Comparison of nonparametric and parametric methods for time-frequency heart rate variability analysis in a rodent model of cardiovascular disease

The aim of time-varying heart rate variability spectral analysis is to detect and quantify changes in the heart rate variability spectrum components during nonstationary events. Of the methods available, the nonparametric short-time Fourier Transform and parametric time-varying autoregressive modeli...

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Bibliographic Details
Published in:PloS one 2020-11, Vol.15 (11), p.e0242147
Main Authors: Wong, Emily M, Tablin, Fern, Schelegle, Edward S
Format: Article
Language:English
Subjects:
Abdomen
Algorithms
Analysis
Analysis of Variance
Anatomy & physiology
Animals
Autonomic Nervous System - physiology
Autoregression (Statistics)
Autoregressive models
Biology
Biology and Life Sciences
Blood
Cardiovascular disease
Cardiovascular diseases
Cardiovascular Diseases - physiopathology
Comparative analysis
Development and progression
Disease Models, Animal
Electrocardiography
Exposure
Fourier Analysis
Fourier transforms
Heart Rate
Hypertension
Laboratory animals
Male
Medicine and Health Sciences
Methods
Modelling
Nonparametric statistics
Ozone
Physical Sciences
Physiology
Rats
Rats, Inbred SHR
Regression Analysis
Research and Analysis Methods
Respiration
Social Sciences
Spectral analysis
Spectral analysis (Signal analysis)
Spectrum analysis
Statistical analysis
Statistics
Statistics, Nonparametric
Surgery
Telemetry
Transmitters
Variability
Veterinary colleges
Veterinary medicine
Wavelet transforms
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Summary:The aim of time-varying heart rate variability spectral analysis is to detect and quantify changes in the heart rate variability spectrum components during nonstationary events. Of the methods available, the nonparametric short-time Fourier Transform and parametric time-varying autoregressive modeling are the most commonly employed. The current study (1) compares short-time Fourier Transform and autoregressive modeling methods influence on heart rate variability spectral characteristics over time and during an experimental ozone exposure in mature adult spontaneously hypertensive rats, (2) evaluates the agreement between short-time Fourier Transform and autoregressive modeling method results, and (3) describes the advantages and disadvantages of each method. Although similar trends were detected during ozone exposure, statistical comparisons identified significant differences between short-time Fourier Transform and autoregressive modeling analysis results. Significant differences were observed between methods for LF power (p ≤ 0.014); HF power (p ≤ 0.011); total power (p ≤ 0.027); and normalized HF power (p = 0.05). Furthermore, inconsistencies between exposure-related observations accentuated the lack of agreement between short-time Fourier Transform and autoregressive modeling overall. Thus, the short-time Fourier Transform and autoregressive modeling methods for time-varying heart rate variability analysis could not be considered interchangeable for evaluations with or without interventions that are known to affect cardio-autonomic activity.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0242147