Heart Rate Variability

Heart rate variability: trivia and the explanation of some peculiarities and features

The modern indicator of Heart Rate Variability (HRV) is slowly but surely creeping into the domain of widespread adoption. More and more people are downloading and examining various heart rate apps. Consequently, the general public is progressively becoming more and more educated on the subject. However, there is still quite a lot of work ahead before heart rate variability will not be confused with standard heart rate and exist as a separate entity in people’s minds. 

Anyway, the existing progress on grasping basic premises should not in any way interrupt the consistent flow of new knowledge. As such, in this article, I would like to state and answer some more profound questions regarding HRV that, in my humble opinion, will enhance and deepen your familiarity with it. Of course, some of them are outright trivial, and some were already answered in there brilliant article (take your time to read it, too!) done by the specialists in the field employed by Welltory – leading blood pressure and heart rate app. Each of us wonders how to restore energy and improve vitality. And while the answers to these questions are not a necessity to be known for you, they are still quite helpful in broadening your horizons. 

The historical remarks of HRV

Heart rate variability is intrinsically bound to the pulse rate. The description and consequent attempts to study it under the ordinary laws of newborn medicine were made briefly in Antiquity. However, only after the invention of the “Physician’s Pulse Watch” in 1707 – which can be considered the first of heart rate variability monitors – the changes in the pulse rate can be evaluated with due preciseness so that scientific methods could be applied to research it. 

The development of ECG in 1895 and the further enhancement of it by Norman Holter, which allowed long-time ambulatory ECG recordings by the portable, accurate heart rate monitor

(the grandfather of modern ECG heart rate variability devices) furtherly sparked the interest in understanding the HRV, particularly in its relation to the prognosis and diagnostics of the illness. 

The algorithms used today to assess HRV were, nonetheless, only developed in NASA in the ’60s to check on astronauts’ health in space conditions. The HRV was used as a non-invasive method to measure the stress level in the body, assess the functional state, the risk of getting sick, and other parameters. Thus, it is not a surprise that such a helpful methodology gradually evolved into an effective diagnostic tool used by healthcare providers throughout the globe.

Is my HRV normal? The rationale of self-content

It is an understandable desire to know whether and how your HRV values correspond with average heart rate variability to follow up (if necessary) with the knowledge of how to increase HRV. However, for the sake of briefness, the detailed response is often dismissed, giving way for the two rules of a thumb – “The higher, the better” and “It is a highly individualized metric” – instead. But what is the basis of these premises? How can an individual get an individualized metric?

Well, see for yourself. The HRV values are born out of many factors, including – but not limited to – predetermined, like age, gender, environmental conditions, genetics, and modifiable ones – anamnestic fitness level and lifestyle choices. Consequently, it is pretty complex to extract any infallible inductions, correlations, and causations except for the lackluster statistical parameters like mean, median, or mode (for example, the standard value of SDNN measure is 141±39 ms it beneficial?). In this regard, even existing papers can be fundamentally flawed.

Therefore, the HRV values alone mean practically nothing to the individual – what really matters are the heart rate variability trends. It is way more practical to use HRV trends created yourself! Using the HRV charts, over time, you will notice those values that serve as the base from which HRV either decreases during stressful situations or increases after taking steps to improve overall mental and physical wellbeing. That base can be considered normal, but only temporarily – for you should strive to move it up higher thanks to the correct lifestyle choices.

Also see: Tips for staying healthier this year

The nature of heart rate variability in respect to the influence of the autonomic nervous system

“Variability is a law of life…” is a part of a famous quote credited to Sir William Osler, a famous physician, and educator. So naturally, the quote has an empiric foundation since the ability to adapt (ergo variability) is the fundamental property of any life form since, without adaptation, no life form can survive. 

The human mechanism of adaptation is regulated by the autonomic nervous system (ANS), with neurons’ nuclei centralized in the gray matter of the brain stem. The ANS is split into two antagonistic branches: the sympathetic nervous system (SNS) and parasympathetic nervous system (PSNS). The SNS regulates the “fight or flight” response – a complex of neurohumoral reactions that helps the organism to outlast what the brain considers a dangerous situation, while PSNS mediates the “rest and digest” response – respectively, a complex of reactions that allows the body to recuperate after such circumstances.

It is important to remember that the heart has its own set of pacemaker cells that generate contrasting impulses. So, in particular, when talking about the heart, it should be understood that SNS impulses serve merely as the throttle pedal, while PSNS – as the brake pedal, respectively. As a result, SNS hyperstimulation can lead to ventricular fibrillation, while PSNS hyperstimulation – to cardiac arrest – are both lethal failures.

Hence, when the SNS stimulation occurs, it increases heart rate and decreases heart rate variability. But the decrease of HRV is born purely of a statistical nuisance here! You can’t fit in much variability when the brain requires 140 BPM, after all! Just consider this: the heart is beating faster, thus the heartbeat intervals are smaller; since the heartbeat intervals are smaller, the statistical discrepancies between each heartbeat are getting smaller as well.