Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis

Annu Int Conf IEEE Eng Med Biol Soc. 2011:2011:1745-8. doi: 10.1109/IEMBS.2011.6090499.

Abstract

In this study, a new entropy measure known as kernel entropy (KerEnt), which quantifies the irregularity in a series, was applied to nocturnal oxygen saturation (SaO(2)) recordings. A total of 96 subjects suspected of suffering from sleep apnea-hypopnea syndrome (SAHS) took part in the study: 32 SAHS-negative and 64 SAHS-positive subjects. Their SaO(2) signals were separately processed by means of KerEnt. Our results show that a higher degree of irregularity is associated to SAHS-positive subjects. Statistical analysis revealed significant differences between the KerEnt values of SAHS-negative and SAHS-positive groups. The diagnostic utility of this parameter was studied by means of receiver operating characteristic (ROC) analysis. A classification accuracy of 81.25% (81.25% sensitivity and 81.25% specificity) was achieved. Repeated apneas during sleep increase irregularity in SaO(2) data. This effect can be measured by KerEnt in order to detect SAHS. This non-linear measure can provide useful information for the development of alternative diagnostic techniques in order to reduce the demand for conventional polysomnography (PSG).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computer Simulation
  • Diagnosis, Computer-Assisted / methods*
  • Entropy
  • Female
  • Humans
  • Middle Aged
  • Models, Biological*
  • Models, Statistical
  • Oximetry / methods*
  • Oxygen / blood*
  • Polysomnography / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Sleep Apnea Syndromes / blood*
  • Sleep Apnea Syndromes / diagnosis*

Substances

  • Oxygen