Frequency-Domain Measurements of Heart Rate Variability
HRV frequency-domain measurements reveal the sources of physiological changes and play an integral role in heart rate variability biofeedback (HRVB).
We train clients to increase LF power in the clinic to enhance vagal tone and HF power when they breathe at typical rates in everyday life (Gevirtz, 2020).
Listen to a mini-lecture on HRV Frequency-Domain Metrics © BioSource Software LLC.
Where time-domain indices quantify the total amount of heart rate variability (HRV), frequency-domain measurements quantify absolute or relative power distribution into four frequency bands.
Analogous to the electroencephalogram (EEG), we can use power spectral analysis or autoregressive (AR) modeling to separate HRV into its component rhythms. Each rhythm operates within a different frequency range. This is analogous to a prism that refracts light into its component wavelengths. Graphic © kmls/Shutterstock.com.
Review this post to learn more about Fast Fourier power spectral analysis.
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 VLF, LF, and HF bands are shown below.
BCIA Blueprint Coverage
This unit addresses IV. HRV Measurements: B. Frequency-domain measurements and their meaning, properties, and correlates.
Professionals completing this unit will be able to discuss the following HRV frequency domain indices:
A. ULF
B. VLF
C. LF
D. HF
E. LF/HF ratio
This unit covers the ULF, VLF, LF, and HF Bands, minimum recording periods, and the controversial LF/HF ratio.
Please click on the podcast icon below to hear a full-length lecture.
Perspective on Frequency-Domain Measurements
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.
We 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).
Ultra-Low-Frequency Band
The ultra-low-frequency (ULF) band (≤ 0.003 Hz) indexes fluctuations in interbeat intervals with a period from 5 minutes to 24 hours and 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).
ULF Sources
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). Different psychiatric disorders show distinct circadian patterns in 24-hour heart rates, particularly during sleep (Stampfer, 1998; Stampfer & Dimmitt, 2013). There is disagreement about the contribution of the PNS and SNS to this band. Due to its long cycle length (> 5 hours), ULF activity is too gradual to train using conventional biofeedback (Stauss, 2003).ULF Correlates
ULF power is highly correlated with the SDANN time-domain index (Bigger et al., 1992).Very-Low-Frequency Band
The very-low-frequency (VLF) band (0.0033-0.04 Hz) comprises rhythms with periods between 25 and 300 seconds. VLF measurement requires a recording period of at least 5 minutes but may be best monitored over 24 hours (Task Force, 1996). In the FFT spectral plot, VLF power is colored gray.
VLF Sources
There is uncertainty regarding the physiological mechanisms responsible for activity within this band (Kleiger et al., 2005). The heart's intrinsic nervous system appears to contribute to the VLF rhythm (Shaffer, McCraty, & Zerr, 2014).
VLF power may also be generated by physical activity (Bernardi et al., 1996), thermoregulatory, renin-angiotensin, and endothelial influences on the heart (Akselrod et al., 1981; Claydon & Krassioukov, 2008). There may be an alpha-adrenergic (norepinephrine-mediated) vascular tone contribution (Lehrer & Gevirtz, 2021). PNS activity may contribute to VLF power since parasympathetic blockade almost completely abolishes it (Taylor et al., 1998).
SNS nerve bursts occur 1-2 times per second, each lasting 0.5-2 seconds (Macefield & Wallin, 1999). VLF cycles take 25 to 300 seconds per wave. At 0.67 seconds per burst, 37.5 bursts fit in the shortest VLF cycle and 450 in the longest. Therefore, SNS nerve bursts are 37 to 450 times faster than VLF cycles--far too rapid to generate the slow oscillations seen in the VLF band.
In addition, the SNS lacks a mechanism to generate regular, sustained oscillations that comprise VLF oscillations. SNS activity doesn’t rise and fall smoothly like a perfect wave—it reacts spontaneously to stressors, not in a predictable rhythm.
In contrast, sympathetic blockade does not affect VLF power, and VLF activity is seen in tetraplegics, whose SNS innervation of the heart and lungs is disrupted (Task Force, 1996; Berntson et al., 1997).
Based on work by Armour (2003) and Kember et al. (2000, 2001), the VLF rhythm appears to be generated by stimulating afferent sensory neurons in the heart. This, in turn, activates various levels of the feedback and feed-forward loops in the heart's intrinsic cardiac nervous system, as well as between the heart, the extrinsic cardiac ganglia, and the spinal column.
Dr. Lehrer explains the VLF band © Association for Applied Psychophysiology and Biofeedback. You can enlarge the video by clicking on the bracket icon at the bottom right of the screen. When finished, click on the ESC key.
VLF Correlates
While all low values on all 24-hour clinical HRV measurements predict a greater risk of adverse outcomes, VLF power is more strongly associated with all-cause mortality than LF or HF power (Tsuji et al., 1994, 1996; Hadase et al., 2004; Schmidt et al., 2005). The VLF rhythm may be fundamental to health (Shaffer, McCraty, & Zerr, 2014).
Low VLF power is associated with arrhythmic death (Bigger et al., 1992) and PTSD (Shah et al., 2013). In several studies, low VLF power has been associated with high inflammation (Carney et al., 2007; Lampert et al., 2008).
Finally, low VLF power correlates with low testosterone levels, while other biochemical markers, such as those mediated by the HPA axis (e.g., cortisol), did not (Theorell et al., 2007). VLF power strongly correlates with the SDNN index time domain measure, which averages 5-minute standard deviations for all NN intervals over 24 hours.
Significance for HRV Biofeedback
VLF elevations may signal chronic SNS activation or vagal withdrawal (parasympathetic suppression) due to chronic worry or excessive effort during training (Gevirtz, 2017).Low-Frequency Band
The low-frequency (LF) band (0.04-0.15 Hz) is comprised of rhythms with periods between 7 and 25 seconds, is affected by breathing from ~3-9 breaths per minute (bpm), and requires a recording period of at least 2 minutes (Task Force, 1996). The baroreflex system’s resonance falls within the LF band. This region was previously called the baroreceptor range because it reflects baroreceptor activity during resting conditions (McCraty & Shaffer, 2015). In the FFT spectral plot, LF power is colored orange.
LF Sources
While there is disagreement regarding this band's activity sources, a sympathetic role during resting measurements appears unlikely (Hayano & Yuda, 2019). The PNS and blood pressure regulation may produce LF power via baroreceptors (Akselrod et al., 1981; Berntson, Quigley, & Lozano, 2007; Lehrer, 2007; Task Force, 1996) or by baroreflex activity alone (Goldstein et al., 2011). The late Evgeny Vaschillo studied a possible SNS component near 0.05 Hz (Lehrer & Gevirtz, 2021). Breathing at rates below 8.5 breaths per minute, sighing, and taking deep breaths may contribute to LF activity via the vagus (Shaffer, McCraty, & Zerr, 2014).Dr. Lehrer explains the LF band © Association for Applied Psychophysiology and Biofeedback.
Significance for HRV Biofeedback
Use LF band power to assess the success of HRVB when your client breathes from 4.5-7.5 bpm (Shaffer & Ginsberg, 2017). Expect elevated LF during resonance frequency (RF) breathing. High LF at typical breathing rates (e.g., 12-14 bpm) signals that the vagal brake is malfunctioning (Khazan, 2020).A single high amplitude peak near 0.1 Hz indicates high coherence within the Institute of HeartMath model.
Caption: The Institute of HeartMath display shows instantaneous HR at the top. The bottom left features a HRV spectral display. Note that there are two peaks around 0.1 Hz instead of one. The bottom right shows coherence ratios. Note that the individual has only achieved 68% high coherence at the low challenge level.
Coherence is a proprietary HeartMath term that means a "narrow, high-amplitude, easily visualized peak" from 0.09-0.14 Hz (Ginsberg, Berry, & Power, 2010, p. 54).High-Frequency (HF) Band
The high-frequency (HF) or respiratory band (0.15-0.40 Hz) is influenced by breathing from 9-24 bpm (Malik, 1996) and requires a recording period of at least 1 minute. For infants and children, who breathe faster than adults, the resting range can be adjusted to 0.24-1.04 Hz (Quintana et al., 2016).
HF Sources
The HF band reflects parasympathetic activity and is called the respiratory band because it corresponds to the HR variations related to the respiratory cycle. These phasic HR changes are known as respiratory sinus arrhythmia (RSA) and may not be a pure index of cardiac vagal control (Grossman & Taylor, 2007).
Recall that HR accelerates during inspiration and slows during expiration. During inhalation, the cardiovascular center inhibits vagal outflow, speeding the heart rate. Conversely, during exhalation, it restores vagal tone, slowing the heart rate via the release of acetylcholine (Eckberg & Eckberg, 1982).
Total vagal blockage virtually eliminates HF oscillations and reduces power in the LF range (Shaffer, McCraty, & Zerr, 2014).
Dr. Lehrer explains the HF band © Association for Applied Psychophysiology and Biofeedback.
HF Correlates
HF power is highly correlated with the pNN50 and RMSSD time-domain measures (Kleiger et al., 2005). HF band power may increase at night and decrease during the day (McCraty & Shaffer, 2015). Lower HF power is correlated with stress, panic, anxiety, or worry. Vagal tone modulation helps maintain the dynamic autonomic regulation important for cardiovascular health. Deficient vagal inhibition is associated with increased morbidity (Thayer et al., 2010).Significance for HRV Biofeedback
Use HF band power and time-domain metrics like RMSSD to assess HRV biofeedback training success during resting baselines (Shaffer & Ginsberg, 2017).HRVB trains clients to increase LF power during slow-paced breathing to increase HF power during baselines when they breathe at typical rates.
