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00925njm 22002777a 4500 dc Álvarez González, Daniel author Gutierrez Tobal, Gonzalo César author Alonso Álvarez, María Luz author Terán Santos, Joaquín author Campo Matias, Félix del author Hornero Sánchez, Roberto author 2014 Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a sleep related breathing disorder that has important consequences in the health and development of infants and young children. To enhance the early detection of OSAHS, we propose a methodology based on automated analysis of nocturnal blood oxygen saturation (SpO2) from respiratory polygraphy (RP) at home. A database composed of 50 SpO2 recordings was analyzed. Three signal processing stages were carried out: (i) feature extraction, where statistical features and nonlinear measures were computed and combined with conventional oximetric indexes, (ii) feature selection using genetic algorithms (GAs), and (iii) feature classification through logistic regression (LR). Leave-one-out cross-validation (loo-cv) was applied to assess diagnostic performance. The proposed method reached 80.8% sensitivity, 79.2% specificity, 80.0% accuracy and 0.93 area under the ROC curve (AROC), which improved the performance of single conventional indexes. Our results suggest that automated analysis of SpO2 recordings from at-home RP provides essential and complementary information to assist in OSAHS diagnosis in children. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014, v. 2014, p. 1860-3 1557-170X http://uvadoc.uva.es/handle/10324/21714 10.1109/EMBC.2014.6943972 2014 Sleep Apnea in Children Statistical and Nonlinear Analysis of Oximetry from Respiratory Polygraphy to Assist in the Diagnosis of Sleep Apnea in Children