The Counting Talk Test

Back in November, I reviewed a series of videos from the online cycling magazine GCN. In that review I mentioned that the authors felt that heart rate was not a good way to identify one's Zone 2, but that breathing rate was. The criterion they suggested for the top of Zone 2 was the point where conversation is forced but possible. This metric is used, in various forms, by many coaches and is called the Talk Test. I do not find the criterion used by GCN easy to use because it is vague; what exactly does it mean for conversation to be forced but possible? Recently, I encountered an alternative version of the Talk Test which I found much easier to use, a version called the Counting Talk Test.

The Counting Talk Test (CTT) is a way of quantitating the Talk Test. In the Counting Talk Test, you exhale, take a deep breath, then count "One one thousand, two one thousand, three one thousand..." until you cannot count one number higher without taking a breath. This measurement is made while resting and then during exercise. The results of the Counting Talk Test is expressed as the percentage of number a patient can reach during exercise relative to what they can reach while resting. The table at the top of the post shows the results of my first attempt to use that test. What I did was get on my trainer, set the gears at 61", ride at 60 rpm for five minutes and then executed the CTT. I then increased the gear to 71" (maintaining my cadence at 60 RPM), rode for five more minutes and then repeated the CTT. I repeated this for  80". 91", and 106". At 106" I was only able to continue for 2 minutes. I then reduced the gear to 71" and measured CTT after 5 then 3 minutes. As I acquired more experience with the CTT, I have gotten better executing it. One consequence of this is that I have decided that my resting CTT is closer to 23 counts rather than the 16 counts measured in that first test, so I now calculate my percentages relative to that constant value of 23.

I encountered the Counting Talk Test in the Journal of Exercise Physiologyonline (JEPonline) Volume 5 Number 1 February 2002. This paper, and in fact every paper I have encountered that investigates the Counting Talk Test, considers it in a medical context rather than a sports context (which is why I used the word patient rather than athlete in the previous paragraph.) The medical community mostly uses a three zone Intensity system, Easy, Moderate and Vigorous, as opposed to the seven Intensity zone (Zones 1 through Zone 7) that the coach I follow, Coach John Hughes, uses. However, over the years I have come to the conclusion that the top of most coaches' Zone 2 and the top of the medical communities' Moderate exercise zone are both equal to each other and equal to the aerobic threshold. Since locating my aerobic threshold is probably the most important use I have for the Talk Test, the difference in training zone systems was not a big limitation. What was a big limitation is that the authors of this paper chose not to distinguish between Moderate and Vigorous exercise but considered the two together (they reported a value for the Counting Talk Test of 55% at the bottom of Moderate Exercise and 30% at the top of Vigorous Exercise.) The value I needed, the boundary between Moderate and Vigorous exercise, was not reported. A search for a scientific study that did report that value lead to Frontiers in Physiology Volume 13 article 832647 2022

The Frontiers in Physiology paper was, in fact, a comparison between the Counting Talk Test and an alternative they developed, the Regulated Monosyllabic Talk Test. I was not persuaded to switch to their Regulated Monosyllabic Talk Test but did find this paper useful because it reported the values for the Counting Talk Test at lower and upper boundaries of the Moderate (63% to 48%) and Vigorous (48% to 32%) exercise zones.

Both of these papers had as their goal the use of some version of the Talk Test to find the boundaries of the Moderate and/or Vigorous Exercise zones. To do that, they had to know where these boundaries are and then measure the value of their Talk Tests at these boundaries. How did they define these boundaries? Unfortunately, they did so using Heart Rate, exactly what GCN (and others) have argued should be avoided. In response to that concern, I compared the CTT to the version of the Talk Test used by GCN and determined that the percentages given in the Frontiers in Physiology appear to be about right, at least for me.

