Making Sense of the Data

Marco:
Stability is really what we are after when we look at HRV. And for a very long time it has been pushed the idea that higher is better. more stable is better is not about HRV going up up is about, you know, know, being within that normal range, which means that you stress the body and then it bounces back. And when you measure again, it’s again what it should be.

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Steve:
My guest today is a scientist who has arguably done more than anyone to move heart rate variability out of the lab and into the real world. Doctor Marco Altini holds a Ph.D. in data science and has built a remarkable academic resume. He’s a guest lecturer at Reinier University in Amsterdam, a data scientist and advisor for Aura, and has published over 50 peer-reviewed papers on physiology and health. He’s also the founder of the HRV for training platform. But the reason I wanted to speak to Marco was not so much his software. software. It was more because of his philosophy. In a world where wearable wearables are trying to always sell you a green light or readiness score to run your life and your training. Marco has been a voice of restraint. He has been a data scientist who really understands how HRV works. Telling us that if you wake up feeling great but your watch says you’re tired, you should trust yourself, yourself, not the machine. He’s also a serious athlete himself. He qualified for the Boston Marathon. He’s done ultras, and he treats his own body like kind of a walking laboratory in fact, I’ve been reading along with with his, Substack, where he spent the last few months strictly kind of manipulating as carbohydrate intake to see if you can force his own metabolism to be more flexible and burn more fat. Proving that even for a genius data scientists, the hunger knock is still a real thing. Marco Altini, welcome to the Uphill Athlete Podcast.

Marco:
Thank you. Thank you so much for having me, Steve. Real pleasure to be here.

Steve:
Well, thank you. As I was saying before the show, you’ve had a lot of influence on us as a group of coaches. And I think that this, like, Voice of reason has been a big reason for that. And you know that the wearables industry has been obsessed with this idea of a readiness score, a watch or device that tells you your body battery is 80% charged, and you’ve been pretty vocal that these aggregated scores can be very misleading. And can you help me understand why a single readiness number may or may not be scientifically flawed?

Marco:
Yeah. Yeah. For sure. I think there’s a topic that’s been close to my heart for a while. In, in, in, I’ll say that in principle. What they do, let’s say the companies developing this course kind of makes sense. Like, even if we, you know, it could come from a positive approach, even to their own story. Like not trying to, you know, trick the user in any way, of course, but trying to help them, you know, it’s a simple idea, like we have many signals so we aggregate them and then you don’t have to look at

Steve:
Yes.

Marco:
at all the individual things. You don’t need to be an expert in your sleep stages, in your HRV or resting heart rate, in your training behavior, and all sorts of things that are included in this score. And we just guide you this way. But I think eventually what happens is that this course do us a bit of a disservice because especially as athletes or people that are really interested in their training and, you know, their body is responding to their training, right? Am I getting better? Am I capable of assimilating more stress today? Which is why we started developing these tools right? When we put everything together, we give maybe the false impression that we are providing more information, but we are actually, I think, diluting that information. For example, if I have a negative readiness score today and that comes from my behavior, not my physiological response, because everything is together and the model makes assumptions, right? That is this idea that is instructing us personalized to you. But in reality, there are broad generalizations and assumptions that are made for the score to exist. For example, do you do or did you do a lot more physical activity than you normally do? Then you must be less right that your score must be lower. You must be less. Recall it right? It is a simple deterministic thing. It’s not really about how you respond; it is just that more exercise means less readiness, and similarly, less sleep means less readiness. But you know, the hub really is a complex biological system. It’s not so simple. Maybe you can take two or three nights with poor sleep. And of course, you don’t want to make that chronic. So the behavior matters. But it does not mean that on those days you cannot perform or you cannot assimilate monsters. So I think

Steve:
We should.

Marco:
think eventually, especially as athletes, we might be interested in looking at our resting physiology, as you said, you know, spent many years developing tools and looking at this data. I believe the data is useful, but I think it is more useful to look at the resting physiology data resting heart rate, resting heart rate variability in response to our behavior. So using behavior as context more than, you know, aggregating going to get everything together and making began the assumption that you can determine what is the state of the body. Because we cannot do that. And I think that also, as other implications, because if we look at actually, we could also talk to an athlete as a coach and explain what that is and why we look at it and also its limitations, why the idea of

Steve:
You should.

Marco:
of the recovery or readiness scores is indeed that it puts everything together. And that’s such that is sort of no limitation, right? It’s it’s a comprehensive

Steve:
Who? We?

Marco:
A comprehensive score of how you feel. feel. But then we know, for example, that the main limiter for most athletes in endurance sports is probably, on a given day, muscle soreness. Right. If we did a hard session yesterday, then we might be sore and unable to do another one today. Even if our resting discharges are perfectly normal and those kinds of things. For example, for the muscle, our point of view cannot be captured by any of these technologies that are available today and is to use. So it’s just something that is part of the equation. And as a coach or as an athlete, you need to keep your mind, of course. And that’s why with that nice training and plan, you know, hard days, easy days, obviously there’s that component is always present in our mind, but it’s not tracked by the device. So I think, again, the compound score, the the readiness recovery score hides also these limitations of the technology. And the people expect that those things can also be tracked, but they cannot. So I think we we are just better off, you know, breaking it down again and looking at the individual components and looking at the objective data and then looking at the behavior and then of course, that’s always the subjective component that in my view, and I guess so. So your view is one of the key components. But that doesn’t fit the rhetoric of the tool automates everything. And you don’t have to do anything. So you don’t and you know fill in a questionnaire. But anything like that before getting the score because like the the score knows your body better than you, which of course it’s not the case.

Steve:
So what I’m hearing you say too is that and we’ve been talking about readiness score. We’re also going to talk about heart rate variability. And they’re, they’re related, but they’re two different things. I want to clarify that. So let’s let’s dial in a little more tightly on, HRV. why is HRV HRV a response to stress more than a predictor of performance? And can you kind of unpack that? I think that this is kind of one of the core misunderstandings of heart rate variability. And yeah. Can you help us understand how that works?

Marco:
Yeah. Yeah. So heart variability, if we measure it at the right time, which I think is important because at the beginning this

Steve:
Okay.

Marco:
This was taken for granted. But right right now there are tools that measure it all the time. And if separate, what could be done at a certain time. Still, you know, 24 seven and those that that relationship doesn’t really exist. And the tool cannot be used that way. But let’s say we measure at the right time. And that typically means.

Steve:
Right. Quick means pause there. What is the right time? I got to know.

Marco:
The. Yeah. So the right time I would say either first thing in the morning or with some different considerations throughout the night. So the way wearables do it automatically as you sleep, I think is also fine. What defense there is that that of course you measure earlier while in the morning you measure after the restorative effect of sleep. So in my opinion it is a better time for that reason because you you give more

Steve:
Okay.

