Literature DB >> 10723884

Evaluation of frequency and time-frequency spectral analysis of heart rate variability as a diagnostic marker of the sleep apnoea syndrome.

M F Hilton1, R A Bates, K R Godfrey, M J Chappell, R M Cayton.   

Abstract

The sleep apnoea/hypopnoea syndrome (SAHS) elicits a unique heart rate rhythm that may provide the basis for an effective screening tool. The study uses the receiver operator characteristic (ROC) to assess the diagnostic potential of spectral analysis of heart rate variability (HRV) using two methods, the discrete Fourier transform (DFT) and the discrete harmonic wavelet transform (DHWT). These two methods are compared over different sleep stages and spectral frequency bands. The HRV results are subsequently compared with those of the current screening method of oximetry. For both the DFT and the DHWT, the most diagnostically accurate frequency range for HRV spectral power calculations is found to be 0.019-0.036 Hz (denoted by AB2). Using AB2, 15 min sections of non-REM sleep data in 40 subjects produce ROC areas, for the DFT, DHWT and oximetry, of 0.94, 0.97 and 0.67, respectively. In REM sleep, ROC areas are 0.78, 0.79 and 0.71, respectively. In non-REM sleep, spectral analysis of HRV appears to be a significantly better indicator of the SAHS than the current screening method of oximetry, and, in REM sleep, it is comparable with oximetry. The advantage of the DHWT over the DFT is that it produces a greater time resolution and is computationally more efficient. The DHWT does not require the precondition of stationarity or interpolation of raw HRV data.

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Year:  1999        PMID: 10723884     DOI: 10.1007/bf02513379

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  32 in total

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Journal:  Sleep       Date:  1996-06       Impact factor: 5.849

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Journal:  Lancet       Date:  1984-01-21       Impact factor: 79.321

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  6 in total

1.  A novel recursive Fourier transform for nonuniform sampled signals: application to heart rate variability spectrum estimation.

Authors:  Alexander Holland; Mateo Aboy
Journal:  Med Biol Eng Comput       Date:  2009-02-27       Impact factor: 2.602

2.  Robust spectral analysis of thoraco-abdominal motion and oxymetry in obstructive sleep apnea.

Authors:  Cesar L Nino; Carlos E Rodriguez-Martinez; Maria J Gutierrez; Ravi Singareddi; Gustavo Nino
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2013

3.  Heart rate regularity analysis obtained from pulse oximetric recordings in the diagnosis of obstructive sleep apnea.

Authors:  C Zamarrón; R Hornero; F del Campo; D Abásolo; D Alvarez
Journal:  Sleep Breath       Date:  2006-06       Impact factor: 2.816

4.  Systematic comparison of different algorithms for apnoea detection based on electrocardiogram recordings.

Authors:  T Penzel; J McNames; A Murray; P de Chazal; G Moody; B Raymond
Journal:  Med Biol Eng Comput       Date:  2002-07       Impact factor: 2.602

5.  Heart rate variability analysis during central hypovolemia using wavelet transformation.

Authors:  Soo-Yeon Ji; Ashwin Belle; Kevin R Ward; Kathy L Ryan; Caroline A Rickards; Victor A Convertino; Kayvan Najarian
Journal:  J Clin Monit Comput       Date:  2013-02-01       Impact factor: 2.502

6.  Comparison of two systems for long-term heart rate variability monitoring in free-living conditions--a pilot study.

Authors:  Jesper Kristiansen; Mette Korshøj; Jørgen H Skotte; Tobias Jespersen; Karen Søgaard; Ole S Mortensen; Andreas Holtermann
Journal:  Biomed Eng Online       Date:  2011-04-12       Impact factor: 2.819

  6 in total

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