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oai:uvadoc.uva.es:10324/655982025-02-24T10:04:26Zcom_10324_1191com_10324_931com_10324_894col_10324_1379

00925njm 22002777a 4500 dc Marcos Martín, José Víctor author Hornero Sánchez, Roberto author Nabney, Ian T. author Álvarez González, Daniel author Gutierrez Tobal, Gonzalo César author Campo Matias, Félix del author 2016 The relationship between sleep apnoea–hypopnoea syndrome (SAHS) severity and the regularity of nocturnal oxygen saturation (SaO2) recordings was analysed. Three different methods were proposed to quantify regularity: approximate entropy (AEn), sample entropy (SEn) and kernel entropy (KEn). A total of 240 subjects suspected of suffering from SAHS took part in the study. They were randomly divided into a training set (96 subjects) and a test set (144 subjects) for the adjustment and assessment of the proposed methods, respectively. According to the measurements provided by AEn, SEn and KEn, higher irregularity of oximetry signals is associated with SAHS-positive patients. Receiver operating characteristic (ROC) and Pearson correlation analyses showed that KEn was the most reliable predictor of SAHS. It provided an area under the ROC curve of 0.91 in two-class classification of subjects as SAHS-negative or SAHS-positive. Moreover, KEn measurements from oximetry data exhibited a linear dependence on the apnoea hypopnoea index, as shown by a correlation coefficient of 0.87. Therefore, these measurements could be used for the development of simplified diagnostic techniques in order to reduce the demand for polysomnographies. Furthermore, KEn represents a convincing alternative to AEn and SEn for the diagnostic analysis of noisy biomedical signals. Medical Engineering & Physics, 2016, vol. 38, n. 3, p. 216-224. 1350-4533 https://uvadoc.uva.es/handle/10324/65598 10.1016/j.medengphy.2015.11.010 216 3 224 Medical Engineering & Physics 38 Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome