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A Comprehensive Guide to HRV Myths

Updated: Apr 4


human heart

HRV indexes how efficiently we mobilize and utilize limited self-regulatory resources to maintain homeostasis. HRV plays a vital role in regulatory capacity, executive functions, health, and performance. This review addresses 16 misconceptions regarding cardiovascular health, HRV measurement, and HRV biofeedback training. We highlight the importance of context and individual differences in interpreting HRV. We debunk common misconceptions to improve HRV biofeedback training for health and performance.



Heart Rate Variability


Heart rate variability (HRV) has emerged as a significant biomarker for assessing cardiovascular health and autonomic nervous system function. Despite its growing application in both clinical and research settings, misconceptions about HRV persist. This document aims to dispel these myths by providing evidence-based insights into HRV, clarifying its physiological underpinnings, measurement, and implications for biofeedback training. By demystifying these aspects, we endeavor to enhance the understanding and effective utilization of HRV in clinical practice, ultimately contributing to improved patient care and outcomes.



Cardiovascular Health


We will cover two cardiovascular health myths: 1. Variability is good, stability is bad. 2. A healthy heart is a metronome.

Myth 1. Variability is good, stability is bad.


Not all variability is healthy. Whereas heart rate variability (HRV) is desirable, blood pressure (BP) variability can endanger health. We require blood pressure (BP) stability under constant workloads (Gevirtz, 2020). BP variability graphic adapted from Dr. Richard Gevirtz by minaanandag at Fiverr.com.


blood pressure


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Myth 2. A healthy heart resembles a metronome.


“A healthy heart is not a metronome” (Shaffer et al., 2014). When the time intervals between heartbeats significantly change across successive breathing cycles, this shows that the cardiovascular center can effectively modulate vagal tone.

"The complexity of a healthy heart rhythm is critical to the maintenance of homeostasis because it provides the flexibility to cope with an uncertain and changing environment...HRV metrics are important because they are associated with regulatory capacity, health, and performance and can predict morbidity and mortality" (Shaffer et al., 2020).


metronome

Figure 4 shows healthy variability. The time intervals between successive beats differ.


healthy variability

In contrast, Figure 5 shows low variability since the interbeat intervals (IBIs) are identical. This could represent a heart that may soon need a pacemaker.


low variability

"The complexity of a healthy heart rhythm is critical to the maintenance of homeostasis because it provides the flexibility to cope with an uncertain and changing environment” (Shaffer et al., 2020).


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HRV Sources


We will cover the HRV source myth that short-term resting HRV contains a sympathetic component.

Myth 3. Short-term (~5 min) resting HRV is partially sympathetic.

Research using tilt tables to provoke a sympathetic response have fueled the myth that resting HRV contains a sympathetic component. Tilt table graphic © Pepermpron/Shutterstock.com.


tilt table


However, respiratory sinus arrhythmia, the baroreceptor reflex, and the vascular tone rhythm are the most important sources of short-term (~5-min) HRV. They are exclusively parasympathetic (Hayano & Yuda, 2019; Vaschillo et al., 2002).


HRV sources


Respiratory sinus arrhythmia (RSA), HR speeding and slowing across each breathing cycle, is the primary and entirely PNS source of HRV (Gevirtz, 2020). The blue waveform is breathing and the red is instantaneous HR. Screenshot by Dr. Shaffer.


RSA


In the graphic adapted with permission from Elite Academy the upper waveform represents the breathing cycle, and the lower signals is HR.


RSA


Inhalation partially disengages the vagal brake, speeding HR. This is purely parasympathetic. Graphics inspired by Dr. Richard Gevirtz.


RSA


Exhalation reapplies the vagal brake, slowing HR.


RSA


Vaschillo’s two closed-loop model (2002) described the heart rate (HR) and vascular tone (VT) baroreflexes as closed loops. They proposed that stimulating one closed loop activates its counterpart. Graphic adapted from Vaschillo and colleagues.


two closed-loops model

Each baroreflex is a potential target for HRV biofeedback training. The HR baroreflex regulates acute BP changes to ensure stability. Although HRV promotes health, BP variability

endangers it.

