Abstract

The understanding of heart rate variability (HRV) has increased parallel with the development of modern physiology. Discovered probably first in 1847 by Ludwig, clinical applications evolved in the second part of the twentieth century. Today HRV is mostly used in cardiology and research settings. In general, HRV can be measured over shorter (e.g., 5–10 min) or longer (12 or 24 h) periods. Since 1996, most measurements and calculations are made according to the standard of the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. As the first step, the series of times between successive R-peaks in the ECG are in milliseconds. It is crucial, however, to identify and remove extrasystoles and artifacts according to standard protocols. The series of QRS distances between successive heartbeats can be analyzed with simple or more sophisticated algorithms, beginning with standard deviation (SDNN) or by the square root of the mean of the sum of squares of differences between adjacent normal RR (rMSSD). Short-term HRV is frequently analyzed with the help of a non-parametric fast Fourier transformation quantifying the different frequency bands during the measurement period. In the last decades, various non-linear algorithms have been presented, such as different entropy and fractal measures or wavelet analysis. Although most of them have a strong theoretical foundation, their clinical relevance is still debated.

Highlights

  • Langley erroneously defined the ANS as a purely visceral motor system, mediating the consequences of central nervous states to the periphery [today we know that 80% of vagal fibers are in reality afferent, providing important information to the brain regarding the state of the visceral organs [17]]

  • Amitryptilin and Doxepin, taken in a period of 2 weeks was associated with general decreased frequency domain parameters [111], the effect of tricyclic antidepressants, selective serotonin reuptake inhibitors and other antidepressants was confirmed in a larger study [112] here, a comprehensive overview can be found in Ref. [11], chapter 4

  • NN50 is the number of pairs of successive NNs that differ by more than 50 ms, pNN50, the proportion of NN50 divided by total number of NNs over a 24h-recording {(2) #1505} and is often interpreted as a proxy for cardiac parasympathetic activity {(134) #2345}. root Mean Sum of Squared Distances (rMSSD) stands for the square root of the mean squared differences of successive NN intervals [2, 135]

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Summary

Gernot Ernst*

Anesthesiology, Pain and Palliative Care Section, Kongsberg Hospital, Vestre Viken Hospital Trust, Kongsberg, Norway. Specialty section: This article was submitted to Family Medicine and Primary Care, a section of the journal Frontiers in Public Health. The series of times between successive R-peaks in the ECG are in milliseconds. It is crucial, to identify and remove extrasystoles and artifacts according to standard protocols. The series of QRS distances between successive heartbeats can be analyzed with simple or more sophisticated algorithms, beginning with standard deviation (SDNN) or by the square root of the mean of the sum of squares of differences between adjacent normal RR (rMSSD). Short-term HRV is frequently analyzed with the help of a non-parametric fast Fourier transformation quantifying the different frequency bands during the measurement period.

INTRODUCTION
History and Methods of HRV
METHODS
Possible parameters
Food intake Ethnicity
Geometric Methods
Task force
Frequency Domain
Fractal Analysis
Findings
Other Algorithms

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