How does the CTT compare to heart rate as a way to measure Intensity? The main thing I use heart rate for is to measure average Intensity of a ride and thus cumulative Load over time and the CTT is impractical for that purpose. The reason I initially pursued it was that it was one more test that I could use to determine if I had correctly located my aerobic threshold. Having done that I now continue to use now and again it because it is free of some of the complexities of heart rate. Heart rate can be higher or lower based on fatigue, stress, caffeine, environmental temperature, etc. Based on my experience so far, CTT seems to be much less sensitive to such considerations. Also, heart rate is a lagging indicator, it takes time for it to increase after Intensity increases. As best I can tell, CTT responds to an increase in Intensity with little or no delay.

Does the aerobic threshold I measure using CTT agree with what I had previously assumed it was? The answer to that question is not so simple, as is illustrated by the following output from the software used by my heart rate monitor:

This ride was on my Trainer and done at a constant effort, 70 RPM in a 71 inch gear. The Counting Talk Test yielded a value of 11 counts which corresponds to 48%, the top of Zone 2. However, my average heart rate over the course of that ride is 123 beats per minute which corresponds to the middle of Zone 2. Is this a disagreement? Perhaps, but note that, although I held my Intensity constant over the 30 minute of the ride, my heart rate was not constant but increased during at least the first half of the ride. If I look at only the second half of the ride, my heart rate, estimated by the white line, is at 132 beats per minute, much closer to the top of Zone 2. I suspect that my heart rate during the first half of the ride is not a good indicator of Intensity because heart rate lags behind Intensity. If this explanation is correct, then the Counting Talk Test agrees with the other approaches I have used to locate my lactate threshold.

In summary, I think the Counting Talk Test is a better way to estimate breathing rate than the approaches suggested by the exercise community to date. To be most useful, the exercise community would have to adopt the CTT (or something similar) and calibrate it against reliable laboratory measures of Intensity like blood glucose or O2/CO2 levels in the breath. This would provide a clear, accurate way for the average athlete to locate their aerobic threshold quickly, easily, and inexpensively. 

Heart Rate and Intensity

If I ride a given route quickly, it will leave me more tired than if I ride it slowly despite the fact that I spend more time riding at the slow speed. That assertion  is widely accepted by the vast majority of exercise scientists, coaches, and athletes. How to quantitate that is more controversial. For some purposes, speed (e.g. miles per hour) is used for such a quantitation. For example, many coaches recommend periodic time trials on a fixed course where the speed at which one can ride that time trial is a measure of Fitness. But because simple speed is affected by so many factors (e.g. hills) it is not usually used as a routine measure of Intensity, the generalized term used to quantitate the impact of different riding speeds. The most common measures used to routinely calculate Intensity are heart rate, power, and relative perceived exertion (RPE.) RPE is the simplest, it is just how hard a ride feels. That is the metric I used in last month's post to determine if I had been riding too much or too hard.

Power is something like a normalized version of speed in that it corrects for factors like hills that affect speed. It is measured using a power meter which is incorporated into the drivetrain of the bicycle. These are widely available if somewhat pricey. Power (like speed) needs to be calibrated for differences in the fitness and ability of different athletes. 150 watts of power might be at the upper end of the amount of Intensity I can manage while being an easy ride for a better cyclist, and the meaning of 150 watts would be different for me at the beginning of the season when I am not very fit versus at my peak fitness after I have trained for an important event. I have never owned a power meter and so I use speed on standard routes as something of a proxy for power.

Two months ago, when I posted about Zone 2 training and how the reporter Manon Lloyd used herself as a guinea pig to investigate Zone 2 training, something I did not mention is that when Lloyd developed a training plan with her coach, he specifically advised her to use both a power meter and a heart rate monitor. Why both? In many ways, power is considered to be the superior metric. It responds instantly to changes in Intensity and is independent of many factors that affect heart rate, things such as stress, caffeine, etc. However, power is rapidly affected by training and that changes are significant. At the beginning of her six weeks of training, if Lloyd rode at the top of Intensity Zone 2, she could generate 140 watts of power. At the end of her six weeks of training, she could generate 160 watts of power at the same level of Intensity. Thus, had she used only power to guide her training, she would have been training at too low an Intensity at the end of her training. Heart rate is also affected by training, but on a much longer time scale. Although not given in the videos, it is likely that Lloyd's Zone 2 heart rate at the beginning and end of her six weeks of training would have been similar or identical. In short, for the purpose of keeping her effort within Intensity Zone 2, power was the better metric over the course of one ride but heart rate was the better metric over the course of six weeks of training.

