Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome

Research output: Contribution to journalArticle

View graph of relations Save citation

Open

Authors

Research units

Abstract

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.

Documents

Details

Original languageEnglish
Pages (from-to)216-224
Number of pages9
JournalMedical Engineering and Physics
Volume38
Issue3
Early online date21 Dec 2015
DOIs
StatePublished - Mar 2016

Bibliographic note

© 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

    Keywords

  • oxygen saturation, entropy rate, approximate entropy, sample entropy, kernel entropy, density estimation

DOI

Employable Graduates; Exploitable Research

Copy the text from this field...