The graphic below shows HF power in blue during a pre-training baseline, HRVB training, and a post-training baseline. Note the greater LF power concentration post-training compared with pre-training during which the client breathed at typical rates. Inna Khazan generously provided the spectral plots.
LF/HF Ratio
Power is the signal energy contained within a given frequency band. The ratio of LF to HF power is called the LF/HF ratio. This ratio was based initially on 24-hour recordings, during which both PNS and SNS activity contribute to LF power, although PNS activity primarily contributes to HF power. The intent was to estimate the ratio between SNS and PNS activity.
Calculating a LF/HF ratio from brief or resting recordings is controversial because short-term measurements are poorly correlated with 24-hour values. Moreover, the SNS contribution to LF activity varies profoundly with testing conditions (Lehrer, 2012). For example, when LF is calculated during resting conditions, the primary contributors are PNS activity and baroreflex activity--not SNS activity. Therefore, a 5-minute resting baseline cannot estimate autonomic balance (McCraty, 2013).
MINIMUM RECORDING PERIODS FOR FREQUENCY-DOMAIN MEASURES
The table below shows conventional and ultra-short-term samples (in parentheses) for the four HRV bands (Shaffer, Meehan, & Zerr, 2020).
HF Power and RSA Do Not Represent Vagal Tone
In healthy individuals, RSA can be increased by slow, deep breathing. Respiration rate changes can produce large-scale shifts in RSA magnitude without affecting vagal tone, which is mean HR change across conditions (e.g., rest to exercise) (Grossman, 2017b).
Grossman (2017a) proposed an experiment. If you slow your breathing to 6 bpm, you should observe increased HR fluctuations compared with 15 bpm. During this time, mean HR should not appreciably change because vagal tone did not decrease.
While HF power indexes vagal modulation of HR, it does NOT represent vagal tone. If shifts in HF power mirrored shifts in vagal tone, they should produce corresponding changes in average HR. But, breathing at different rates within the 9-24-bpm range, which changes HF power, does not change mean HR.
RSA and vagal tone are dissociated during large-scale changes in SNS activity, chemical blockade of the SA node, and when intense vagal efferent traffic dramatically slows HR during inhalation and exhalation (Grossman & Taylor, 2007).
Shifts in respiration rate and volume can markedly change HRV indices (HF power, peak-to-trough differences, pNN50, RMSSD) without affecting vagal tone.
LnHF Power Can Estimate Vagal Tone Under Controlled Conditions
The natural logarithm (Ln) is the logarithm to the base e of a numeric value. Under controlled conditions while breathing at normal rates, we can use LnHF power to estimate vagal tone (Gevirtz, 2017).
Baroreflex sensitivity is strongly associated with power in the high-frequency band.
In the Kubios table below, HF power of 910.67 corresponds to LnHF of 6.81.
Dr. Lehrer explains HF band power and vagus nerve function © Association for Applied Psychophysiology and Biofeedback.
Summary Tables
HRV Myths
Misconception: HF and VLF measurements are valid during slow-paced breathing.
HF and VLF values are meaningless during slow-paced breathing near the RF.
Misconception: The SNS contributes to LF power.
During resting baseline conditions, the SNS does not generate LF power. PNS activity and the baroreceptor reflex are the two primary LF sources.
Misconception: The LF/HF ratio estimates autonomic balance during short-term baseline measurements.
Since the SNS does not contribute significantly to LF power under these conditions, the LF/HF ratio does not measure autonomic balance.
Glossary
absolute power: the magnitude of HRV within a frequency band measured in milliseconds squared divided by cycles per second (ms2/Hz).
coherence: self-coherence; signal power in the 0.09-0.14 region of the LF band.
heart rate: the number of heartbeats per minute, also called stroke rate.
heart rate variability (HRV): the beat-to-beat changes in heart rate, including changes in the RR intervals between consecutive heartbeats.
high-frequency (HF) band: a HRV frequency range from 0.15-0.40 Hz that represents the inhibition and activation of the vagus nerve by breathing (respiratory sinus arrhythmia).
interbeat interval (IBI): the time interval between the peaks of successive R-spikes (initial upward deflections in the QRS complex). This is also called the NN (normal-to-normal) interval.
low-frequency (LF) band: a HRV frequency range of 0.04-0.15 Hz that may represent the influence of PNS and baroreflex activity (when breathing at the RF).
natural logarithm (Ln): the logarithm to the base e of a numeric value.
normal units (nu): the division of the absolute power for a specific frequency band by the summed absolute power of the low frequency (LF) and high frequency (HF) bands.