The vascular tone (VT) baroreflex regulates resistance blood vessel diameter. A larger arteriole diameter means lower blood pressure. Graphic © Ali DM/Shutterstock.com.


arteriole

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HRV Measurements


We will cover five HRV measurement myths: 4. Very-low-frequency (VLF) increases during HRV biofeedback training are sympathetic. 5. Low-frequency (LF) power measurements during rest contain a sympathetic component. 6. High-frequency (HF) power measurements during slow-paced breathing are valid. 7. We can directly compare HRV recordings of different lengths. 8. You should trust smartphone HRV app values.



Myth 4. Very-low-frequency (VLF) increases during HRV biofeedback training are sympathetic.


The LF band (0.0033-0.04 Hz) comprises rhythms with periods between 25 and 300 seconds. There is uncertainty regarding the physiological mechanisms responsible for activity within this band (Kleiger et al., 2005).

Excessive effort during HRV biofeedback training can trigger vagal withdrawal (parasympathetic inhibition). Contrary to popular belief, the fight-or-flight response (i.e., sympathetic activation) occurs in response to threats to our survival, as opposed to mild stressors. Everyday stressors cause vagal withdrawal instead of sympathetic activation.


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Myth 5. Low-frequency (LF) power measurements during rest contain a sympathetic component.


The LF band (0.04-0.15 Hz) is comprised of rhythms with periods between 7 and 25 seconds and is affected by breathing from ~3-9 breaths per minute (bpm). LF power increases during slow-paced breathing (SPB) and slow-paced contraction (SPC), likely reflecting baroreceptor and parasympathetic, but not sympathetic, activity.

The LF/HF ratio calculated at rest is controversial because there should be no sympathetic activity. Graphic adapted from Dr. Richard Gevirtz by Dani S@unclebelang.


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Myth 6. High-frequency (HF) power measurements during slow-paced breathing are valid.


The HF band (0.15-0.40 Hz) is influenced by breathing from 9-24 bpm (Task Force, 1996). HF measurements are invalid during SPB and cannot serve as a proxy for vagal tone (parasympathetic activity).


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Myth 7. We can directly compare HRV recordings of different lengths.


Recording period significantly affects both HRV time- and frequency-domain measurements.

Cycle-length dependence prevents directly comparing 5- and 10-minute recordings because longer recording periods can capture more variability (Pomeranz et al., 1985).

Resting values obtained from brief monitoring periods can dramatically underestimate HRV, correlating poorly with 24-hour indices.


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Myth 8. You should trust smartphone HRV app values.


HRV time- and frequency-domain values obtained from smartphone apps may be invalid due to their failure to control artifacts. Popular HRV apps either do not clean data or perform minimal data cleaning. They are overwhelmed by abnormal beats like premature atrial contractions. Manual data artifacting within programs like CardioPro and Kubios is the "gold standard."


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HRV Biofeedback Training


We will cover eight myths: 9. Try to relax. 10. Take deep breaths. 11. Slow-paced breathing is the best way to increase HRV. 12. Successful HRV biofeedback training always produces a 0.1 Hz LF peak. 13. VLF power increases during HRV training are sympathetic. 14. When slow-paced breathing increases HR oscillations, this signals greater vagal tone. 15. The best sign of HRV training success is high resting LF power. 16. HRV biofeedback asks clients to slow their daily breathing permanently.



Myth 9. Try to relax.


When clients try too hard during HRV biofeedback practice, they can trigger vagal withdrawal. Active volition (e.g., trying) may increase VLF power and produce unwanted autonomic changes such as increased skin conductance and decreased skin temperature.



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Myth 10. Take deep breaths since we need more oxygen.


At rest, we do not need more oxygen! Near sea level, the air we inhale contains 21% oxygen, whereas the air we exhale contains 15% oxygen. We only use one-fourth of inhaled air.


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Myth 11. Slow-paced breathing is the best way to increase HRV.


Slow-paced contraction (SPC) offers an alternative to slow-paced breathing (SPB), which is sometimes challenging (e.g., chronic pain) or medically contraindicated (e.g., kidney disease). SPC may be helpful for clients who breathe dysfunctionally or who cannot slow their breathing to the adult resonance frequency range (4.5 to 6.5 bpm).


