish-Gozal; Gonzalo C Gutierrez-Tobal; Veronica Barroso-Garcia; Eduardo Santamaria-Vazquez; Felix Del Campo; David Gozal; Roberto Hornero Journal: IEEE J Biomed Health Inform Date: 2021-08-05 Impact factor: 7.021
Authors: Fernando Vaquerizo-Villar; Daniel Álvarez; Leila Kheirandish-Gozal; Gonzalo C Gutiérrez-Tobal; Verónica Barroso-García; Andrea Crespo; Félix Del Campo; David Gozal; Roberto Hornero Journal: PLoS One Date: 2018-12-07 Impact factor: 3.240