Honing Your Heart Rate?

By
Declan Connolly, PH.D, FACSM, CSCS*D
Posted April 29th, 2009

For years and years we’ve been testing people in our Human Performance lab at UVM for all kinds of studies ranging from fluid intake to heat tolerance. One thing that has always plagued me is the accuracy of the maximal heart rate numbers we get. For the most part we don’t really question the data as it’s all carefully collected and monitored. After we collect it, the athletes use it to calculate and recalculate their training zones, thresholds, and the like. For me, the best way to calculate training zones has always been to use real data and not predictions, so the fitness testing approach is very common.
But you know, lots of factors influence heart rate, and they range from age to hydration to effort to training status to hormones. And while we get to control a lot of factors in the lab, one factor that is hard to reproduce is the element of competition and thus hormones, and hormones can affect heart rate a lot. So, I find myself asking this question: “Is heart rate achieved during competition actually higher than we can get in lab?” Well, maybe, and that answer puts us on the quest for the heart rate holy grail. This year, we will do a series of experiments where we’ll record this data under both conditions. Next year, a colleague of mine, Coach Roy Benson, and I will put out a new book on the recent advances on heart rate training. Until then, we are still left with the choice of lab measurement versus calculations (or predictions). And on that topic I have a few comments.
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 and competitive athletes alike. 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. In fact, some data from the Human Performance Laboratory at UVM suggests that in certain populations, prediction equations might only be correct about 15 percent of the time.
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. These are the more common calculation methods:
Equation 1: 220 minus age (yrs) = MHR
Equation 2: 210 minus 0.5 age (yrs) = MHR
Equation 3: Karvonen formula (uses 220 minus age (yrs) 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 pretty much the primary determining factor. However, like most physiological variables, there is a high degree of inter-individual variation. Consider the following numbers based on calculating 70 to 80 percent training zones for a 40-year-old (RHR 65 bpm) using each method.
Equation 1: 220 minus age = 180 bpm MHR (70 to 80%) = 126 to 144 bpm
Equation 2: 210 minus 0.5 age (40) = 190 bpm MHR (70 to 80%) = 133 to 152 bpm
Equation 3: HRR = 155 MHR (70 to 80%) = 145 to 157 bpm
Using these simple figures alone we have up to a 14 percent 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. For multi-sport athletes this should be measured for all sports as MHR does vary between activity modes. This measurement does not need sophisticated equipment, but merely an accurately administered and progressive protocol that incrementally will exhaust the athlete in 12 to 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. Many facilities who offer these services do not understand proper protocol methodology and consequently generate inaccurate data, much to the frustration of the client who then uses it for months without the desired adaptations.
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 wattage, speed, 500-meter splits, etcetera, depending upon whether you run, row, or bike. This number will yield much greater accuracy than a traditional prediction equation. Also, be aware that we often see a small spike in MHR following the cessation of maximal exercise and this should not be considered a sustainable max heart rate. This is another common mistake of unqualified personnel.
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, and as a cyclist on the bike, and as a runner on the treadmill. Each athlete should have his or her own individually measured MHR and remember his or her target zone.
The data shows variation in calculated heart rates quite nicely. First it showed the variation in MHR as a function of mode, and it also showed that running produced MHR numbers close to the “220 minus 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 the University of Vermont, we are in the process of looking at this data. Cycling data was, on average, 96 percent of treadmill data. A meta-analysis by some authors suggested that age accounted for about 75 percent of MHR variability; others have reported lower percent explanation more recently. On average, the HR variability from age predicted MHR is ± 10 to 12 bpm.
Using the data from earlier, we now see that a 40 year old using a prediction equation could exercise anywhere from 124 to 144 bpm and assume it is 70 percent. This is a large variation and not altogether accurate. The take-home message is that many of us will have an MHR that varies significantly from the predicted values, and if we are using these equations they may well be 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. Consequently, you should seek qualified personnel to perform your testing.
As a side note, accurate HR determination is not just about competition. Across the spectrum of intensity, our energy substrate usage changes considerably. Heart rate also can be used to monitor our substrate usage, which has implications for fat burning during weight loss programs. But this is another topic.
Declan Connolly is a professor of exercise physiology and kinesiology at the University of Vermont, a fellow of the American College of Sports Medicine, a certified strength and conditioning specialist, past president of the New England American College of Sports Medicine, and consultant to the NHL, NFL, and IOC. He will be speaking about heart rate monitoring at the Skirack on May 13 at 6 p.m. For more information, training tips, and articles by Dr. Connolly, go to www.vermontfit.com.