Electrocardiogram based evaluation of children with sleep related upper airway obstruction

A. Baharav, Z. Shinar, Y. Sivan, M. Greenfeld, S. Akselrod

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Sleep disordered breathing became an important health issue. It remains under diagnosed due the complexity and cost of the standard overnight polysomnography. The ECG signal contains important information concerning sleep and autonomic function. In the present study we reassessed the behavior of several HRV parameters during sleep stages. In addition we developed an algorithm, able to discriminate between different sleep stages. This classification algorithm was based on phase space of HRV parameters that have proved to be significantly different between different sleep stages in children with sleep related breathing disorder and in normal children. The algorithm was then validated on 21 children using the "leave-one-out" technique. The sensitivity of the classification was 59%-69% for different sleep stages, and its specificity between 51%-66%. The overall accuracy was 66%, less than inter-expert agreement and better than automatic PSG analysis.

Original languageEnglish
Pages (from-to)289-292
Number of pages4
JournalComputers in Cardiology
Volume31
StatePublished - 2004
Externally publishedYes
EventComputers in Cardiology 2004 - Chicago, IL, United States
Duration: 19 Sep 200422 Sep 2004

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