Approximation To The Variability Of The Heart Rate

Edna Cantin
Sep 4, 2018 · 5 min read

In this post, we bring you a small foray into the wonderful world of heart rate variability, what it is for, how it behaves at rest, or in exercise, and the valuable information that we can extract with regard to just looking at the value that the heart rate monitor shows us when we are “at rest”.

Let’s Go By Parts. What Is The Variability Of The Heart Rate?

Variability of the heart rate: variation that occurs in the time interval between two consecutive heartbeats. It is obtained by identifying the moment where each R wave appears and the time elapsed between two consecutive R waves is calculated.

The Heart Rate Variability (HRV) is an indicator parameter of the level of cardiovascular health so that its analysis allows a non-invasive study of the activity of the autonomic nervous system (SNA composed of sympathetic and parasympathetic nervous system) on the sinus node. The exact relationship between HRV and SNA is not well known, but it can be stated that when sympathetic activity increases, there is a decrease in HRV, whereas when parasympathetic activity predominates, HRV increases. Therefore, the HRV reflects how the SNA takes part of control over the cardiovascular system, so if we have a high HRV we are facing a correct functioning of the SNA, with a predominance of the parasympathetic and a low HRV would mean an unbalanced or abnormal functioning, insufficient adaptability of the SNA, predominance of the sympathetic, which would lead us to indicate a poor state of health.

What Happens When We Exercise?

During exercise, both sympathetic and parasympathetic activity participate in the control of heart rate, in this case, the sympathetic predominates and an immediate and acute effect is the increase in heart rate (release of catecholamines, increased myocardial contractility). As we know, if physical exercise is maintained over time and is performed continuously, there is a predominance of parasympathetic activity and a decrease in resting HR.

Having internalised the aforementioned, when we are doing physical exercise, HRV tends to be lower, and when we return to rest, the HRV tends to increase. In addition to comparative studies between healthy subjects and cardiopathy, in the scientific literature, we can find how HRV and its analysis can help us to diagnose the assimilation of the internal load and the possible overtraining of athletes early.

The most important applications for training are the following:

· To better understand the behaviour and meaning of the heart rate to not only look at the “beats per minute at rest” data.

· Know the state of health and the capacity of cardiovascular adaptation to each effort.

· Know the assimilation of consecutive workloads and, therefore, have an alarm signal for fatigue and overtraining.

· Differentiate the sympathetic or parasympathetic predominance in different situations.

· It’s simple and cheap. Very favourable cost/benefit ratio for its great applicability.

How Can We Measure It?

First of all, in order to measure VFC, we need a frequency measuring device with a corresponding receiver that allows the extraction of the data from each heartbeat, so that we can analyse said data and draw conclusions that give us valuable information.

There are many types of measurements, at baseline (at rest or during sleep), prior to the effort and during recovery (acute, or during close sleep).

There are linear methods (such as the time domain and the frequency domain) and non-linear methods (such as the poincaré graphic) for the analysis of HRV.

Among the linear methods, those that professionals for the analysis of the VFC are the following:

· SDNN: Standard deviation of RR intervals (Time enters each beat). This parameter indicates the minimum range established with the standard deviation, by which the variability must be at least greater than 100 ms. These values ​​if they are between 50–100 would be a dangerous zone, <50ms would be pathological.

· RMSSD: The difference between one heartbeat and another (ms) is collected in a different column (assuming that the values ​​are being analysed in an excel sheet), and with those values, ​​we make a standard deviation. This value> 20 can be used in a normal population. In young people and athletes, the normal is:> 30.

· PNN50: Number of pairs of adjacent RR intervals that differ by more than 50 ms in the complete record, divided by the total number of RR intervals, expressed as a percentage. > 3 would be valid values ​​for the normal population. In athletes and young people, it is usually in values> 10

· Stress-Score (SS): Inverse of the diameter SD2 multiplied by 1000. The normal resting values ​​of the SS should be <10. And different healthy lifestyle app is also used.

· S / PS ratio: quotient between SS and SD1 in order to obtain a real relationship between sympathetic and parasympathetic that reflects the autonomous balance through HRV. The lower this value is, the greater the parasympathetic domain and the less sympathetic activation by the SS values. When these values ​​increase to levels of for example 10–12, it means that the denominator is very low and the numerator becomes larger and therefore there is an activation of the sympathetic system in rest situations and therefore the assimilation of the load on the subject is not being “good”.

For non-linear methods we use the Poincaré Graph: In this graph, we can see the transversal axis (SD1), which shows us the sympathetic activity and is proportional to it. However, the longitudinal axis (SD2) shows sympathetic activity but is inversely proportional, therefore, the lower this SD2, the more sympathetic activity we will have. The more variability there is, the greater the point cloud. An ellipse is being configured. Which will have a greater longitudinal diameter and a smaller transversal diameter (in rest situation). When we exercise, we tend to the point, and therefore to the zero or zero variability;

SD1: Normal values ​​are> 30, which would indicate a high level of parasympathetic activity when these values ​​we can appreciate the disappearance of parasympathetic control.

SD2: Normal values ​​are> 70, (in sports population is usually higher, values ​​of 100–120) which would indicate a low level of sympathetic activity, when these values ​​fall, below 50–60 approx, we can affirm that sympathetic activity is taking on strength due to the inversely proportional component of “Poincaré”.

We hope this small grain of sand has been helpful for an approach to VFC.

Finally, to think… Is life a complex phenomenon?. Are we complex non-linear dynamic systems? Our behaviour is not expressible as the sum of the behaviours of the descriptors. And we are not subject to the principle of superposition. Are we difficult to model, and our behaviour with respect to a given variable is extremely difficult to predict (Very high sensitivity to initial conditions)?

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Edna Cantin

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Edna Cantin is one of the best psychologist of Florida. She possess a vast experience in the field of psychology.

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