Marco:
more time to the body to recover from the stressors of the previous day. And also you include the sleep as as a positive. If the sleep point to a stressor or otherwise if disrupted or anything like that, you still capture your data first thing in the morning after that. And also measuring in the morning allows you to measure in a different body position, which I think also is key, especially for endurance athletes. So to measure when you are setting up, the body is slightly more stressed. So to speak, and that makes the measurement more sensitive to stress. So changes that while you are sleeping are very small, those typically are the changes due to training and even going to altitude and things like that. So sometimes it’s more subtle changes, especially for good athletes. And if you sit up and then measure shortly after that, say within a minute those changes are amplified. So then the measurement becomes more more useful because you see these things better while the night measurements, you know, you will suddenly see if you are sick. But that’s, you know, an enormous stressor that hopefully you’re not facing very frequently. Right? So if you want to really balance training and things and things like that, then again, the modeling might be a better time. So let’s say we measure heavy at those times. What the data reflects is our capacity to assimilate stress in that moment. Let’s say. So for the day ahead as we plan training and not necessarily our capacity to actually perform. So and that is indeed a common misconception, like in the past, especially, I think a lot of people thought with a low heavy load typically means higher stress. Right? So it’s a negative thing. So with a lower level we give a lot of trouble executing the training. But that is not really really the case. And we’ve seen this quite a few studies. Also typically in the world of let’s say actually guided training, which means that, you know, you have two groups of people, one is doing some form of periodization and the other group is doing the same. same. But then the periodization is slightly adjusted on a day-to-day basis, depending on the day that should be taken. So that’s why it’s actually guided. So what you see eventually is that it’s not as much about what you can do, but it’s about how much you can assimilate of the workout to get better over time, which is the goal of training. training. So if you have a low HRV or race day, it doesn’t matter because you are racing right? Then you will take, you know, time to recover and so on. But then during a training block, it seems favorable to not add stress on a body that is already stressed because then we can execute the training, but then we will not get better. So it’s sort of useless to do it. And

Steve:
Yeah. Yeah.

Marco:
even there, I I think it’s important to understand that the data reflects many different things, because HRV is just a marker of stress, of our stress response. And, you know, it could be just the evening before you ate something that, that, you know, didn’t go well with you, and you’ll have a bit of separation or it’s nothing to worry about. So I don’t think we need to be very reactive. Like every suppression, we need to change their their training and things like that, and also research. As I reflect that, like in the past, that was the approach. Well, now typically you look at the moving averages. So a week basically of data with respect to what is considered a your normal and your normal is typically built over 1 to 2 months. So it’s a broader range. And if your weekly average goes below your normal then a change is implemented. But of course, for our weekly results to go below your normal, it takes a couple of bad days, so you are not reacting to any change. But then if you do have a couple of bad days, then maybe it’s a good idea to make a small adjustments and weight, you know, so that things renormalize before you add additional stress. So I think that is a bit the principle behind it. And how it is used today.

Steve:
And I mean that’s the principle behind coaching I mean there’s so many you know times I’ve told people I can give you know 20 athletes the same workout. And it’s all going to, it’s going to have a different effect on each of them. And and that’s what we do as coaches every day is you know, look at the athlete in the morning and get the kind of subjective report, look at the look at the data and then say, okay, yeah, I think you can absorb this much stress today or that much stress today. I’ve talked about training stress here. But I mean, mean, the other stresses of life are also relevant, right? Like you need to be aware of. And HRV is trying to, pick up on all of those and then, you know, the the modeling you’re doing is trying to say, okay, this is how this relates to how we up or down regulate the training stimulus. And I think that that that’s, that’s that’s exactly the way a coach’s mind works. And I think that that’s really one of the strengths of this approach is that it is trying to replicate a human knowledge knowledge worker process, if you will, to try to like, pull on all the collect all the data, look at the plan, make an adjustment to the plan and, and look at this sort of over not just days but weeks and months and years. So that’s that’s sort of sort of interesting. So what’s the bottom like. What’s what do you tell people people that they say my, my data by HRV says I’m a red light, but I feel like a green light. You know who’s right. How how do you had how do you have that conversation with an athlete?

Marco:
Yeah. So, I think I’ve gained a lot more experience in these in the past three years since I’ve started also coaching endurance afterwards. And I see see that often. The question is is my data shows this. And the other part that you mentioned like, but I feel like this is not even there. So it’s, you know, it’s the data shows this. And then my first question is always how do you feel. Right. So that is I think, the most important piece of information. But on finances it’s not even even apparent right. Because, of course, if you just look at the tool, the tool doesn’t know, but then the data doesn’t know. But you need to talk to the task side. You need to get that sort of input. So typically I think the people that work with me, I’m obviously lucky that they have read about the things I wrote. So So a lot of the explaining has already been done in the blog and and it’s become easier. But I try to stress these points that we discussed the so the fact that, you know, if are low, they can happen because of many different things, and it does not impact our ability to perform this session. At the same time, we don’t want to get in a situation of chronic negative response to stress. So how do you feel the most important thing? Because if you feed poorly, then the data is just reflecting something that is off. off. Maybe you are really getting sick or something like that. So in that case we might take action right? But if you feel good to say, hey, if you feel good, we do the session and we see what happens, meaning that

Steve:
Okay.

Marco:
Typically, if it was nothing the day after, everything is normal, and then it means that, you know, there was no need to make changes. So I always give it 2 or 3 days. If the person feels good and we see if I will think that I normalize this, which happens basically every time, unless, you know, there is really something stronger happening. And of course, sometimes it can happen. But it is again rare if the person also feels good, you know, for 2 or 3 days is difficult that you developed something negative. And then yeah, we so we, we, I start from there, from that question and then we try not to be overly reactive and really use the data in certain situations in which then we have a couple of bad days and typically I would say maybe every single time is life happening more than training. Right. So I think that’s where where the data is useful, even though many people say, okay, when I use this tool to really guide my training, but what the tool does, so what? And each of you measurement reflects is just overall stress and training is typically I plan it in a way that, you know, I should not and you know, in a whole. Right. So there’s stress is applied in a way and which I think is what you can handle right now, depending on your history and everything in your life. Right. Right. So it is very unlikely that we do some sessions and we see that a reduction in HRV after the session, typically, I would think that there we did something that maybe we were not ready to handle. So again, unlikely to happen. But then, you know, people travel or their kids are getting sick or this, you know, all sort of, you know,

Steve:
Yeah.

Marco:
know, seasonal allergies like all sorts of things.

Steve:
All kinds of stress.

Marco:
things. Right, exactly. So we are all exposed to all sorts of stressors all the time. And that’s why that it is useful, I think, because it gives us context also, in terms of all these things that are happening and where we might might not really be aware sometimes as coaches, even if we talk to our athletes, you know, so much happens in everybody’s life that if we see something, something, maybe it’s just an excuse to start a conversation, right? Just like, hey, you know that it has been low two days. What do you think is up? And maybe, you know, they tell me, hey, yes, my family has been sick for a week and I can’t. Okay, so maybe we need to think about that. Yeah.

