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Why is it that every wearable and digital wellbeing app is looking into incorporating heart rate variability (HRV)? Why is it that research using HRV as an endpoint is exploding? Let's break it down.
"You can't have speed, quality and price!" used to apply to biomarkers too."
Biomarkers like steps, average heart beat, BMI, or VO2max are inexpensive to measure (you get a good"price"), but offer limited realtime insight into decisions like "what's my ideal workout today?" or "did I get enough sleep?".
Other biomarkers (like blood glucose trending) offer insights into your stress, recovery, fitness and wellness. But measuring them is expensive, invasive and slow. You don't get the "speed".
But HRV hits the sweet spot. It's speedy, and when measured and interpreted correctly, it's effective. For example, studies looking at HRV-based guidance have shown":
And now, HRV is more accessible than ever.
Ok, HRV does start with the heart, through the differences in spaces between heartbeats. These differences create many interesting patterns, and make HRV a unique biomarker.
These patterns actually correspond to a "fingerprint" of your nervous system, as it directs many different organ systems to adjust and respond to the stressors of your ever-changing environment.
To understand HRV, you need to know that the human heart is not a metronome. A heart rate of sixty beats per minute might suggest one beat per second; in reality there are millisecond variations between successive heartbeats. Some beats are less than one second apart, while others are more than a second apart.
Oddly enough, the healthiest individuals (all mammals) don't have steady consistent heartbeat intervals. Instead, these hearts react and recover from stressors and soothers quickly, causing intervals to vary constantly. Because of that, more heart rate variability is better!
Even when the body is completely at rest, a grand balancing act - called homeostasis - is taking place. Homeostasis means "changing to stay the same", and is central to understanding how even the simplest single-celled organisms stay alive in a dynamic environment.
The principle of constantly adjusting to stay the same is visceral, as seen below:
The athlete makes thousands of realtime adjustments, just like your body does every second of every day as you respond to the dynamic conditions of your environment.
The variability we experience between heartbeats is a direct result of the autonomic nervous system fine-tuning our physiology. Researchers have categorized these inputs and outputs as they show up in HRV patterns:
High HRV correlates with resilience, fitness, longevity and better mental health; low HRV correlates with inflammation, reduced fitness, and increased risk of many chronic diseases (cardiac, metabolic, renal, neurodegenerative, autoimmune, psychosocial, and more).
If you're interested in learning more about HRV, stress and the homeostatic mechanisms connecting them, we teach an accredited self-paced online workshop. Feel free to access it here).
HRV took a long time to be widely adopted because of the challenges in filtering out the signal from the noise.
Our mission has been to solve for this, having researched HRV for over 7 years, analyzing over four billion cardiac intervals, serving over 700,000 users, examining over 20 million user sessions, and partnering with over 115 research institutions.
In our journey, we pioneered and validated methods to separate the true HRV signal from the noise, sort through different patterns, and apply the right proprietary interpretive algorithms in the right situation.
For example, our algorithms are finely-tuned towards understanding short windows of HRV, which are easily captured via smartphone cameras (or from wearables). These short readings are easily trended together over days and even weeks to surface emergent patterns that shed new insights into health, fitness and wellbeing.
(By contrast, a 12 hour+ reading might be powerful, but only presents one snapshot. It's like trying to understand the plot of a movie by looking at just one high-fidelity frame).
HRV can also act as a cornerstone biomarker to create new insights into sleep, illness, workout recovery, biological age, mental flow, and more - when combined with other biomarkers. At Spren, we're dedicated to surfacing more insights that reside within the combination of HRV and other biomarkers.
Sources (ask for our Research Brief):
- A Hernández-Vicente et al, 2020 Front Physiol., Heart Rate Variability and Exceptional LongevityU
- Zulfiqar et al; 2010 Am J Cardiol., Relation of high heart rate variability to healthy longevity
- DP Williams et al; 2019 Brain Behav Immun., Heart rate variability and inflammation: A meta-analysis of human studies
- VC Goessl et al; 2017 Psychol Med., The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis
- S Chen et al; 2016 J Hum Hypertens., Effects of heart rate variability biofeedback on cardiovascular responses and autonomic sympathovagal modulation following stressor tasks in prehypertensives
- V Vesterinnen et al; 2016 Med Sci Sports Exc, Individual Endurance Training Prescription with Heart Rate Variability
- A Galegos et al; 2020 International Journal of Environmental Research and Public Health, HRV-Based Training for Improving VO2max in Endurance Athletes. A Systematic Review with Meta-Analysis
- S Williams et al; 2017 J Sports Sci Med., Heart Rate Variability is a Moderating Factor in the Workload-Injury Relationship of Competitive CrossFit™ Athletes
- A Javaloyes et al; 2018 Int J Sports Physiol Perform, Training Prescription Guided by Heart Rate Variability in Cycling
- J Sacha; 2014 Ann Noninvasive Electrocardiol. Interaction between Heart Rate and Heart Rate Variability
- J Fatisson et al; 2016 Heart International, Influence Diagram of Physiological and Environmental Factors Affecting Heart Rate Variability: An Extended Literature Overview
- More sources available in our Research Brief