COACHING – HEART RATE VARIABILITY

Heart Rate Variability

Ben Wisbey and David Shepherd

“I once watched a snail crawl along the edge of a straight razor. Crawling, slipping. And surviving”. This was Marlon Brando as Colonel Kurtz in Apocalypse Now. Training to compete at the top level is like walking the edge of a razor – too far back from the edge and the athlete won’t reach their potential, step over the edge and the consequences are even worse. How then does the athlete know where the edge is? The snail that Kurtz sees in his nightmare can see the edge, but for an athlete there is no physical edge. How often have you wondered if you should be doing that quality session today despite being a bit flat? How often have you wondered whether you were fatigued or just lacking motivation? Heart Rate Variability (HRV) is a tool that has recently been developed to help an athlete visualize the edge of the razor.

What Is HRV?

HRV is essentially the variation in the time between heart beats. A heart rate of 60 beats per minute (BPM) does not necessarily imply the heart beats once per second like a clock. The time between beats will vary - the degree of this variation is dependent upon factors such as fatigue, sickness, travel, altitude, temperature and even mental stress. We know that heart rate (HR) increases when we exercise, but underlying this is the autonomic nervous system (ANS) which plays a direct role in speeding up and slowing down HR. There are two branches to the ANS that influence HR - the sympathetic nervous system (SNS), responsible for speeding up heart rate; and the parasympathetic nervous system (PNS) which is responsible for slowing HR. Following long term training, lower resting and exercising HR’s are observed and HRV usually increases. However, during periods of excessive training (overtraining) the SNS can be overactive as the body responds poorly to recovery, resulting in an elevated resting HR and minimal variation in HR at rest. ACTAS athlete, Canberra Cockatoo and Australian WOC Team member David Shepherd (Shep) has been using HRV analysis provided by Ben Wisbey at FitSense Australia (www.fitsense.com. au) throughout the past 18 months. Recent research shows that using HRV analysis to control the timing of hard training, athletes can actually train less and achieve better results by completing key sessions when the body is ready to adapt to them. HRV analysis has helped Shep train smarter during recovery from ankle surgery late last year and get back into form for the Australian 3-Days and gain selection into the 2006 WOC Team. HRV has also been used by the likes of Commonwealth Games Gold Medallist cyclists Oenone Wood and Natalie Bates, multiple World Champion cyclist Michael Rogers and numerous AFL teams.

Monitoring HRV

Sympathetic and parasympathetic tone can be monitored through tracking HRV on a day-to-day basis so that the athlete’s training state can be assessed. We gain information on fatigue levels, detect overtraining/overreaching, determine training readiness and eventually assist competition preparation by assessing when the athlete is ready to perform. HRV data is obtained using a 5minute orthostatic test - 3 minutes lying down and 2 minutes standing. Orthostasis means upright posture and the change in posture (from prone) causes a change in blood pressure. HR must increase if we stand upright quickly to ensure the blood supply to the brain is sufficient to stop us from fainting. The orthostatic test is a reliable method to determine HRV in athletes since it combines laying and standing. The laying period is dominated by the PNS (slows down HR), with the interaction of the SNS (speeds up HR) upon standing. Using a HR monitor and software we can measure the input from the ANS during the orthostatic test and track the changes over the athlete’s training cycle.

Analysing HRV

This is where it gets a little technical. HRV analysis is not as simple as assessing your resting HR. In fact, the beat-to-beat data is run through a combination of time domain and spectral density analysis so that it can be assessed effectively. While this process may sound a bit high tech, this is what allows the HRV analysis to be such a sensitive measure of stress and performance readiness.

Figure 1: Power spectral density of sample HRV data - we are interested in ratio of the power of the high (RHS) and low (centre) frequency components.

Using HRV

Monitoring HRV means the athlete has current information on their training status, they can see how their body is responding and hence how far they are from the razor’s edge. Knowing this the athlete and their coach can adjust training loads to suit the level of fatigue. Without this information the level of fatigue is subjective - low motivation can trick an athlete into thinking they are fatigued so they skip a session they should have done; conversely highly motivated athletes have been known to “push through” fatigue which can result in the athlete slipping over the edge and overtraining. Denmark’s former world champion Chris Terkelsen overtrained soon after winning the overall World Cup in 1998 and didn’t return to the top for nearly 8 years! HRV information is graphed to create an overall picture of ongoing training stress. A moving average is used to monitor accumulated fatigue while day-to-day measures allow sensitive changes to be assessed on a daily basis. The accumulated trend information is very important in predicting racing performance – excellent performances usually occur as the fatigue begins to rise following a recovery period, which indicates SNS activation which is essential for optimal performance. Bad performances generally occur when large volumes of SNS tone are present, corresponding to high levels of fatigue. Over a period of time an individual athlete’s profile can be established to determine the best training/ recovery combination leading into a race. Training and recovery can then be planned accordingly.

LFHF ratio

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Figure 4: Summary of Shep’s HRV data showing pNN50 (top chart), which is a time-based measure of variability, and the LF/HF power ratio (lower chart) which is filtered (black) to remove daily fluctuations and more easily see the trends. High pNN50 means high variability and is a good indicator of endurance; high values of the LF/HF ratio generally indicate fatigue.

What’s Next?

Figure 2: Shep’s HRV Data on Thursday before the Australian 3-Days - note high variability – fresh for the coming races.

In order to get optimal results from your training, fatigue is something that needs to be considered when deciding whether to continue with a high training load or whether to back it off. There are times when high levels of fatigue are required (and expected) to get gains, without these overload periods, performance will remain stagnant. However, there are also times when excessive fatigue will limit the effect of training. Having the ability to know fatigue levels adds a new dimension to training and allows you to control your training load to walk close to the edge of the razor. HRV analysis is a relatively new tool and new results are being regularly published. Consider the development of a twig with notches at regular intervals to calipers with nanometer accuracy. HRV analysis presents athletes with an objective means of monitoring training for the first time, something to consider for every elite athlete wanting to get the most out of their training. See www.fitsense.com.au for more information on their expert services and www.fitshop.com.au for all training supplies from nutrition to clothing and HR monitors.

Figure 3: Shep’s HRV Data on Tuesday after the Australian 3-Days, showing less variability and indicating the fatigue-related stress response following the four races.

For more information on Shep’s current training, use of HR variability, and training sessions go to www.fitsense.com.au/blogs