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Myth 12. Successful HRV biofeedback training always produces a 0.1 Hz LF peak.


If you train your client using a resonance frequency protocol, their target breathing rate might fall between 4.5-6.5 bpm, for adults, and as high as 8 bpm, for children. The peak frequency (e.g., the highest amplitude frequency) depends on your client’s breathing rate. Although breathing at 6 bpm yields a 0.1 Hz peak (6/60 = 0.1 Hz), 5 bpm creates a 0.08 Hz peak (5/60 = 0.083 Hz).


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Myth 13. VLF power increases during HRV training are sympathetic.


VLF power increases may represent vagal withdrawal instead of sympathetic activation.



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Myth 14. When slow-paced breathing increases HR oscillations, this signals greater vagal tone.


Slowing breathing to rates between 4.5-6.5 bpm, for adults, and 6.5-9.5 bpm, for children, increases RSA (Lehrer & Gevirtz, 2014). Increased RSA immediately “exercises” the baroreflex without changing vagal tone or tightening BP regulation. Changing vagal tone or tightening BP regulation requires weeks to months of practice.


HRV biofeedback can immediately increase RSA 4-10 times compared to a resting baseline (Gevirtz et al., 2016; Vaschillo et al., 2002). Graphic adapted from Gevirtz et al. (2016).



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Myth 15. The best sign of HRV training success is high resting LF power.


The best sign of HRV training success is high resting HF power when breathing at normal rates.

The natural log of HF power is a proxy for vagal tone. High resting LF power when breathing between 11-18 bpm is undesirable and could indicate that the vagal break is “stuck.”


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The next graphic, courtesy of Dr. Khazan, shows that HF power (blue) increased from ~100 μV

to ~300 μV from pre-training to post-training baselines. HF power is a proxy for vagal tone when clients breathe at normal rates without feedback.


HF power


Myth 16. HRV biofeedback asks clients to slow their daily breathing permanently.


HRV biofeedback training may prescribe slow-paced-breathing practice up to 20 minutes, two times daily. Clients breathe normally the rest of the time, adjusting their breathing to their workloads. For example, in weightlifting, it would be counterproductive to curl a dumbbell throughout the day. Graphic © ra2 studio/Shutterstock.com.

weightlifting


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Conclusion


The exploration of HRV myths and their subsequent debunking serves not only to correct common misconceptions but also to highlight the intricate relationship between HRV and overall health. The evidence presented underscores the importance of accurate HRV interpretation and application in clinical and performance settings. As we advance our understanding of HRV through rigorous research and practice, it becomes crucial to integrate these insights into patient care. Doing so promises to refine diagnostic and therapeutic approaches, fostering a holistic understanding of cardiovascular health that is informed by the dynamic interplay of physiological systems.



Glossary


baroreflex: baroreceptor reflex that provides negative feedback control of BP and HR. Elevated BP activates the baroreflex to lower BP, and lower BP suppresses the baroreflex to raise BP.

cycle-length dependence: the phenomenon where faster HRs reduce the time between successive beats and the opportunity for the interbeat intervals (IBIs) to vary, resulting in lower HRV.

effortless contraction: SPC using about 25% of maximum effort.

frequency-domain metrics: the absolute or relative power of the HRV signal within four frequency bands.

heart rate (HR): the number of heartbeats per minute.

heart rate baroreflex: the closed loop encompassing the cardiovascular control center, heart rate control system, and blood pressure control system.

heart rate variability (HRV): the beat-to-beat changes in HR involving changes in the RR intervals between consecutive heartbeats.

heart rate variability (HRV) biofeedback: the display of beat-to-beat changes in HR, including changes in the RR intervals between consecutive heartbeats to a client.

high-frequency (HF) band power: signal energy in the 0.15-0.40 Hz range that represents the inhibition and activation of the vagus nerve by breathing (respiratory sinus arrhythmia).

HR Max-HR Min: the average difference between the highest and lowest HRs during each respiratory cycle.