Steve:
There it is. Yeah.

Marco:
Yeah. Yeah. Excellent. It’s, you know, and it’s not always so straightforward, but in general, I think, that’s a good way to go about it. So you look at the data and you have a conversation and you see what other steps are present, and try not to be overly inactive, but then still pay attention here and there, to also make sure we don’t get, get, you know, the situation in which we are always in a negative physiological response, so to speak, which is unlikely to help us long term.

Steve:
Maybe we should have done this earlier, but can you explain to me in the audience what exactly HRV is measuring and how does it.

Marco:
yeah. For sure. So when we measure HRV, we look at the variability between heartbeats because the heart does not beat at the constant frequency. There is always some variation. And this variation is not random, but is actually due again when when measured at the right time. So in the morning during the night it is due, to the activity of the automatic autonomic nervous system. And the nervous system is basically basically modulating heart rhythm and therefore heart rate and heart rate variability in response to stress. So we face a stressor again. And stressor as we just mentioned. And then we have a physiological response like from a hormonal point of view as well. Right. So our cortisol might rise. And there’s all sorts of things that are happening that we cannot easily measure. So it’s not that it’s less relevant to look at hormones with respect to heart rate variability. It’s just that it’s not easy. While the response of the nervous nervous system and in particular the parasympathetic branch, the one that is more active in a state of rest or relaxation, impacts heart rhythm, so makes variability higher when there is higher parasympathetic activity. So a higher recovery or a state typically makes my heart beat a bit higher and the stress stress makes it lower, while heart rate is the opposite. Right. I think that that people can easily relate when they are stressed. They feel their heart is racing and you that is actually happening. Hotter is higher and and by a bit is reduced. So all of that is driven by the nervous system. And when we take this heart rate variability, measurement in practice is just an indirect measure of our stress response. I think that also the key again is really is the response. Right. It’s not the stress per set. So if we respond well

Steve:
Right. Right. Right.

Marco:
well to stress then our variability will be back to normal after many maybe an acute suppression that is normal. But again we measure normal 24 hours later in the morning or in the night. Everything is right normalized again after our training or all other stressors because we responded well, even if that was high stress. So good good viability, it doesn’t mean no stress, it means good response. And then if we cannot stress normalize right within 24 hours, typically something is off.

Steve:
And. And what is it. How does it actually physically the measurement made I mean we all think of in the old days when people would put the probes on the, on the chest, like an EKG type machine. And now it’s done in a ring or with the the phone camera or the, a wire, some sort of device, a hoop and so how is that working and how direct is that measurement?

Marco:
Yeah, that’s also a great question because in reality, how variability is the variability of heart rhythm. And that can only be measured with another cardiogram. So right now the most easy to use electrocardiogram is not any more than electrodes and things like that. But there still is a chest strap. Right. So, like a polar chest strap works great for heart rate variability analysis. So you would put that on and take your measurement in the morning. Then of course this is also sometimes not the most convenient way or at least since the development of optical technology like what you have in the rings, in the watches or in our lab with the phone camera, that means that you are looking at change at the periphery. So again, not at the heart, but you’re looking at blood volume changes, for example, at the finger. Because of course the heart beats and blood flows. So at the periphery you can look at changes. This is typically very highly correlated, which means that on a day-to-day basis for a person, the data follows basically this same trend. When you measure

Steve:
Okay. Okay.

Marco:
measure it these two different places, places, there can be small differences because of course by the time it reaches the periphery, you know, there’s other factors that impact blood flow, like blood pressure, for example. example. So, there can be variations. And there’s also for some people that could be larger variation than for other people. But in general, I think is accepted that these methods can be very accurate, especially to capture relative changes over time. Assuming, you know, again, the devices being validated validated against this. Like, it’s not that all optical sensors can do that, but even the chest straps, like not all just straps can measure heart rate variability correctly. Like I have a bunch here here because you know, for what it does, things things and so on. But when I measure, I always use the polar one because I see that with the other ones that I do sometimes is more erratic. So even if they can give you a heart rate correctly, does not mean it can give you heart rate variability incorrectly. So, it’s always important to use a device that at least as shown in some validation, published that, it’s very close to all any surgery, you know.

Steve:
Interesting. Yeah. I’ve personally and with my athletes experimented with the, with the chest strap. And that was very intuitive to me how that could. I think I was using a Garmin at the time I was trying it the, the, the actual chest strap. But, I’ve, I’ve wondered what that correlation is and I haven’t haven’t personally seen that, that data or those validations. And then, you know, I knew that, you know, your app uses a phone camera and you know, that there’s, you know, sort of based on the same optical technology that would be be in like an aura ring or and I assume that would works. The same way. And I and I was never that confident in them. Is there a significant variation in the accuracy of the different, optical methods that are measuring in the extremities, or are they all similar or the same?

Marco:
So I would say they are very similar. At the end of the day, when you are asleep or when you take a measurement that is short, like with a phone camera in the morning, because in a situation in which there is very limited movement, because in theory, let’s say the finger is a better place, right? That’s because, you know, you have closer access to the arteries while in the wrist, the arteries that actually have the bottom and the sensor at the top. And we all know from, you know, exercising, running the various heart rate is typically the worst place where where you can measure it. And now you have even the same technology, you know, in arm bands that you place, you know, just maybe near the shoulder and just day and night. Right? It feels so much better. It is the same thing. So it’s just the wrist is just the poor place effort to measure these kind of things. But when you sleep, that’s different, right? You’re not moving. There’s

Steve:
Right.

Marco:
There’s almost no artifacts or even there. I think it’s good. So in general, I would say these technologies can be used, at the same time, also with our app, like with the camera, the latest iPhones, for example, they put the flash and the camera very far. And that is a problem like to the point that myself like since the new phones, I use the strap again. Right. Because I use the camera for,

Steve:
Okay. Okay.

Marco:
for, you know, a decade always works great. But then the technology was such that the phone, let’s say, could be hacked the correct way because the camera and the flash were next to each other. And you need to use the flash tool again, illuminate the finger so that you can record the change in blood volume. But if the flash is very far then you cannot do that well. So for me it was simple matter of using the strap. strap. But then, you know, it’s just too I like that it’s never so simple or it’s never the same. Technology evolves and things like that. And with wearables also the the same, like they they decide the design, but at the same time, there’s many considerations beyond HRV in what they are doing. And then there is a new generation of of hardware, and maybe there is more more sensors and maybe they should be piece become something. You know that again, as trade offs with respect to the new things that they mounted in there that they want to do. So everything needs to be validated sort of every iteration just to make sure we still collect good data.

