Application of the Lomb-Scargle Periodogram to InvestigateHeart Rate Variability during Haemodialysis

Joint Authors

Stewart, Jill
Stewart, Paul
Walker, Tom
Gullapudi, Latha
Eldehni, Mohamed T.
Selby, Nicholas M.
Taal, Maarten W.

Source

Journal of Healthcare Engineering

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-18, 18 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-08

Country of Publication

Egypt

No. of Pages

18

Main Topic

Public Health
Medicine

Abstract EN

Short-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.

American Psychological Association (APA)

Stewart, Jill& Stewart, Paul& Walker, Tom& Gullapudi, Latha& Eldehni, Mohamed T.& Selby, Nicholas M.…[et al.]. 2020. Application of the Lomb-Scargle Periodogram to InvestigateHeart Rate Variability during Haemodialysis. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1186559

Modern Language Association (MLA)

Stewart, Jill…[et al.]. Application of the Lomb-Scargle Periodogram to InvestigateHeart Rate Variability during Haemodialysis. Journal of Healthcare Engineering No. 2020 (2020), pp.1-18.
https://search.emarefa.net/detail/BIM-1186559

American Medical Association (AMA)

Stewart, Jill& Stewart, Paul& Walker, Tom& Gullapudi, Latha& Eldehni, Mohamed T.& Selby, Nicholas M.…[et al.]. Application of the Lomb-Scargle Periodogram to InvestigateHeart Rate Variability during Haemodialysis. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1186559

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1186559