Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome
| Autor: | Daniel Álvarez, Félix del Campo, Roberto Hornero, Ian T. Nabney, J. Víctor Marcos, Gonzalo C. Gutiérrez-Tobal |
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| Rok vydání: | 2016 |
| Předmět: |
Male
Correlation coefficient Entropy Oxygen saturation 0206 medical engineering Biomedical Engineering Biophysics 02 engineering and technology Nocturnal Approximate entropy 03 medical and health sciences symbols.namesake Sleep apnoea syndrome Sleep Apnea Syndromes 0302 clinical medicine oxygen saturation entropy rate approximate entropy sample entropy kernel entropy density estimation Statistics Humans Medicine Oximetry Entropy rate Receiver operating characteristic business.industry Signal Processing Computer-Assisted Middle Aged 020601 biomedical engineering Pearson product-moment correlation coefficient nervous system diseases Oxygen Sample entropy symbols Female business 030217 neurology & neurosurgery |
| Zdroj: | Marcos, J V, Hornero, R, Nabney, I T, Álvarez, D, Gutiérrez-Tobal, G C & del Campo, F 2016, ' Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome ', Medical Engineering and Physics, vol. 38, no. 3, pp. 216-224 . https://doi.org/10.1016/j.medengphy.2015.11.010 UVaDOC. Repositorio Documental de la Universidad de Valladolid instname |
| ISSN: | 1873-4030 |
| DOI: | 10.1016/j.medengphy.2015.11.010 |
| Popis: | Producción Científica 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. Junta de Castilla y León (project VA059U13) Ministerio de Economía y Competitividad (project TEC 2011–22987) |
| Databáze: | OpenAIRE |
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