Steve:
Yeah. Interesting. I want to ask you about the, the orthostatic stress. And I’ll just tell you a little story like when I was training full time 20 years ago. And it’s a sort of professional athlete climber. We used to do orthostatic tests for our recovery, you know like do like box step-ups, for example, get the heart rate up to a certain amount and then sit in the always the same kind of position and measure how quickly the heart rate came down. I mean, you see, is this also like on on expeditions expeditions at base camp? It’s sort of this incredible portable, low tech way to measure recovery. And I feel like it worked pretty good. Again, gave another data point of felt, more objective than just pure feeling. And it often aligned with, with pure feeling. So can you talk to me about orthostatic stress and why body position matters when when you when you when you I mean, we’ve talked about the the time of day, but the position of the body and that it’s I guess similar between tests is is important or is relevant. Right.

Marco:
Yeah, yeah, yeah, it’s very important that we measure in the same position and even that if we can we exploit the of the static stressor like basically the change in body position. Right. So the test you were doing and then looking at heart rate is, I think, great. Now with HRV, I think the advantage is that it’s a more sensitive measure of stress. So we don’t need to do so much to see a change like we would do do with heart rate and where maybe we were were looking that big on the heart rate recovery and things like that so that they would get addressed with HRV. We can capture much of that change, but if we change body position, then of course we create basically, you know, the body has to respond to that change, right? Even just in terms of blood volume and, you know, falling in the right places and things like that, because you don’t want to faint every time you stand up, for example. Right. So those kind of changes make it so that if you measure shortly after, then

Steve:
Yeah.

Marco:
the measurement is just more sensitive to stress because the response is amplified. So if I’m a bit sick and, you know, not badly sick, just a bit sick, and then in the night I’m still sleeping, having a decent night, and maybe in my heart rate instead of, you know, 48 is 50, that change is so small that I cannot really see much into that. It’s just day-to-day variability, which is within that. But then if I’m set up in the morning, then instead of being, you know, 51, it’s 63. Like the change is really amplified by that change in

Steve:
Okay. Okay. Okay.

Marco:
in body position on the same day. day. Like and I have collected also this type of data like to show the importance of, you know, the static test and changing body position and so on. So that’s why I’m saying it’s a good thing to do. It’s simple. If you are already taking your morning measurement, just do it sitting up. And then typically that it is a bit more more useful. And that is all that is, I think in terms of the the static stressor, because HRV is more sensitive than heart rate already. So we don’t need, you know, to do maybe a measurement before changing position or measurement after that was also done in the past, or maybe a more complex test, a bit like you were doing as well. I think we can still keep it simple with the resting measurement, but after the change in body position, I think that is, a better protocol is was actually a study very recently, maybe last year, with people going at altitude and you could not see a change change even going at actitud in their night data. So night HRV was the same. But then they measured also in the morning standing there. And it was a huge change with respect to sea level. So and it’s just

Steve:
Okay. Okay.

Marco:
just easier to capture it that that way. And then I would assume, you know, if you keep measuring and you stay at altitude and you adapt, then you know that difference with sea level would narrow down, while again, in my data would always be the same. So, you know, sometimes very convenient to use wearables, wearables, but it doesn’t mean the the collecting useful data.

Steve:
Yeah. I want to come back to altitude a little bit, because I think that’s going to be super interesting for our audience, but I want to kind of drill into people that HRV reflects a response to stress, not how hard you trained and more. How did did you respond to the training? And, you know, that’s that’s something that I a concept that I am constantly explaining to athletes that is, I I think, counterintuitive when people haven’t been training much before that they think, you know, we’ve watched too many Rocky films and seen too much of this, like, macho version of of training and real training is much more subtle and much more about signal and response. And I think HRV is aligned with that. It’s a response to the stress that would you amend or edit anything in that statement?

Marco:
Yeah, yeah. You You know, I think that’s great. It reminds me, actually, of how some people think that when they train or train hard, they should see a suppression in nature the day after. Like if they don’t, they think they didn’t train hard enough. But that is absolutely incorrect. Like if you see a suppression, you just went went way beyond your capacity to simulate that stimulus. And that means typically that, you know, it’s not going to it’s not going to have to get better. And in fact, like the best athletes, you know, elite athletes that definitely train a lot, high volume and very hard, have the most stable data, like there are very, very few separations. And it’s hardly ever about training again. Maybe it’s travel travel if they are competing somewhere else. Or again, all sorts of things that happen in everybody’s life. But their response to training actually the better you are, the fitter you are, the quicker you’re bound to your normal. Right? Which is also why, as a good athlete, you can take more training, or maybe you can train twice per day, as long as you’re not training in that depleted state or in that overly stressed state.

Steve:
Yeah. Yep.

Marco:
Or before you bounce back to normal, almost does is like you just bounce back very fast. And so typically, even if you’re trying very hard and the day after your career is normal, that is a very good signal. It means, you know, you could take that training.

Steve:
They’re absorbing the training. Well, yeah, I think that that that’s absolutely right. And you know, we’ve. Yeah, 100% agree with that. I want to we you know, when we’ve talked about stress and HRV, the illness has come up a bunch of times in some of the the writing that I’ve read of yours, who’ve been very precise about the differences between detecting, not predicting illness. Can you, explain that to us a little bit?

Marco:
Yeah, I think that was part of peak hype. It should be during the pandemic or those times where, you know, I like those tracking HRT and, you know, there was always this statement that it’s a way we would predict illness. I mean, for sure, there are situations in which your body’s already sick and you haven’t haven’t developed symptoms yet, so you haven’t noticed yet. So there is a case for the data sort of showing something that you have not realized yet, even though,

Steve:
Well, who.

Marco:
though, of course, that is something that is already happening in your body right now that, you know, we are predicting the future, right? Because then sometimes it’s very what people think. So we we maybe have not developed symptoms yet, and you might already see it in the data to a certain extent, even though I think most in under most circumstances, typically the data is simply reflecting what we also feel like we feel down. You are getting sick and you also see it in the data like the two come together. That is not

Steve:
The The who?

Marco:
not very different from training. training. So I think in general, maybe for some people it helps them pay attention a bit more, or some cases in which you are a bit more uncertain. About, you know, how you feel. That is also they use in training

Steve:
Well. The.

Marco:
training again with for objective data, as you also mentioned, during your expeditions as an athlete, I could do the task to have one extra data point, because even when you are in tune with your body and you know, feel is what drives your decisions. Still, it’s not black and white every day. So sometimes you are pushing your limit and you know, you just have another data point to consider. So I think in that context it it can be useful. But you you know, the data typically can only reflect what is already happening in the bodies. It could also be that if you pay attention a little more, you realize you already have some symptoms that maybe you were ignoring.