Although I use RPE as my primary measure of average ride Intensity, I use average heart rate as an important secondary measure. The goal of this post was to determine how reliable average heart rate is and specifically, to compare average heart rate of a ride to the speed of that ride on a standard route. I used two standard routes for that comparison, my Cañada route and my Alpine route. As noted above, the impact of training on ride speed would be expected to confound that comparison. As I train and become more fit, I would expect my speed a given heart rate to increase. To remove that confounding factor, I did my comparison over a period of time during which I felt that my fitness stayed relatively constant. The results for the Cañada route are shown at the top of this post. The results for the Alpine route are shown here:

Encouragingly, the results for the two routes were similar. I will focus here on the results for the Alpine route. This graph shows the results for 19 rides on the Alpine route from June 30, 2024 and October 24, 2024. It begins after I had gotten in shape for metric centuries, a period during which I was attempting to maintain my fitness but not trying to increase it. For each ride, I plotted the average speed of that ride on the vertical axis as a function of the average heart rate for that ride on the horizontal axis. The line is the best fit line through those points. The equation for that line (which can be ignored) is shown at the top of the graph as well as the value for R-squared (R².) R-squared is a measure of how effective heart rate is at predicting ride speed. R-squared varies between 0 and 1, and if both heart rate and ride speed were perfect measures of ride Intensity, R-squared would be 1. The value measured for the Alpine route is approximately 0.7, very similar to that measured on the Cañada route. This is a pretty good correlation between speed and heart rate which means that both of them are pretty good measures of Intensity, but that one or both of them are imperfect measures. Besides Intensity, what might affect ride speed? The two things I can think of are fitness and wind. As noted above, I have done my best to control for fitness and my intuition suggests that wind is not a major factor. Besides Intensity, what might affect heart rate? Unfortunately, many things: caffeine, emotional state, and fatigue* to name but a few. This would suggest that speed is a better indicator of Intensity than is heart rate, so why not just use speed? 

There are two reasons not to use speed instead of heart rate as a measure of Intensity:

1. Speed is only a good indicator for one specific route. It is possible that I might be able to map some kind of equivalence for two commonly ridden routes like the Alpine and Cañada routes, though I worry that even this level of data processing could lead to false conclusions. Perhaps more importantly, many of my rides are ridden over a wide variety of routes, none of which I ride commonly enough to provide the data needed to map speed onto Intensity. That is why many cyclists use power meters.
2. The speed corresponding to a given level of Intensity changes with training. The graph at the top of this post shows data for rides on the Cañada route between June 17 and October 26 of 2024. If I do a similar analysis for rides on the Cañada route between July of 2022 and October of 2024, the R-squared value drops from a respectable 0.70 to a useless 0.36. This is because variations in how much I was training and my resulting fitness varied substantially over that longer time period.

Where does this all leave me? In a pretty good place, I think. It is definitely true that heart rate is an imperfect measure of Intensity for any single ride. During the June through October 2024 time period, four of my rides on the Alpine route resulted in an average heart rate of 126 beats per minute. The speeds of those four rides varied between 10.8 and 11.5 miles per hour. However, the most important use I make of average heart rate applies not to single rides but rather to accumulation of fatigue over time, and for that purpose, these variations tend to cancel each other out so that average heart rate is a perfectly adequate metric. In that context, the R-squared value of 0.7 I determined from the comparison of speed and heart rate gives me confidence that recording my average heart rate is helpful to my training. But how do I use that to estimate accumulated fatigue? I plan to discuss that in a future post.

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* Many coaches advise that when an athlete is fatigued, their heart rate will be lower than usual at a given level of effort. A rationalization sometimes given for that result is that the athlete's heart is "too tired" to beat any faster.