Application of the Lomb-Scargle Periodogram to Investigate Heart Rate Variability during Haemodialysis
Eldehni, Mohamed T
Selby, Nicholas M
Taal, Maarten W
MetadataShow full item record
AbstractShort-term cardiovascular compensatory responses to perturbations in the circulatory system caused by haemodialysis can be investigated by the spectral analysis of heart rate variability, thus providing an important variable for categorising individual patients' response, leading to a more personalised treatment. This is typically accomplished by resampling the irregular heart rate to generate an equidistant time series prior to spectral analysis, but resampling can further distort the data series whose interpretation can already be compromised by the presence of artefacts. The Lomb-Scargle periodogram provides a more direct method of spectral analysis as this method is specifically designed for large, irregularly sampled, and noisy datasets such as those obtained in clinical settings. However, guidelines for preprocessing patient data have been established in combination with equidistant time-series methods and their validity when used in combination with the Lomb-Scargle approach is missing from literature. This paper examines the effect of common preprocessing methods on the Lomb-Scargle power spectral density estimate using both real and synthetic heart rate data and will show that many common techniques for identifying and editing suspect data points, particularly interpolation and replacement, will distort the resulting power spectrum potentially misleading clinical interpretations of the results. Other methods are proposed and evaluated for use with the Lomb-Scargle approach leading to the main finding that suspicious data points should be excluded rather than edited, and where required, denoising of the heart rate signal can be reliably accomplished by empirical mode decomposition. Some additional methods were found to be particularly helpful when used in conjunction with the Lomb-Scargle periodogram, such as the use of a false alarm probability metric to establish whether spectral estimates are valid and help automate the assessment of valid heart rate records, potentially leading to greater use of this powerful technique in a clinical setting.
CitationStewart J, Stewart P, Walker T, Gullapudi L, Eldehni MT, Selby NM, Taal MW. (2020). ‘Application of the Lomb-Scargle Periodogram to Investigate Heart Rate Variability during Haemodialysis'. Journal of Healthcare Engineering, pp. 1-18.
JournalJournal of healthcare engineering
- Quantifying errors in spectral estimates of HRV due to beat replacement and resampling.
- Authors: Clifford GD, Tarassenko L
- Issue date: 2005 Apr
- Spectral estimation in unevenly sampled space of periodically expressed microarray time series data.
- Authors: Liew AW, Xian J, Wu S, Smith D, Yan H
- Issue date: 2007 Apr 24
- Emphasizing difficulties in the detection of rhythms with Lomb-Scargle periodograms.
- Authors: Schimmel M
- Issue date: 2001 Jul
- Searching for biological rhythms: peak detection in the periodogram of unequally spaced data.
- Authors: Van Dongen HP, Olofsen E, VanHartevelt JH, Kruyt EW
- Issue date: 1999 Dec
- Detecting periodic patterns in unevenly spaced gene expression time series using Lomb-Scargle periodograms.
- Authors: Glynn EF, Chen J, Mushegian AR
- Issue date: 2006 Feb 1