Steve:
Yeah, 100%. I love that, distinction. And I want to go back to connect back to what we were talking about a minute ago with how as athletes get fitter, their suppressions are less and people. I’ve I’ve had athletes that expect their HRV to climb as their fitness improves, but that’s usually not what happens. And I think we need to understand this idea of parasympathetic saturation to explain why super-fit people, sometimes their HRB just sort of looks stagnant. And another, you know, variable that, that I learned about, from, from reading your work is that coefficient of variation as a, as another metric. Can you kind of put these I mean, we’re getting into some sort of technical technical terrain here, but I know there’s a good chunk of our audience loves this stuff. So let’s can you, help define these terms that that crop up and how to help us see what.

Marco:
Yeah, Yeah, yeah, for sure. So in terms of our absolute HRT, so the value of our injury, you know, not related to how it changes over time with respect to our history, but just the number, I think maybe we can start there because there also there are some misconceptions about, you know, higher values values always being better or, or, better athletes having higher risk. So I think none of that is true. true. So, higher values abnormally high for you. So again, you have a normal range like you have for your, you know, for blood glucose or blood pressure. There’s also for HRV, but unlike unlike blood glucose and blood pressure. Yeah the normal range is not population. The drive is actually under your own. And that is because the genetic component potentially is maybe predominant even in terms of this absolute value. So I would it makes sense even if I take, you know, I’m a male and I am 42 years old, and if I take only people like me and that that even train like me or, you you know, end up from this area of the world and so on, still there. Recovery would be all over the place, to the point that I cannot build a frame of reference for my own data using even people like me. So the only way to have a frame of reference is to collect my own data data for, let’s say, a month, ideally two, and then we be in this normal range. Now when your data is above things or margins. So that’s particularly high. Abnormally high. That could be also that the body is in a state in which is not very recall that so to speak, but is working hard to recall that. So maybe it’s to parasympathetic in a way. And typically that comes also with heart rate quite suppressed. And I think people that coach or train unfamiliar unfamiliar with heart rate being suppressed during a run, for example, that, you know, it’s not a sign that you suddenly got extremely fit, right. It’s still a sign that you are fatigued. So

Steve:
Yeah. Yeah. Yeah. You can get your heart rate up as as like you expected. And athletes asked us all the time. Like, why couldn’t I get my heart rate up yesterday and the answer is one, they don’t like to hear us, so they’re probably

Marco:
Yeah. Yeah,

Steve:
probably too fatigued for

Marco:
Yeah,

Steve:
for that workload.

Marco:
yeah, yeah, yeah. Exactly. So for resting physiology, you can think similarly sometimes. So if there is an acute change where heart rate is quite suppressed and HRV is quite high, then it could be that, you know, again it does not it cannot be interpreted as many variables do, which is higher is better. better. So I’ll go out and go very hard. So that is another misconception. I think it’s important to remember. It’s much better to be within your normal range that to be with particularly high value, because that that could mean again, that is just more fatigue. So that is one side of things. And given that there is a strong genetic component, again, you might be a very good athlete. And your heart rate typically resting heart rate tends to be quite low. So that is a much stronger link between your your respiratory fitness and resting heart rate than there is with HRV. So your job could still be with respect to the population, not very, very high. And you know, you would use the data data in the same way relative changes with respect to your normal how that goes. But it’s not that you need to have particularly high values. So I think that’s just important to know because people expect maybe that, you know, the timing should be higher for fitter people or that as they get fitter it gets gets higher. I think I think much of the change in the as they get fitter, if they were being as before, maybe. So there is a dramatic change in fitness, then there can be some some change necessary, but that’s typically typically also just a reflection of the fact that the resting heart rate is going to be lower. So there is more room for variability. So it is kind of accounted in large part by the change in heart rate. Now the issue issue of parasympathetic saturation saturation that you mentioned I think is something also to keep in mind, in certain situations. So what that what does that mean. So a parasympathetic situation means that basically HRV. Under Under certain circumstances does not track parasympathetic activity anymore. Very well. Because even if parasympathetic activity increases, basically the receptors in the heart are saturated, meaning, you know, they cannot take anymore. It’s like, you know, you have a loss of water. And then if the water level never reaches the top, then you know, it tracks very well. But then if you reach the top, you can keep pouring water, but it stays there like you cannot measure more water

Steve:
Cannot Cannot measure more than the size of the vessel.

Marco:
water in that glass. And so. so. So it’s the same in this case. And also there I think typically we’ve seen that if you get people to measure while sitting or standing, you sort of remove this problem, meaning that it is more unlikely to show to see saturation again if you use the orthostatic stressor to change position. So let’s give stress a bit. The body typically of course, the data, the HRV data, for example, even in absolute numbers tends to be a bit lower. And when you’re sitting or standing with respect to a lying down. And so that is a simple trick. But maybe in night data data it’s not possible to do that. And so either could be a situation in which, you know, so it does not change much. And that could be good saturation. It’s not really something that diagnoses you can not look at and see, you know, if heart rate is, you know, not changing with respect to the neurotransmitters that are modulating heart rhythm. So it’s a bit of, sort of the empirical way to look at things. Is your heart rate very low?

Steve:
Okay.

Marco:
Are your training at a very high volume? Are you measuring early in the night? Are we not seeing changes then? It might be a saturated. Now the other thing you mentioned was the coefficient of variation. This is a bit of a different way to look at the data. Instead of looking at your weekly average or your daily scores, you look at how much your data is changing over a period of time, typically a week.

Steve:
Okay.

Marco:
So are much jumping around you’ll you’ll have in a week, because if your HRV is 100 milliseconds the average of this week, obviously it could be that every day it was 100, or it could be that it was, you know, 128 and so on. Right? Right? So it jumps around more this variability in variability. Right. So how much it jumps around is also reflective of your stress response in a way that typically if you letter is is within your normal range or let’s let’s say skewed is not particularly suppressed, then it is preferable for the coefficient of variation to be low, which means the data to jump around less, because again, it is also quite intuitive, right? If it is, if you are training or there is another stressor and today is very suppressed. Right. Right. And then you recover tomorrow you, you know, take an extra nap and you know, you eat well and so on. And then you jump back up and then you are again very stressed and again it’s suppressed. So there’s a lot of jumping around typically not a great thing. And this is also in the video. So it’s not that for every person it’s the same amount of jumping around. And that is also something. Keep in mind never compare you know with your friends day to day variability. It’s about how is sensing for you with respect to your historical data.

Steve:
is stability more important than magnitude in that sense.

Marco:
So I think that

Steve:
sense. Or, or am I misunderstanding?

Marco:
that yeah, yeah, I think stability is really what we are after when we look at HRV. And for a very long time it has been pushed the idea that higher is better. And I think we are finally getting to, you know, more stable is better is not about HRV going up up is about, you know, know, being within that normal range, which means that you stress the body and then it bounces back. And when you measure again, it’s again what it should be. So the stability of it I think is the optimal response more than an increase or anything else.

