Heart rate variability analysis: how to improve your training performance

Heart rate variability analysis (HRVA) is fast becoming a versatile instrument for athletes and coaches. In this article Alan Ruddock provides further evidence for HRVA’s efficacy and gives a step-by-step guide for sportsmen and women who wish to use HRVA as a monitoring tool to enhance training response

 

In endurance sports, several ‘endurance markers’ are used to monitor athletes, assess the effects of training and determine training intensity. The most frequently applied models are the ventilatory threshold (VT) and respiratory compensation point (RCP). To identify these endurance markers, athletes normally undertake an incremental exercise test to volitional exhaustion, usually within, but not restricted to, an exercise physiology laboratory.

VT and RCP are identified using cardiopulmonary gas analysis equipment, which continuously measures oxygen and carbon dioxide concentrations and the flow of air inhaled and exhaled by athletes during exercise. As exercise intensity increases during the test, so does lactate and hydrogen ion production, and as the body attempts to ‘buffer’ the hydrogen, an increase in carbon dioxide occurs. The response of the physiological system is to increase ventilation (the total volume of gas being inspired and expired) to expel the carbon dioxide.

The point at which lactate begins to accumulate rapidly in the blood, causing an increase in ventilation is important to sport scientists because several studies have reported a strong correlation between these markers and endurance performance. For instance, an athlete’s running speed at a lactate concentration of 2.5mmol/L-1 appears to be highly predictive of distance running performance at distance events such as the 10,000m and marathon(1).

The problem, however, is that blood lactate and ventilatory assessments are primarily restricted by laboratory protocols and expensive equipment that makes testing large numbers of athletes out in the field extremely difficult.

Consequently, an inexpensive and non-invasive method to assess ventilatory thresholds has been proposed using HRVA.
HRVA is a non-invasive assessment of the autonomic nervous system’s (ANS) control of heart rate. Heart rate variability reflects the time intervals between ‘R spikes’ of the ‘QRS complex’ displayed by an electrocardiogram (see figure 1 for explanation).



The ANS functions without consciousness or volition and regulates numerous bodily functions via the sympathetic and parasympathetic nerves. Activity of the sympathetic nerves constricts blood vessels, decreases gastric movement, constricts sphincters and increases heart rate while parasympathetic nerves have the opposite effects. In heart tissue, sympathetic nerve endings are situated on the myocardium, while parasympathetic nerves on the sino-atrial node, atrial myocardium and atrio-ventricular node. Together these nerves act to control both heart rate and force of contraction.

HRV and ventilation

Several theories have been proposed to explain why HRV and ventilation are closely related. These theories propose that the ANS detects changes in blood pressure, cell chemistry, force sensors, local tissue metabolism and circulating hormones, which causes an appropriate response via the sympathetic or parasympathetic nerves in an attempt to maintain homeostasis.

The most studied theory in relation to HRV and exercise is that of respiratory sinus arrhythmia (RSA). RSA is an interaction between respiration and circulation whereby normal heartbeat and blood pressure vary secondary to respiration. The synchronicity can be seen in heart rate variability where R-R intervals are shortened during inspiration and prolonged during expiration.

During inspiration, the activity of the cardiac parasympathetic nerve is almost abolished, which results in a shortening of the R-R interval. In contrast, during expiration, the cardiac parasympathetic nerve reaches its maximum thus extending the R-R interval(2). Think of it like this: when you inhale, you feel your muscles that control inhalation contract, which is when the sympathetic nervous system is predominant. When you expire you feel more relaxed – this is when the parasympathetic nerves are dominant. This link between respiration and HRV has led sports scientists to research into the effectiveness of HRV to detect ventilatory thresholds.

There are numerous ways to process/analyse HRV data and it is far beyond the scope of this article to explain how. Instead, interested readers are directed to the HRV standards and guidelines for clinical use for a detailed explanation(3).

However, while the study of HRV and ventilatory thresholds is a fairly new domain, back in the late eighties a piece of research was carried out that identified VT using breathing frequency (breaths per minute)(4). Since then ventilatory thresholds have been identified using different methods with reasonable reliability.

Recently, researchers from France looked at the relationship between HRV and ventilatory thresholds(5). Using both sedentary and athletic participants they found that the HRV method used to detect ventilatory thresholds was highly correlated with a gas analysis method for detecting ventilatory thresholds. In other words, the point at which VT was detected using gas analysis was close to the point at which the HRV method estimated VT. The researchers concluded that HRV was a useful tool for identifying ventilatory thresholds in both sedentary and athletic populations.
Other researchers have used different methods of HRVA analysis to detect ventilatory thresholds and despite differences in methods of analysis compared to previous studies, these groups have found HRV analysis to be a potentially reliable tool for detecting ventilatory thresholds.

For example, a group from France used a field-based incremental exercise test to determine whether ventilatory thresholds could be detected using HRV in professional French football players(6). These researchers used a commercially available Polar S810 heart rate monitor to record R-R intervals. After data analysis they found that HRV analysis underestimated VT by 0.25kmh-1 and RCP by 0.5kmh-1. Statistically, there were no significant differences between the HRV method and gas analysis in detecting either threshold. This led the researchers to conclude that the study provided an advance in exercise physiology since coaches now have the ability to assess ventilatory thresholds of athletes using inexpensive HR monitors.



