Heart Rate & Exercise Intensity PDF

Hello and welcome back. In this lesson, we're going to talk about whether heart rate is a passé measure of stress and what can other measures add. So my biases that heart rate can be incredibly useful. And so I've made myself a little plot here of heart rate versus work rate, and I just want to shar...

Hello and welcome back. In this lesson, we're going to talk about whether heart rate is a passé measure of stress and what can other measures add. So my biases that heart rate can be incredibly useful. And so I've made myself a little plot here of heart rate versus work rate, and I just want to share a couple pieces here. So typically what we expect is that there is a nice linear relationship between exercise intensity and heart rate. And so somebody might come in with heart rates around 60 on the front end, somebody might show up to perform some exercise with a resting heart rate of around 60. And as we begin to have increases in their work rate, what we would expect is that heart rate will go up accordingly. And in fact, that there will be a relatively linear relationship between the exercise intensity and the heart rate of the individual. However, even though this is a very strong relationship, it's important to note a couple of pieces that we have over here. And that includes some exceptions to this general rule. So the emotional state of the individual certainly can contribute, mental stress can contribute to a higher higher rate than expected and especially prominent is anticipatory effects. So if someone knows that they are going to actually be measured during the exercise, or they're anxious about the exercise to be performed, then one of the things that we can expect is that they show up with much higher heart rates. And so we expect then that there will initially be something kind of like this, that same person came in quite anxious, it would begin to be more like this. Okay, so these anticipatory effects can be a bit confusing on the front end of exercise and it's typically because people are quite anxious. But part of the reason that heart rate is so valuable is that it also can provide us a consideration of training effects. So if someone was to come back and perform these exact same work rates, and so we might put these into a context that's easier to appreciate. These could be, for example, in miles per hour. So if we put them on a treadmill at the exact same speeds, what we would expect is that after training these heart rates would be lower. So we would have a shift in the heart rate values at every intensity. We would still expect there to be a linear relationship, but what we expect is that person could continue to go out to faster and faster speeds. And that their heart rates would be lower at each of the absolute speeds that were provided as we're seeing on this slide here. So what we're seeing here in the blue line is a classic response of heart rate to increasing intensity. A linear relationship from resting level of heart rate, up until maximal exercise. We expect there to be a linear relationship. The red line here is describing what happens in the setting of an anticipatory effect where someone comes in with anxiety about the exercise they're about to perform. And as a result of that anxiety at baseline, their apparent resting heart rate is much higher, maybe 30 beats higher. And so they begin to exercise and the heart rates will stay considerably higher for some time. But eventually, as they get up to higher and higher intensities, it will basically converge and be very similar to the heart rate of the person who came in with a very linear relationship, who's not anxious. And then in our black line, we're describing someone after training. So if the blue line was a person who is not accustomed to exercise, the black line, which is always falling below the blue line. Is describing that for any intensity, let's say we put someone on a treadmill at 8mph, we would expect the person after training, after say, weeks or months of training, they would be able to run on the treadmill at that same speed with a considerably lower heart rate. And so this idea of a linear relationship between heart rate and intensity is something that we see not only in fit individuals, but also in people that are not regularly active. So we've talked about the relationship between exercise intensity and heart rate, and I've given my bias that I think heart rate is great, but let's talk about the actual pros and cons. So a great pro is that it's a very accessible measure, and it's especially accessible at rest. It's also very simple to understand. We appreciate what heart rate is, it is a vital sign that everyone is pretty familiar with. And it's also easily analyzed. Some of the cons we've already introduced, but the major issue is that it can be influenced by other factors. So we've already mentioned mental and emotional stress, but in addition, environmental conditions can also play a major role on heart rate. For example, if we were to go back to that last slide and look at the relationship between intensity and heart rate. What we'd expect is if we put that same person on the treadmill at 8mph, but in a high heat condition that they would have a higher heart rate despite doing the exact same exercise. Currently, wearable devices are using heart rate to capture many things. We've already spoken some about resting heart rate, and this is often used as a surrogate of recovery status. In addition, we've spoken about exercise heart rate as a measure of relative exercise intensity. Another piece is heart rate during sleep to help characterize different sleep stages. And finally, something that we'll dive into in this lesson is heart rate variability, which can be used to capture information about the state of the autonomic nervous system. Is all this high rate data use just because it's easy to collect. Well heart rate can serve as an excellent dynamic measure of stress. As periods of low activity or inactivity can result in rapid heart rate reductions as observed in this figure here. This is actual data from an athlete in the middle of a competition. And what we can see is changes in heart rate between about 100 beats per minute and nearly 200 beats per minute. I'm cheating a little bit because I'm including in this figure, some external measures, in this case, of the distance traveled per second on the bottom and the player load in the middle. So as you can see here, heart rate can be a great dynamic measure that