Sep 7, 2026 · 1 hr 24 min · 17 segments
Marco Altini is a scientist, developer and athletic coach who’s work centres on the intersection of health, technology, and human performance. In 2012 he founded HRV4 Training, a mobile platform that…
Marco AltiniGuestDonnieHostOkay, let's talk about HRV.
What is it? Is the first question.

So HRV, technically speaking, refers to basically the fact that heart rate is not constant so our heart is not beating at a constant rhythm there is always some variation between consecutive beats so if we look at our heart rate over let's say a minute and even in you know the simple case in which our heart rate is 60 beats per minute we do not have a beat exactly every second there is some variability between beats And this variability can be quantified into a number which we call heart rate variability.

And that's interesting because this variability is not random, but it's actually associated to how our body is responding to stress through the autonomic nervous system.

So in a way, when we look at HRV, it's basically an indirect proxy to our nervous system response to stress and this is the case only if we look at it under certain circumstances but that's the principle why we look at it
right and i was trying to explain to to my friend today exactly what what it is you're measuring Shout out to Arnaud.
I hope you're listening and I hope it all makes sense after this.
So just to clarify for the listeners, you're measuring the length of time between each heartbeat.

So maybe, you know, from one heartbeat to the next one, it could be 1.1 seconds.

and then the following one comes after 950 milliseconds and so on so we capture all these time intervals and then we compute the variability in these time intervals that's just you know math to compute variability in a series of numbers there's nothing to do with physiology it's just statistics but we do that and this way we can summarize this variability in a way that is representative of what is happening in response to stress.
Right.
So most people are familiar with the concept of the resting heart rate and their heart beat and their beats per minute.
And what you're talking about here is something different.
It's the time between the length of time between the the heartbeats and when you are looking at that number what are you looking for what is considered good and what is considered poor

yeah that's a great question because once you measure your hrv i would say you just cannot label it that way so there is a good value a bad value a good range of numbers that is one of the challenges i think with this type of data and with the information we can find around where maybe things are oversimplified a bit the easiest way i think for people to understand how this works is to think about other physiological signals that we might be used to interpret.

For example, I think pretty much everyone has measured, you know, their blood pressures, you know, at a certain point in their life.

And when we look at blood pressure, typically, we know that there is an optimal range.

And so it shouldn't be too high, shouldn't be too low, there is a range in which we should be at rest.

Now, heart rate variability has a similar concept, but with the main difference is that this range is not population derived, like with blood pressure.

So with blood pressure, we know that At the population level, there are what we call healthy ranges, and then as we move away from those, maybe we get people with hypertension or pre-hypertension.

Similarly with blood glucose, we have an optimal range, and then if we get outside, maybe we get into a pre-diabetic range or we get into a diabetic range.

With HRV, this optimal range, we can only build it for ourselves because there is a strong genetic component.
Okay, let's talk about HRV.
What is it? Is the first question.

So HRV, technically speaking, refers to basically the fact that heart rate is not constant so our heart is not beating at a constant rhythm there is always some variation between consecutive beats so if we look at our heart rate over let's say a minute and even in you know the simple case in which our heart rate is 60 beats per minute we do not have a beat exactly every second there is some variability between beats And this variability can be quantified into a number which we call heart rate variability.

And that's interesting because this variability is not random, but it's actually associated to how our body is responding to stress through the autonomic nervous system.

So in a way, when we look at HRV, it's basically an indirect proxy to our nervous system response to stress and this is the case only if we look at it under certain circumstances but that's the principle why we look at it
right and i was trying to explain to to my friend today exactly what what it is you're measuring Shout out to Arnaud.
I hope you're listening and I hope it all makes sense after this.
So just to clarify for the listeners, you're measuring the length of time between each heartbeat.

So maybe, you know, from one heartbeat to the next one, it could be 1.1 seconds.

and then the following one comes after 950 milliseconds and so on so we capture all these time intervals and then we compute the variability in these time intervals that's just you know math to compute variability in a series of numbers there's nothing to do with physiology it's just statistics but we do that and this way we can summarize this variability in a way that is representative of what is happening in response to stress.
Right.
So most people are familiar with the concept of the resting heart rate and their heart beat and their beats per minute.
And what you're talking about here is something different.
It's the time between the length of time between the the heartbeats and when you are looking at that number what are you looking for what is considered good and what is considered poor

yeah that's a great question because once you measure your hrv i would say you just cannot label it that way so there is a good value a bad value a good range of numbers that is one of the challenges i think with this type of data and with the information we can find around where maybe things are oversimplified a bit the easiest way i think for people to understand how this works is to think about other physiological signals that we might be used to interpret.

For example, I think pretty much everyone has measured, you know, their blood pressures, you know, at a certain point in their life.

And when we look at blood pressure, typically, we know that there is an optimal range.

And so it shouldn't be too high, shouldn't be too low, there is a range in which we should be at rest.

Now, heart rate variability has a similar concept, but with the main difference is that this range is not population derived, like with blood pressure.

So with blood pressure, we know that At the population level, there are what we call healthy ranges, and then as we move away from those, maybe we get people with hypertension or pre-hypertension.

Similarly with blood glucose, we have an optimal range, and then if we get outside, maybe we get into a pre-diabetic range or we get into a diabetic range.

With HRV, this optimal range, we can only build it for ourselves because there is a strong genetic component.
The rest of this transcript — segmented and speaker-labeled, so you land on the exact moment something was said
Search every transcript — by keyword, by phrase, or by meaning, across every show Radar indexes
Trends — what is surging across podcasts, measured against its own baseline
Alerts — when a name you follow appears in a newly indexed episode
No account is needed to search Radar.