HRV Frequency-Domain Measurements for Smart People
Updated: 2 days ago
What Are HRV Frequency-Domain Metrics?
Heart rate variability (HRV) frequency-domain metrics quantify the absolute or relative power within four frequency bands. HRV frequency-domain measurements reveal the sources of physiological changes.
Like time-domain measurements, they are calculated from the interbeat interval (IBI). An IBI is a period between successive heartbeats. It is also called an R-R interval because it is the time between adjacent R-spikes. Graphic © arka38/Shutterstock.com
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Interbeat Interval Refresher
We measure the time intervals between successive heartbeats in milliseconds (ms). The software starts counting after detecting the first beat and calculates the first IBI in ms after detecting the second beat. This process is repeated until the end of the epoch (data collection period). Graphic adapted from Dr. Richard Gevirtz.
Note: the numbers in boxes are IBIs measured in milliseconds.
What is the Source of HRV Frequency Bands?
The processes that contribute to HRV operate at different speeds and therefore generate different frequencies. Frequency-domain measurements quantify the absolute or relative amount of HRV signal power within each of four frequency bands (ultra-low, very-low-frequency, low-frequency, and high-frequency).
In the graphic below, adapted from Dr. Richard Gevirtz, ultra-low-frequency activity is red, very-low-frequency activity is green, low-frequency activity is yellow, and high-frequency activity is white.
Analogous to the electroencephalogram (EEG), we can use power spectral analysis or autoregressive (AR) modeling to separate HRV into its component rhythms. This is analogous to a prism that refracts light into its component wavelengths. Graphic © kmls/Shutterstock.com.
The Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996) divided heart rate oscillations into four frequency bands. The very-low-frequency (VLF), low-frequency (LF), and high-frequency (HF) bands are shown below.
Why does each rhythm operate within a different frequency range? The processes that generate the VLF, LF, and HF bands oscillate with increasing speed (shorter cycles). VLF processes are the slowest, followed by the progressively faster LF and HF processes.
A Few Cautions
Very-low-frequency and high-frequency power measurements are invalid when individuals breathe slowly (e.g., ~ 6 bpm).
We cannot compare HRV frequency-domain values (e.g., low-frequency) obtained during slow-paced breathing to resting norms. Brief resting measurement periods underestimate 24-hour frequency-domain values. Finally, consumers should exercise caution in interpreting smartphone time-domain values because apps either do not artifact or perform limited data clean-up. To address this problem, export text file data from the device software to additional analysis software.
Kubios Standard, which is freeware, allows automatic and manual artifact correction, and reports an extensive range of time- and frequency-domain metrics.
We will cover the ultra-low-frequency (ULF), very-low-frequency (VLF), low-frequency (LF), and high-frequency (HF) bands. In addition, we will examine the problems with the controversial LF/HF ratio. Researchers express absolute power in ms squared divided by cycles per second (ms2/Hz). Relative power is a frequency band’s percentage of total HRV power. We can express this in normal units (nu) by dividing the absolute power for a specific frequency band by the summed absolute power of the low-frequency (LF) and high-frequency (HF) bands.
While normal units allow us to compare the spectral distribution in two clients directly, they conceal the actual contributions of each frequency band to HRV (Gevirtz, 2020). Journals now prefer the natural logs of LF and HF power. A natural log expresses a value to the base e. The irrational mathematical constant e ≈ 2.71828.
The autonomic contribution to the ultra-low-frequency (ULF), very-low-frequency (VLF), and low-frequency (LF) bands remains controversial since measurements profoundly vary with testing conditions (Lehrer, 2012).
The ultra-low-frequency (ULF) band (≤ 0.003 Hz) indexes fluctuations in interbeat intervals with a period from 5 minutes to 24 hours. The ULF band is measured using 24-hour recordings (Kleiger et al., 2005). Due to its long cycle length (> 5 hours), ULF activity is too gradual to train using conventional biofeedback (Stauss, 2003).
There is no consensus regarding the mechanisms that generate ULF power. Very slow-acting biological processes are implicated. Circadian rhythms may be the primary driver of this rhythm (Shaffer, McCraty, & Zerr, 2014).
Core body temperature, metabolism, and the renin-angiotensin system operate over a long period and may also contribute to these frequencies (Task Force, 1996; Bonaduce et al., 1994).