Steve:
Okay. And the stability as it relates to you and based on and you kind of specify like a range of sort of, you know, six to 6 to 8 weeks or what did you say, 6 to 8 weeks or 40 weeks of data to kind of establish that.

Marco:
Yeah, yeah I do. So in our lab we use two months and in research typically they are in a rash. So they use one month. But I think you know that anything between 1 and 2 months is acceptable. You know.

Steve:
The one thing I wanted to kind of ask you is if this and I’m asking. Asking for a friend, had this happen where someone had their sleep is good, their nutrition is good, the stress is low, and the HRV is still trending down.

Marco:
You can see.

Steve:
Is that in that case, still an early overtraining signal or, you know, and assuming this is relative to that person.

Marco:
Yes.

Steve:
Is that what it most likely means? And how do we know that that’s the correlation?

Marco:
yeah, yeah. Not necessarily maybe. What I mean is that, first of all, I think when we use this data, while useful, we also need to accept that we don’t have all the answers. And sometimes there might be changes that we don’t know exactly what is happening. But one thing that we should keep in mind always, which of course, we are very well aware of given, you know, all the work at altitude and so on, is the, our environment. But our environment sometimes means even just the seasons changing. So there’s seasonality in our physiology. And I think that is something that we also need to keep in mind, because typically if we live in a place where seasons are quite different in terms of our long is the day, the temperature. And, you know, again, yeah, just I would say mostly it is daylight and temperatures.

Steve:
Interesting.

Marco:
Then those factors reflect in our resting physiology quite well. There’s social studies showing studies showing this where basically your resting heart rate tends to be lower in summer and higher in winter, and HRV is the other way around. So it’s a bit lower in winter and higher in summer. So, you know, if you see some changes that you cannot explain very well and are also quite chronic in a way. So it’s not not that they they suppress the day or two, but it kind of stays there for a week or two. It could be also these kind of changes in our environment or the seasons and you know, depending on where we live and so on. So sometimes it’s kind of is kind of like, you know, that’s how it is. It’s not really that if you cannot cannot change your environment then then that’s how it is. And what are the implications for training? I think maybe that’s an open question. Like I don’t think we know that. Like, sure, there is a change in our physiology and maybe that means that we really cannot assimilate the same amount of stress that we could assimilate, you know, over summer. Maybe that is the case. Training certainly differs typically for people living in this new environment. So, you know, I’m racing season this summer typically in the mountains, mountains, right. And then in winter there’s a lot of base training maybe in different kind of like less intensity or smaller bits of intensity. Depends of course. But still, it could be that something there is also driven by these changes and not necessarily something related to training or negative in the response of the person. Yeah. I would say, again, we don’t always have an answer, but we also need to keep in mind that it’s not only the factors that we can control, it’s also where we are placed as people and and how that impacts impacts us.

Steve:
Interesting. Yeah. Okay. Well that bridges to one of the other kind of seasonality. I wanted to ask you about a half of our athletes are female and a lot of them are flagged as stressed for for ten days a month simply because they’re in the luteal phase of their cycle. Physiologically, what happens to to HRV during this phase of a woman’s cycle? And as a coach or as an athlete, how should they think about adjusting their baseline? So we are not giving them false rest days based on that feedback.

Marco:
Yeah. Yeah. So I think that there so I’ll tell you first what at the population level can be seen in the data. But then we talk about the individual because that changes everything. That would be the advice advice of our example. So at the let’s say that that very broad broadly speaking at the population level, we see that the physiology in terms of resting heart rate and HRV tracks similarly to changes that we see also in temperature, which are of course due to hormonal changes during the cycle. So So in the second phase of the cycle, the little phase typically there is, reduced HRV and slightly higher heart rate. And that is what we can see at the population level. But then I think just like in many other things, physiology and training related, the individual variability is higher than the variability between groups, even groups of similar people. So the individual variability is so high that between two people that have have the mental cycle, we could have very different responses, interesting physiology data. But even the same person across cycles over time can can see different patterns because the synthesis might be different with different. The other structures that are present are of course different. We are not, you know, static and, you know, again, the seasons are changing. Our training is changing. Our are the stressors of changing. So everything changes at the same time. So it’s very difficult. I think, to have expectations on the data or or to see in the data what we we see at the population level. And then there was a study just I think, out this week, also looking again at HRV and other parameters in different phases of the cycle, but then looking also at performance outcomes in athletes. athletes. And so they could show that in different phases that the physiology was different. Again, as

Steve:
Okay.

Marco:
as we discussed now. But then the performance was not so again, the change in physiology doesn’t necessarily mean that the athlete will perform differently, better or worse. Like they could perform the the same in the different phases. phases. So I think that is also important to know because the person might have symptoms. And of course those needs to be accounted. But we at the same time, you can never be sure that you know, you are in a certain phase and often feels good, like performance might be as good, like it’s not necessarily worse, worse, so to speak, because in that phase we know that typically HRV is a bit lower. Some other physiological parameters are more indicative of, more stress state. And again, maybe we don’t know what

Steve:
Yeah.

Marco:
what that means in terms of assimilating the training, right, as we discussed at the beginning. So it could be there are other implications. But in the studies looking at performance, then at the moment that there are no strong changes, changes, that would I think, make a coach decide that things should be modulated that way. I think it’s better at that point to work with the individual and their feedback and how they feel they can execute the training and things like that, and go really on an individual basis more than, yeah, with what we expect from what we see at the group level.

Steve:
Yeah. And it’s one of the points that was made in one of our coaching discussions was that one of the coaches mentioned that it brought up that the HRV is flagging a negative when neither he nor the athlete expected it brought up him asking the question to his female athlete, like, where are you in your menstrual cycle? And it’s just and then found out like and, and sort of solved the problem and then brought that to the, the surface of their conversation more. And, and he was able to do a better job of his coaching just because he was more aware of where she was. And like you said, I think that the the problem has been what I want to say, like false negatives or, you know, we have training plan, but the butt is signaling. No, you shouldn’t train today because your HRV

Marco:
Yeah,

Steve:
HRV says so. And so I think it’s, if nothing else, it’s like elevating this more into the consciousness of our decision making. And making us more aware of it. So, so I think that that’s that’s great. And I think it’s really interesting, and I’m really grateful that there’s more research coming out because this is something up until quite honestly, like just a few years ago, I wasn’t really tuned into or thinking about. So it’s it’s new for me as a coach to.

Marco:
Yeah, yeah. I think in any case it’s key context. So for some people and then it’s important to use, as you just mentioned, it could explain the change in the data that you otherwise might think is due to something. Guys. So if anything is, is context is important is there. And then it can help. Yeah. The day to day.

