RT info:eu-repo/semantics/article
T1 Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome
A1 Marcos, J. Víctor
A1 Hornero Sánchez, Roberto
A1 Nabney, Ian T.
A1 Álvarez González, Daniel
A1 Gutiérrez Tobal, Gonzalo César
A1 Campo Matias, Félix del
K1 Oxygen saturation
AB The relationship between sleep apnoea–hypopnoea syndrome (SAHS) severity and the regularity of noctur- nal oxygen saturation (SaO 2 ) 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 sub- jects 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 corre- lation 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 mea- surements 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.
PB Elsevier
SN 1350-4533
YR 2016
FD 2016
LK http://uvadoc.uva.es/handle/10324/21594
UL http://uvadoc.uva.es/handle/10324/21594
LA eng
NO Medical Engineering and Physics 38 (2016) 216–224
NO Producción Científica
DS UVaDOC
RD 28-abr-2024