Heart Rate Variability & Its Research Applications

Heart Rate Variability & Its Research Applications

We give the lowdown on why HRV is important and how it can be measured using wearables to enhance your research studies.

Mar 18, 2022
Medically Reviewed By Dr. Andrew Ahn
Stylized heart rate on monitor

Heart Rate Variability – What is it? 

A strong healthy heart will speed up and slow down constantly to address environmental changes and stressors as they appear. Consistency is not something to strive for when it comes to the heart. Healthy hearts should have beat-to-beat variability and not consistently beat at the same tempo. This variation between heartbeats is called Heart Rate Variability (HRV). 

Looking at HRV can provide a lot of information about an individual’s physical and mental health because it demonstrates the body’s ability to respond to stress and change. Higher HRV generally means the body is better prepared and resilient when faced with adversities.  

HRV is calculated by looking at the fluctuations between individual heartbeats. The time between each consecutive heartbeat has many names such as R-R interval or inter-beat-interval (BBI or IBI) and is calculated in milliseconds.  That data is then used to calculate the variability that exists in the person’s heartbeat. Using HRV, an individual’s Autonomic Nervous System (ANS) can be analyzed.

Heart Rate Variability vs. Heart Rate (HR) 

All that’s required to calculate an individual’s heart rate is to calculate the average number of heartbeats over a given period of time. Doing exercise or strenuous activities can cause an elevated heart rate whereas a low heart rate is an indicator of rest. Using collected heart rate data, you are limited to monitoring the effectiveness of aerobic exercise or identifying someone’s level of cardiovascular exertion.

If you are looking to monitor the body’s various internal functions then HRV should be used instead of HR.

Case Study

Stanford WELL For Life researchers wanted to measure sleep quality, stress, and depression. They ran a pilot study using smartwatches to capture heart rate, and then used heart rate variability derived from BBI data to estimate sleep quality, stress levels and other biometric data.

Why is HRV important? 

HRV provides a non-invasive method of analyzing the Autonomic Nervous System (ANS). The body has a number of processes that are performed automatically when it is confronted with different stressors. These processes are all performed by the ANS and their functions are how the body is able to manage and recover from internal and external sources of stress. 

ANS plays an important part in keeping blood sugar, blood pressure (BP), and body temperature regulated. The nervous system, cardiovascular system, and respiratory systems are all linked via ANS. This means that with HRV data, an individual’s psychological health, physical health, and environmental condition can be monitored. 

Tracking HRV over time and correlating data segments with specific activities or life events can provide unique insights into the person’s physical fitness level, overall health, or mental health.  Looking at an individual’s HRV trends can also help identify whether lifestyle changes, medications, or other medical interventions are working as intended. 

How to Measure Heart Rate Variability

There are various methods and calculations that can be used to calculate HRV such as time-domain, frequency-domain, and non-linear metrics. An important method used by researchers and health professionals is time-domain (RMSSD). 

To calculate time-domain HRV, heart variability is monitored over a set time period such as 5 minutes or 24 hours. This data is calculated using inter-beat-interval data and can be looked at as a way to understand IBI variability. 


Many consumer wearables such as Garmin smartwatches have an optical heart rate sensor that uses pulse wave measurements to calculate IBI. Heart pulsations are recorded through the wearable by emitting a green light directly into the vein to record blood flow changes. With each heartbeat the level of blood flow will change, making wearables an accessible solution for calculating BBI and HRV. 

Other more traditional methods including ECG (EKG) can also be used to calculate HRV. These methods would involve using a portable Holter Monitor, electrodes stuck to the chest, or chest strap heart monitors. These methods record all the movements of the heart and map out the waves of movement, otherwise knowns as the QRS complex. The largest energy wave in the QRS complex is called the R wave and it is using the time interval between R waves that IBI is calculated. 

In order to create a good baseline, doing 24hr HRV recordings over various days can be beneficial.  24hr HRV recordings take into account the individual’s circadian rhythm, sleep cycle, and even the changes in their renin-angiotensin system (RAS or RAAS) which is the hormonal system that regulates blood flow and blood pressure. 

Consumer wearables present a great solution for gathering 24hr HRV data because they do not require lab or clinic observations and can be comfortably worn day and night. When using wearables connected to the Labfront platform, IBI and HRV data can even be collected and analyzed remotely. 



Applications of HRV in Research 

An individual’s HRV is a great indicator of their autonomic activity. Various physical and mental conditions affect the Autonomic Nervous System including autonomic neuropathies like diabetic neuropathy, depression, PTSD, anxiety, and cardiac health. 

HRV data will help indicate the level of stress or the seriousness of various health conditions by showing the body’s ability to cope. This data can then be used to quantify overall health and identify if further interventions are needed to address specific pathological conditions such as cardiac disease or depression. 

HRV Course part 1 with headshot of Dr. Andrew Ahn

Take a deep dive into HRV with a free master class!

In this course, Dr. Ahn provides a clear and well-structured overview of HRV that breaks down this complex topic in an accessible way.

Last medically reviewed on
Nicola Craig Hora
Nicola Craig Hora
Guest Contributor

Guest writer at Labfront. Nicola is passionate about making academic research accessible to people of all backgrounds.

Dr. Andrew Ahn
Dr. Andrew Ahn
Chief Medical/Science Officer

Dr. Ahn is an internal medicine physician with a background in physics/engineering and physiological signal analyses. He is the Chief Medical Officer at Labfront and an Assistant Professor in Medicine & Radiology at Harvard Medical School. Dr. Ahn is passionate about democratizing health sciences and exploring health from an anti-disciplinary perspective.

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