Steve:
Absolutely. So shifting to another variable that a lot of our athletes manage and we touched on it briefly is altitude. Our group sometimes goes to you know, almost 9000m in altitude without supplemental oxygen. Most of the time they’re using supplemental oxygen but very very high climbing very, very high. And a lot of trail races these days, it’s very common to see courses go for 3000m. Now, Now, the acclimatization era and for these races and for these mountaineering objectives is, is very important. What is the expected? What is the expected hrb response to short term like acute. I think would be the clinical term, but meaning, in a short time frame, exposure to a new altitude. If someone is trying to acclimatize and they go from the valley and they go up and they try to sleep at 3000m, for example, what would be the expected HRV response to that?

Marco:
Yeah. So typically I think studies looking at this, I have shown that we have a suppression like we have an increased heart rate. Probably people feel like the increased breathing rate. Right. So there’s some things maybe they notice others like HRV is not something we can really notice. But then you can measure that there is a change and that the change seems also quite aligned with how high you go. Right? So the higher the stronger the suppression. I think what can be interesting there is that if you stay quite long, say in the order of some weeks, then you might see changes in the data that reflect that you are getting used to the environment. I did a study during, my Masters in which we had a few athletes that weren’t advantaged, and then we looked at how their HRV changed and their racing heart rate, and also this coefficient of variation. We discussed so much, it would jump around one day to the other. And then we put this in relation to what we could consider a marker of their adaptation, which was for example, what’s your heart rate at a given pace. Right. So at sea level you have a certain the heart rates are given pace required altitude, heart rate at the same pace much higher. But then you know, after a couple of weeks it’s sort of renormalize as well. Maybe never like sea level depending on how you are. But you know, it gets better. better. So we could see that the people that had a greater disruption in the first week in terms of their resting physiology, so their HRV would jump around more, their resting heart rate was higher then

Steve:
Gets better. Yeah.

Marco:
where the people that struggle more to adapt or respond according to this criteria of their heart rate, right. Normalizing at time. So it remained basically elevated in a way that they never really adjusted to the altitude. So this is is to say that maybe also what happens in the first week could be telling something about how you will respond in the longer term. So if you have a great disruption, it’s going to take you longer. Or maybe it’s just too high for you, while if you have a smaller disruption, maybe you’re just handling it better. And then also your exercise data were normalized a bit quicker.

Steve:
Yeah. It’s interesting. You know, one of the few observations from having spent a lot of time at high altitude is that there are people who respond to accommodation well and acclimatize quickly, and others that just take longer. And even knowing myself and some of my client partners, I came to know very well, I I would know that some of them acclimated much faster, but I would catch up and we’d be equal after, say, four weeks or something. And also that the body kind of learns generally to get better people who frequently go to altitude, altitude, especially

Marco:
Yeah.

Steve:
especially 1 or 2 or three times a year, their body learns how to do that. If you’re a mountain guide and living in Mumbai, born and raised in the Chamonix Valley, and you’ve been climbing Mont Blanc every summer all your life, like your body learns how to acclimatize to 4000, almost 800m, 800m and it’s and it’s. And then that becomes very normal and very easy for it. But if you take that same person and take them the 8000m that that they may have a different response, like that’s a, that’s another like it’s the altitude. Our colonization and the individuality of it is very interesting. But I think that this is also what you’re saying, like this as a, as a signal is very interesting. And I can see how that could be, really useful to track that for people. you did your studies and did your research or other research on HRV dial in, like, was there was a predictability in terms of the, the time to adaptation, with HRV and correlated to how subjective acclimatization was, or was it just too individualized to come up with an average.

Marco:
Yeah. So the study I did was just very small samples. So we could only see a difference between two groups of people and the ones that we call that could respond well. And the others they couldn’t. I’m not aware of studies using a similar approach, in which you look at the data in the first days to try to come up with what we will happen in the future. Also because typically studies are a bit short also on this, this, maybe evidence from the field would be would be more useful. You know.

Steve:
How do you. Manage, accommodate the fact that sleep can be very fragmented at altitude. That’s one of the things that moving to high altitude does. Does that are you just focusing more on that waking sit upright and do the measurement then and not, relying less on the, during sleep measurement?

Marco:
Yeah, yeah. I would think that’s another reason to measure in the morning because then then sleep is just another stressor. stressor. You know, positive or or not, it will impact impact your state. Well if you measure during then and maybe are also awake a lot, then first of all, the movement for wearables would create artifacts, but then also the data would be somewhat less representative of what we are trying to capture. So your, you know, recovery state in a non situation context because then it’s quite different from the typical sleep. So those cases again I think it’s just a bit better to measure after sleep or even if disrupted or anything like that. Yeah.

Steve:
shift of of topic. I want to think about the future of coaching. And internally we’re developing our own intelligence engine for athletes and coaches. We call it we call her Maria. And her purpose is to help organize and analyze and and prioritize, training data. Because there’s we’re just getting very by training data these days. It’s, you know, it’s not meant to make decisions on its own. It’s meant to surface patterns and help us know when to ask questions and what how to ask better questions. If you’re shaping the logic behind something like this, like, how would you want HRV as a data point to be weighted relative to other data that we can collect with wearables, and also relative to like the subjective feedback, like you said, at one point, you just ask your coach, you’re actually how how do you feel? You know, that’s one of the most important questions to coach you, right? How would you weight these different things? And where would it which, where would HRV be in a sort of priority list? Would it be number one, number three, number ten, top third? I don’t know how to exactly quantify this, but how would that be for you?

Marco:
Yeah. So I think that in terms of the signals that we have to capture our stress response, stress being training or anything else, we have heavy resting heart rate. And then in the context of training, we can also look at heart rate during training. So that’s what we have more than what would be best. Right. As as we were saying earlier, like at the hormonal level, so much happens and we have no clue. So it’s just cannot look at it. So, in the context of objective data points, we can look at, I think it’s a useful one. So it’s one I would look at is one I look at without the psychology. But again, all all the ways to me, I mean, the subjective feel is always the first. Right. So there is and also to use use the data typically is also to aid that self-awareness process of getting a bit more in tune with ourselves, also with heart rate during training. Right. So it’s not that we need to follow this blindly. It’s more about if we set set a cap for what’s an issue around for you. The idea is that we also start thinking about that, like how does your breathing feel, how everything feels subjectively, as we set certain limits, maybe because we want to learn those things so that to a certain point, any good athlete can train all the time without any heart rate. But maybe to get there, looking at the signal sometimes was helpful because, you know, you develop that self-awareness through the data. And I think also resting heart rate and resting HRV can serve that purpose at times. So I think it’s very important to have it always in the context of let’s get better at using feel and subjectively understand how we feel and all of that to making these decisions, because eventually I think that should drive the vast, very vast majority of the decisions. And then it should be something we look at just to have that extra objective data point that still can pinpoint certain situations, but also sometimes can just give us confidence, both as an athlete and as a coach. I think think we are feeling good. The training is going good. But then, you know, also the data reflects that. Everything is, you know, again within your normal range. So it’s still a good signal to have is not there only to flag negatives. It’s also there to show that the process is going, you know, well according to plans and there is a suppression suppression here and there because life happens. But overall, you know, we are not doing anything that is causing. And I get a negative physiological response and I think like that. So from those points of view. So if

Steve:
Yeah.