HRV time-domain indices: calculating the amount of variability in interbeat interval measurements.

interbeat intervals (IBIs): the time intervals between the peaks of successive R-spikes (initial upward deflections in the QRS complex).

low-frequency (LF) band power: 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). NN intervals: the time between successive heartbeats initiated by the sinoatrial node.

peak frequency: the highest-amplitude frequency.

resonance: an amplification process in which an external force causes a closed-loop (negative feedback) system to oscillate with greater amplitude at its inherent resonance frequency (RF).

resonance frequency: the frequency at which a system, like the cardiovascular system, can be maximally activated or stimulated.


respiratory sinus arrhythmia (RSA): the respiration-driven heart rhythm that contributes to the high-frequency (HF) component of heart rate variability. Inhalation inhibits vagal nerve slowing of the heart (increasing HR), while exhalation restores vagal slowing (decreasing HR).


RMSSD: the square root of the mean squared difference of adjacent NN intervals. RR intervals: the time between successive heartbeats.

SDNN: the standard deviation of the normal (NN) sinus-initiated IBI measured in milliseconds.

slow-paced breathing (SPB): breathing in the adult 4.5-6.5 bpm range.

slow-paced contraction (SPC): wrist-ankle or wrist-core-ankle contraction in the

adult 4.5-6.5 cpm range.

time-domain metrics: HRV indices that quantify the amount of variability in IBI measurements.

vagal tone: parasympathetic activity, which is estimated by the natural log of HF power.

vagus nerve: the parasympathetic vagus (X) nerve decreases the rate of spontaneous depolarization in the SA and AV nodes and slows HR. HR increases often reflect reduced vagal inhibition.

Vaschillo’s two closed-loop model: the heart rate (HR) and vascular tone (VT) baroreflexes are closed loops; stimulating one closed loop activates its counterpart. Each baroreflex is a potential target for HRV biofeedback training. SPB and SPC at ~ 6 bpm/cpm can stimulate the HR baroreflex, separately or synergistically. SPC at ~ 1 cpm can activate the VT baroreflex.

vascular tone (VT) baroreflex: negative feedback loop that regulates resistance blood vessel diameter with a 15-second delay and 0.03 Hz resonance frequency.



References


Gevirtz, R. N. (2020). The myths and misconceptions of heart rate variability. AAPB Annual Meeting.

Gevirtz, R. N., Lehrer, P. M., & Schwartz, M. S. (2016). Cardiorespiratory biofeedback. In M.S. Schwartz & F. Andrasik (Eds.). Biofeedback: A practitioner’s guide (4th ed.). The Guilford Press.

Hayano, J., & Yuda, E. (2019). Pitfalls of assessment of autonomic function by heart rate variability. J Physiol Anthropol, 38(1), 3. https://doi.org/10.1186/s40101-019-0193-2.

Kleiger, R. E., Stein, P. K., & Bigger, J. T., Jr (2005). Heart rate variability: Measurement and clinical utility. Annals of Noninvasive Electrocardiology: The Official Journal of the International Society for Holter and Noninvasive Electrocardiology, Inc, 10(1), 88–101. https://doi.org/10.1111/j.1542-474X.2005.10101.x

Lehrer, P. M., & Gevirtz, R. (2014). Heart rate variability: How and why does it work? Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2014.00756

Pomeranz, B., Macaulay, R. J., Caudill, M. A., Kutz, I., Adam, D., Gordon, D., Kilborn, K. M., Barger, A. C., Shannon, D. C., & Cohen, R. J. (1985). Assessment of autonomic function in humans by heart rate spectral analysis. The American Journal of Physiology, 248(1 Pt 2), H151–H153. https://doi.org/10.1152/ajpheart.1985.248.1.H151

Shaffer, F., McCraty, R., & Zerr, C. L. (2014). A healthy heart is not a metronome: An integrative review of the heart’s anatomy and heart rate variability. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2014.01040

Shaffer, F., Meehan, Z. M., & Zerr, C. L. (2020). A critical review of ultra-short-term heart rate variability norms research. Frontiers in Neuroscience. https://doi.org/10.3389/fnins.2020.594880

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


Vaschillo, E., Lehrer, P., Rishe, N., & Konstantinov, M. (2002). Heart rate variability biofeedback as a method for assessing baroreflex function: A preliminary study of resonance in the cardiovascular system. Applied Psychophysiology and Biofeedback, 27(1), 1-27. https://doi.org/10.1023/a:1014587304314


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