power: the signal energy found within a frequency band.
relative power: the percentage of total HRV.
spectral analysis: the division of heart rate variability into component rhythms that operate within different frequency bands.
total power: the sum of power (ms2) in the ULF, VLF, LF, and HF bands for 24-hour recording and the VLF, LF, and HF bands for brief recording.
ultra-low-frequency (ULF) band: a HRV frequency range below 0.003 Hz. Very slow biological processes that include circadian rhythms, core body temperature, metabolism, the renin-angiotensin system, and possible PNS and SNS contributions.
very-low-frequency (VLF): a HRV frequency range of 0.003-0.04 Hz that may represent temperature regulation, plasma renin fluctuations, endothelial, physical activity influences, and possible intrinsic cardiac, and PNS contributions.
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Assignment
Now that you have completed this module, explain why we cannot provide immediate ULF feedback. Why is increasing LF power desirable?
References
Andreassi, J. L. (2000). Psychophysiology: Human behavior and physiological response. Lawrence Erlbaum and Associates, Inc.
Armour, J. A. (2003). Neurocardiology: Anatomical and functional principles. Institute of HeartMath.
Berntson, G. G., Quigley, K. S., & Lozano, D. (2007). Cardiovascular psychophysiology. In J. T. Cacioppo, L. G. Tassinary, & G. G. Berntson (Eds.). Handbook of psychophysiology (3rd ed.). Cambridge University Press.
Claydon, V. E., & Krassioukov, A. V. (2008). Clinical correlates of frequency analyses of cardiovascular control after spinal cord injury. American Journal of Physiology—Heart and Circulatory Physiology, 294(2), H668-H678. https://doi.org/10.1152/ajpheart.00869.2007
Combatalade, D. (2010). Basics of heart rate variability applied to psychophysiology. Thought Technology Ltd.
Gevirtz, R. N. (2017). Cardio-respiratory psychophysiology: Gateway to mind-body medicine.
Gevirtz, R. N. (2020). The myths and misconceptions of heart rate variability. Association for Applied Psychophysiology and Biofeedback Virtual Conference.
Goldstein, D. S., Bentho, O., Park, M. Y., & Sharabi, Y. (2011). Low frequency power of heart rate variability is not a measure of cardiac sympathetic tone but may be a measure of modulation of cardiac autonomic outflows by baroreflexes. Exp Physiol, 96(12), 1255-1261. https://doi.org/10.1113/expphysiol.2010.056259
Grossman, P. (2017a and 2017b). Comments on Heart rate variability and cardiac vagal tone in psychophysiological research. Frontiers in Psychology.
Grossman, P., & Taylor, E. W. (2007). Toward understanding respiratory sinus arrhythmia: Relations to cardiac vagal tone, evolution and biobehavioral functions. Biological Psychology, 74, 263-285. https://doi.org/10.1016/j.biopsycho.2005.11.014
Khazan, I. (2020). The myths and misconceptions of heart rate variability. Association for Applied Psychophysiology and Biofeedback Virtual Conference.
Lehrer, P. M. (2007). Biofeedback training to increase heart rate variability. In P. M. Lehrer, R. M. Woolfolk, & W. E. Sime (Eds.). Principles and practice of stress management (3rd ed.). The Guilford Press.
Lehrer, P. M. (2012). Personal communication about the sources of frequency domain measurements.
Lehrer, P. M., & Gevirtz, R. (2021). BCIA HRV Biofeedback didactic workshop. Association for Applied Psychophysiology and Biofeedback.
Lehrer, P. M., Vaschillo, E., & Vaschillo, B. (2000). Resonant frequency biofeedback training to increase cardiac variability: Rationale and manual for training. Applied Psychophysiology and Biofeedback, 25(3), 177-191. https://doi.org/10.1023/a:1009554825745
McCraty, R. (2013). Personal communication regarding the LF/HF ratio.
Moss, D. (2004). Heart rate variability (HRV) biofeedback. Psychophysiology Today, 1, 4-11.
Nunan, D., Sandercock, G. R. H., & Brodie, D. A. (2010). A quantitative systematic review of normal values for short-term heart rate variability in healthy adults. Pacing and Clinical Electrophysiology, 33(11), 1407-1417. https://doi.org/10.1111/j.1540-8159.2010.02841.x
Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996). Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. Circulation, 93, 1043-1065. PMID: 8598068
Tarvainen, M. P., & Niskanen, J.-P. (2020). Kubios HRV version 3.4 user's guide. University of Finland.
Theorell, T., Liljeholm-Johansson, Y., Björk, H., & Ericson, M. (2007). Saliva testosterone and heart rate variability in the professional symphony orchestra after “public faintings” of an orchestra member. Psychoneuroendocrinology, 32, 660–668. https://doi.org/10.1016/j.psyneuen.2007.04.006