Marco:
if I have a tool, you know, that would integrate data from the, the athletes and the coach and so on, for me it would be one of the data points to look at together with the subjective of the athlete, because then that is always key for the decision making.

Steve:
One of the things that I think people have focused, I know I have inadvertently focused on it in our conversation was like the the signal about today’s workout. Should I train today. The should I train today question or should I modify my workout? But when I have that discussion with with an athlete, of course I’m thinking about that day. But I’m also really thinking about it in the context of the sort of the training density of that week, or even the three weeks of the build cycle we’re in, or is it next week, the recovery week? And we just have, like, you know, two more hard workouts. And I was going to do the hard workout today. Maybe I’m going to shift it tomorrow because I want him or her to feel like those kinds of things, this kind of idea of chronic load accumulation, how is that something something that we can utilize heavy in and understanding where people are at? Like especially like a, you know, the classic is the three week build one week recovery, right? Like as you build the the volume in a training block for sort of three weeks and you’re accumulating fatigue, you know, and that’s where you’re trying to get the body to adapt to. Is there something that’s connected to that concept that it shows up or is measurable to HRV or any this,

Marco:
I think not necessarily. So I think through my experience over many, many years, I think often is a bit more of a lagging indicator. So

Steve:
Okay.

Marco:
That would mean that, see that things suppressed imagery, and you know, we are going down and so on. Typically, we already prefer that it happens, not that we see it a bit before, and we manipulate training. So, that’s why I think HRV can only be used as a support system to a well-thought-out training plan.

Steve:
Okay.

Marco:
And it can never be

Steve:
Yeah.

Marco:
be a training based on HRV, meaning without a plan, because people also think that’s that’s the case, like especially if if they get a wearable or something like that. They would go hard basically every day or any time that the wearable say so. And then when things are not going well anymore, then it’s time to rest. But that of course, is not how you train. But you know, it needs to be said because that’s how some people approach the tool. So the tool can only be used to make adjustments to a good training plan, I think, and in that context useful. So sometimes, you know, just to manipulate what is your capacity to stimulate us on that given day. Maybe it’s not great. And then we push something another day, but it’s not about small adjustments more than the overall structure or long-term changes. So even if training goes very well in certain situations, we might see that you’re always within your normal range. And maybe there’s a trend in the data that goes higher. But then it’s difficult to like. You still need to load at certain point I you I think think the data will not tell tell you that. So you need to do it before you see it in the data. So from that view, I think as as a coach, still, you need to start from your tools and your thinking of the athlete and their planning and so on. And then use HRT as a feedback, day to day feedback or short term feedback. But it’s not always, yeah. So tightly coupled to what is happening at the higher level, or it just lags a bit in terms of showing certain types of changes.

Steve:
Yeah, that’s that’s and that aligns with my experience. Precisely. So it’s really good. I and I was I mean, because I’m not an expert in this, I was wondering if I was missing something, to be honest. So it’s good to get that confirmation from, from you. you. So one final question. If you could design one physiological metric to measure that doesn’t currently exists, or maybe it’s in its infancy somewhere, a true, true center for human performance. What would it measure? What would it be? What would be your dream measurement that you would like to create to have as a coach?

Marco:
Great question. I don’t know if maybe I never even thought of something that we cannot measure, but I would like to see more of the things that happen in the board that we know that are happening, like we were discussing earlier at a hormonal level. Like, I’d be so curious to see what is happening, happening, you know, like, even even just, outside of stress hormones and cortisol and so on. But even related to training and how those things change in relation, I would say, because a lot is done acutely, like, okay, you do a work for this type of workout, this type of intensity. This is what happens. This has been done in the lab. But again, what happens long term, what happens over a training cycle where we stress these specific capacity? Or what is our capacity to assimilate stress at a given point and is there anything in the body actually that can reflect that? Because maybe we have the same, same, let’s say, visualization makeup in different situations. And once we respond very well and improve and the other time we don’t. And why is that? So it’s as I with the art of coaching. But at the same time it makes me curious, like, is there anything there we can look at that could predict predict how we will respond? Like, because even with HRV, there is some research, very little that shows that, for example, when not what it should be is chronically a bit higher, we might actually be able to assimilate more training. So even though I serve you guys, the training is always about holding back when they should be suppressed. So it’s not about, you know, not doing something, reducing intensity and so on. There is is also some research that shows that when it’s higher actually, you might be able to assimilate more. And of course it’s difficult especially we talk about running is high impact sports. You cannot just other workout you risk to break the person. It’s not just about the nervous system. Like there’s so much more that you need to be careful with. But maybe in a sport where there’s less

Steve:
Right. Yeah. Yeah.

Marco:
less impact or maybe in certain situations you could do something with that information. And I think we know too little about that. So that’s something I’d be intrigued, to know more with, as we know.

Steve:
Yeah, I think the hormonal aspect would be my answer. I was thinking about what my answer would be, and not that you’d be interested, but I came up with the genetic-like response. Like what on our at the genome

Marco:
Yeah.

Steve:
genome level. What is, what is triggered. What is the signal? Yeah. What is the genomic response to prolonged training? And how does that change? Because for sure, all of us who have done this for our whole lives or for a long period feel our bodies physically change, right? Like something is happening at a very, very, very basic level. The cause, the changes, at and even at the,

Marco:
Yeah.

Steve:
At. The what, the morphology level like, I don’t know, when I was climbing full time, I was so lean. I mean, I’m not now. I’m 55 and I don’t climb full time, but I’m not. You know, my body still sort of holds on to that, even though it doesn’t have this demand on placed on it anymore. And I think, yeah, that’s, that’s I think that’s that’s entirely part of the process of having been climbing and training for seriously for 25 years. And I, I don’t know that I’m in an I’m an and of one. Right. But I think that it would be super interesting to to know so well,

Marco:
Yeah, yeah. What’s.

Steve:
develop the app to measure hormones with the phone and the genome.

Marco:
Yeah, yeah. I don’t know, some things. Maybe it’s better not to know if you know too much about genetics before working with a person who might lose hope to sort. Sometimes it is.

Steve:
Yeah. Look, well, on that note, thank you so much for all your advice and expertise on this interesting topic. Is, kind of a special place where it’s this intersection of, human physiology and science that, you know, and technology. And I think that as technology has has just feels like it’s going faster and faster and faster every day. It’s a fascinating space to, spend some time and think about and learn from an expert like yourself. So thank you so much.

Marco:
Thank you for having me.

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