Despite these studies, there are still no universally agreed or simple and objective methods to determine ventilatory thresholds using HRV analysis. The news, however, is that even though there are technical difficulties when using HRV to detect ventilatory thresholds, HRVA still provides a simple and effective method that will allow you to guide your recovery and training with more reliability than just subjective perception.This method is based upon the principle that when athletes are overreaching, overtrained or even recovering from a training session, parasympathetic nervous system activity will be reduced. In order for training to be effective, the body needs to have recovered from the previous training session (see PP246 for a more detailed explanation) but if too much time between training bouts has elapsed then gains begin to slowly reduce. The idea then, is to monitor the parasympathetic nervous system using HRV; this method allows coaches and athletes to determine the state of autonomic function and therefore tailor future training sessions appropriately.

• Parasympathetic nervous system activity reduced – decrease training load;
• Parasympathetic nervous system activity increased – increase training load.

Pioneering Finnish researchers have shown that by using this method VT, maximal rate of oxygen uptake (VO2max) and running speed at VO2max can be improved by four weeks of training consisting of running sessions at either a low intensity (65% maxHR [maximum heart rate], duration 40-mins) or high intensity (85% maxHR, duration 30-mins)(7). The scientists took 30 recreational runners aged between 22 and 40 and split them into three groups, 10 in the HRV group (HRV), 10 in the training group (TRA) and 10 in the control group (CON).

• In the HRV group the researchers recorded HRV on a daily basis. Before any training began for the HRV group, a 10-day rest period was implemented to collect baseline HRV measures. Then, during the intervention, if HRV dropped below the calculated reference value, the training load was reduced;
• The participants in the TRA group undertook a standard pre-planned training programme with no measure of HRV;
• Participants in the control group undertook no training.

The results showed that the HRV training group significantly increased their VO2max (from 56 to 60mls/kg/min-1), their maximal running velocity at VO2max (from 15.5 to 16.4kmh-1) and their running speed at VT (from 12.0 to 12.7kmh-1). By contrast, only maximal running velocity at VO2max significantly increased for the participants in the training group. Moreover, the participants in the HRV group undertook more training at a low intensity than the TRA group. The researchers concluded that whenever HRV is lowered, a lower training stimulus might be beneficial to gain a favourable response to endurance training.

Step-by-step guide to using HRV in your own training

The method that the Finnish researchers used to adjust training intensity using HRV is a relatively simple process that can be applied to guide your own endurance training. To do this you will need a Polar heart rate (HR) monitor that records R-R intervals (RS800 series, S810 series), Polar Precision Performance SW 4.0 software, which you can download for free from www.polar.fi. You will also need a spreadsheet package such as Microsoft Excel.

Step1 – The first thing you’ll need to do is to set up your HR monitor to record R-R intervals, referring to your user manual to do this. Before you start using HRV to guide your training, you need to undergo a period of rest (no training) to collect resting baseline values; this period should last between seven and 10 days.

When you’ve decided on when this period will be, you’re ready to start recording. The best time to record HRV is in the morning immediately after you have woken up and emptied your bladder. This will ensure you get the most reliable measure of parasympathetic activity as it is less likely that it will be affected by external influences such as physical activity, dietary intake or psychological stressors. If you regularly measure your morning HR, you need to record HRV when standing up for 5 minutes. This is so your HRV measure isn’t ‘swamped’ by parasympathetic nervous system activity, which occurs when you lie down.

Step 2 – After you’ve recorded this HRV data, import it into the Polar Precision Performance SW 4.0 software. Present the data as a ‘curve of the HR values’ and then right click on the curve to display ‘curve properties’. Under the HR tab, change the HR format to ‘RR Intervals (ms)’. This will display your RR intervals.



Step 3 – In the ‘edit menu’, select the entire exercise then click the right mouse button on the graph and select ‘Error Correction’ in the dialog box. Now select ‘OK’ to remove any errors in the R-R plot.

Step 4 – Right click on the graph and choose the ‘Selection Info’ option. This will bring up a dialog box with information regarding the HRV measure. Look for the ‘HF (0.15 – 0.40 Hz)’ value and make a note of it. Let’s assume (for the next step) you get an HF value of 321.94.

Step 5 – The next stage is to calculate the natural logarithm of the HF value. To do this open Microsoft Excel and in a cell type the command ‘=Ln(321.94)’. This will give you a result for the log of HF (HF Ln) of 5.77ms2. Of course, you’ll have your own HF values – simply substitute the example given above for the calculated HF (0.15-0.40 Hz) value displayed by the Polar software which you’ll obtain from your own data.

Step 6 – Following your baseline period, you need to calculate the standard deviation of these values by typing ‘=STDEV’ in Excel and then selecting all the reported HF Ln values for your baseline/rest period. Calculate the average of the HF Ln values and then subtract the standard deviation you’ve just calculated to obtain the daily reference value for HRV guided training. For each subsequent day calculate the average and standard deviation of the total HF Ln values; this will produce a moving day-by-day reference value.

Step 7 – When you record your HRV after your baseline period (ie when you begin training), you must then calculate HF Ln values using the method described above. If your HF Ln value is above the reference (baseline) value then it is likely that your body is rested and ready for a high-intensity training stimulus. If the HF Ln is below the reference value then you must reduce the training stimulus. Figure 3 shows you how this data will appear in Excel.

Conclusion

HRV analysis provides a non-invasive assessment of the parasympathetic and sympathetic nervous systems. Recent articles in PP and the scientific community have shown that HRVA has the potential to be a versatile tool for athletes, coaches and sports scientists. Researchers are close to providing a simple and valid method for estimating ventilatory thresholds during field-testing by using HRVA but at the moment there exists no definitive method. However, it is possible for athletes and coaches to use HRV analysis to guide endurance training by estimating the level of recovery through quantifying parasympathetic nervous system activity. This method has been proved successful by Finish researchers and with some application, may well aid your training too!

Alan Ruddock MSc, CSCS, YCS is a researcher in exercise physiology at Sheffield Hallam University, UK