gives us rapid feedback on the status of the athlete. However, people are often interested in the latest and greatest measures. So let's take a look at some other novel measures of training stress. The Moxy monitor is a commercially available device that allows the detection of skeletal muscle oxygenation. It works by measuring the amount of oxygenated and deoxygenated blood detected in the tissue near the skin surface where the device is placed. It provides a measure of skeletal muscle oxygenation, which is determined by the amount of oxygen being delivered to a muscle, and the amount being consumed by that muscle. It is critical to appreciate that the device readout is highly specific to the location where it is placed. So this device we're describing, the Moxy monitor, is measuring what's referred to as SmO2 or skeletal muscle oxygenation. So is there a relationship between skeletal muscle oxygenation and fatigue? Is a drop in skeletal muscle oxygenation proof of fatigue? Well, over the course of an exercise session, the skeletal muscle oxygenation value can fluctuate based on the effort of the muscle being evaluated and the blood flow to that muscle. It's important to note that skeletal muscle oxygenation may drop even during the warm up of exercise. However, during that muscles maximal effort we expect skeletal muscle oxygenation may drop significantly. Demonstrating that oxygen is not being delivered as fast as it is being used at that muscle. Let's take a look at a specific example. This is a measure performed by some non wearable devices that work very similarly to the Moxy monitor. And this is a little bit of a busy slide, at the top we see a second x-axis, and I'd like you to pay close attention to that. That's providing us the power of the athlete in this case is a cyclist. So we're basically seeing their values at rest, at time zero, this is a cyclist sitting on their bike ready to perform some exercise. And then there is increasing intensity similar to the graph that we drew earlier. So we're having increasing intensity in a few minutes stages, from 0 to 30 watts to 60 watts, all the way up to 270 watts. And we're seeing skeletal muscle oxygenation here on the y-axis. So during those early stages, that is a very gradual increase, there's plenty of blood delivery to that skeletal muscle. And so as a result, we do not see any drop, or maybe even a slight increase in the skeletal muscle oxygenation. But once this athlete gets up about halfway through this, up to about 150 watts, or 180 watts, we see that the skeletal most oxygenation begins to drop off. And in the last stages near maximal effort, we see that these values begin to really plummet. As soon as the athlete finishes, they can no longer continue at 270 watts. They dropped them back down to that initial stage of 30 watts. And the skeletal muscle oxygenation values very quickly ramp back up, right back towards where they were before, or even higher than they were at the start. So regarding this measure of skeletal muscle oxygenation, let's talk a bit about the pros and the cons. It's highly specific feedback that you're receiving regarding this oxygen availability and it's specific to the target where the device is placed. It's potentially a marker for fatigue as well. On the con side, this is just one device and it's providing feedback for only one muscle. So though you could have someone wearing 12 of these all over different muscle groups, it becomes quite expensive as well as a bit complicated. We will return to more examples of skeletal muscle oxygenation in our next topic when we talk about combining internal and external measurements. Next, let's talk about skeletal muscle activation. For this, we're going to talk about the internal device that's referred to as Athos. Athos is a garment that allows us to measure muscle electromyography, in this case through surface EMG or surface electromyography. This is a method for detecting the amount of electrical activity occurring in a particular muscle by measuring the electrical signal present at the skin surface. The white circles you see here on the garment, on the bottom, are what come in contact with the targeted muscles, allowing the device to record the muscle activation that occurs. Real time visualization of the muscle activation patterns can be seen on the associated IOS app. In the upper graph, what we're seeing is data that we collected with the rowing team here, and we captured here 10 strokes, 20 strokes, 30 strokes. And we see kind of increasing some of this muscle activity, and then we see a 10 stroke max where they're providing again only 10 strokes. And what we see is the blue line is indicating a much higher intensity. So it's able to talk about the sum of the muscle activation, but also about the intensity of that activation. So regarding this muscle activation measure, let's talk about the pros and cons. So first it could provide feedback about how much a muscle was activated during a training session. In addition, it can provide real time feedback on muscle recruitment patterns. However, the feedback that's provided is only providing a limited perspective on the training load that was applied. In addition, the surface EMG electrodes might not have ideal muscle locations on different body sizes and types. One major challenge of the internal measures is accessibility. Many simple wearables allow the wearer to measure heart rate and heart rate variability without the need for extensive technology. However, internal sensors nearly always require a good connection to the wearer. For example, we need direct contact to skin in the case of ECG and PPG. And these two that we just talked about, surface EMG as well as the measure of muscle oxygenation. And one of the biggest problems is with motion artifact which is very common with these internal sensors. So let's recap these internal measures. There are many measures out there that are well established, heart rate and respiratory rate as well as pulse oximetry, and the values are easily and immediately interpretable. Other physiologic measures can be used to assess local training responses, for example, our discussion of muscle activation and muscle oxygenation. And these additional measures can add more information about what is occurring during training or during some physiologic testing. In our next lesson, we will jump into the topic of heart rate variability in order to try and understand why it is often mentioned as being part of athletes readiness for training.