Arguably, the most common measure used to control exercise intensity among competitive athletes is heart rate. The development of small, affordable, portable telemetry units has resulted in their widespread use among fitness enthusiasts. Furthermore , they are used not only to gauge exercise training intensity, but also to regulate race pace and recovery. The question I pose is how accurate is this data in terms of monitoring exercise intensity? The accuracy of the monitor is not in question for it is high, but are the calculations accurate enough to make the numbers meaningful? Furthermore, those who train with HR monitors and training zones are often using predicted values that can vary from true numbers by as much as 20 beats per minute.

Few will argue that the quality of an exercise session is for the most part determined by intensity. In the field, on the track, or in the water, heart rate monitoring allows for more accurate regulation of exercise intensity when compared to traditional measures of perceived intensity such as the Borg perceived exertion scale. The key to this intensity regulation is based on target heart rate calculation to determine exercise intensity at a relative percent of maximum heart rate (MHR). There are several methods of calculating this zone, all yielding varying responses.

Equation 1: 220 – age = MHR
Equation 2: 210 – 0.5 age = MHR
Equation 3: Karvonen formula (uses 220 – age for MHR).
MHR minus resting heart rate (RHR) = heart rate reserve (HRR)
Intensity = % x HRR + RHR

You will note that the determining factor in all calculations is age and it is well established that MHR declines with increasing age and age alone is the sole determining factor. However, like most physiological variables, there is a high degree of inter-individual variation. Consider the following numbers based on calculating 70-80% training zones for a 40 year old (RHR 65bpm) using each method.

Equation 1: 220 – age = 180bpm (MHR) = 126 – 144 bpm
Equation 2: 210 – 0.5 age = 190bpm (MHR) = 133 – 152 bpm
Equation 3: HRR = 155, = 145 – 157 bpm

Using these simple figures alone we have up to a 14% variation in the low-end exercise heart rate. For serious athletes this is a huge difference, which will yield considerable variations in training outcomes. This problem may be compounded when we are actually unsure if any of these numbers are correct? What do I mean?

The savvy reader will note that the major limitation in all calculations is the absence of a true measure of MHR. This is really what all athletes need individually and should determine periodically during their training phases. This does not need sophisticated equipment, but merely an accurately administered and progressive protocol that incrementally will exhaust the athlete in 12-15 minutes. This often requires a little experience in that if you fatigue too early or too late you often don’t get good data. Of course you’ll need a heart rate monitor and then simply record the maximum heart rate achieved during the session (typically it will occur as the athlete is exhausted). When we fitness test we use a telemetry system where we can constantly monitor the response and also relate the HR response to both wattage and 500 meter splits.This number will yield much greater accuracy than a traditional prediction equation. So, how much more accurate will this number be?

You should remember that the mode of exercise used will yield varying responses. Running will yield a higher MHR than cycling for most people. Cycling will be higher if you are a trained cyclist and the same holds true for rowing. Therefore, as a rower you should perform this trial on the ergometer (easier to control) or on the water. Each athlete should have their own individually measured MHR and remember their target zones. Data from research illustrates this variation in calculated heart rates quite nicely. They firstly showed the variation in MHR as a function of mode and also showed that running produced MHR numbers close to the 220 – age equation. The numbers generated on the treadmill were significantly different from all other calculations. The numbers generated during cycling were significantly less than predicted (on average 18 bpm) and varied from –35 bpm to +16 bpm. I do not have any data for rowing but here at University of Vermont we are in the process of looking at this data. Cycling data was on average 96% of treadmill data. A meta-analysis by some authors suggested that age accounted for about 75% of MHR variability, others have reported lower percent explanation more recently. On average the HR variability from age predicted MHR is ± 10 – 12 bpm.

Using the data from earlier we now see that a 40 year old using a prediction equation could exercise anywhere from 124 – 144 bpm and assume it was 70%. This is a large variation and not altogether accurate. The take home message is that many of us will have a MHR that varies significantly from the predicted values and if we are using these equations may be well off the mark. Therefore, a simple approach to increase your accuracy and reliability is to measure your own MHR and then calculate your percent intensity using this ‘real’ number. As an endnote, the determination of MHR requires a maximal effort and therefore for selected individuals presents a potentially dangerous situation. As with all exercise programs, prior to commencement, all individuals should consult with their physician for clearance to begin exercising and find appropriately qualified and skilled personnel to administer the testing..

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