You know everything about HRV, right?
Well, Marco Altini is one of those people who really DOES know everything about HRV. Your wearable might be using it properly to track stress and wellness but athletes are almost certainly using it incorrectly...or, at least, sub-optimally. A few easy changes will sort you out.
Resources & Links:
Source Written Article by the5krunner: “https://the5krunner.com/2025/05/20/hrv-everything-you-need-to-know-garmin-whoop-oura-hrv-hrv4training-training-readiness/”
Main Channel: https://the5krunner.com
My other channels: https://linktr.ee/the5krunner
—Credits:Content in this episode was generated using AI tools (NotebookLM) based on original content from @the5krunner, @MarcoAltini and other sources as cited.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
It really is amazing how much info we get from these little
things on our wrists now isn't? It totally.
I mean, everywhere you look people are sharing sleep scores,
readiness scores. Exactly.
And you know, for people really trying to dial in their
performance, like the folks overat the 5K runner.com, this thing
called HRV heart rate variability has become, well,
(00:20):
kind of huge. It really has.
It used to be pretty niche, you know, just elite athletes.
But now, well, anyone can track it, and that's what we're really
going to dig into today. We'll get into what HRV actually
is, how wearables like say Garmin, Polar and WOOP measure
it, and maybe touch on how they differ a bit from the Wellness
ones like Aura or Ultra Human. Right.
(00:42):
And to help us make sense of allthis, we're leaning pretty
heavily on the work of Marco Altini.
He's the brain behind HRV fourtraining.com.
Yeah, a real leader in this space.
For sure, and his insights were recently featured on the 5K
runner.com, which by the way, isa great site if you're into
running, triathlon, that kind ofthing, run by someone really
focused on performance. Definitely worth checking out.
(01:02):
So our mission for you today really is to kind of demystify
HRV, yeah. Cut through the noise.
Exactly explain what it is, how your device might be tracking
it, and probably most importantly, how you can
actually use that data. You know, get real insights and
distress recovery. And maybe train smarter, feel
better, whether you're casing A5KPB like the 5K runner, or just,
(01:24):
you know, optimising your general well-being, that's the
goal. OK, let's start unpacking it
then. Heart rate variability.
HIV sounds complex. It sounds technical, yeah, but
the basic idea is pretty simple.It's just the natural variation
in time between your heartbeats.So not just how fast it's
beating, but the rhythm. Precisely.
The consistency, or rather the inconsistency of the rhythm and
(01:45):
why that little fluctuation matters is, well, it gives us a
window into your autonomic nervous system.
The automatic stuff like breathing digestion, right?
That system has two main branches, the sympathetic think
fight or flight, and the parasympathetic rest and digest.
When you're stressed, could be ahard workout, a tough day at
work, even bad sleep, your sympathetic system tends to ramp
(02:09):
up. That usually makes your
heartbeat faster and more regularly, so less variability,
lower HRV. Got it.
So lower HIV might mean more stress on the system.
Generally, yeah, it suggests your body's in that fight or
flight mode. Conversely, when your
parasympathetic system is dominant your rest and digest
system, it slows your heart rateand increases that variability.
(02:31):
So higher variability, higher HIV is usually better, more
recovered. Usually indicates better
recovery. Yeah, more adaptability.
Your system isn't stuck in OverDrive.
It's more relaxed and resilient.OK.
That makes sense. It's about the flexibility of
the rhythm. Exactly, and tracking this over
time gives you a really valuablepicture of your sort of chronic
physiological stress level, Not just the one off bad day, but
(02:53):
the accumulated effect of everything.
Which can help you make adjustments right, manage
training lifestyle. Precisely spot trends, see how
you're responding to different stressors, and potentially
improve health or, you know, athletic performance.
So when's the best time to measure this?
My watch seems to track it all day.
Yeah, a lot too. But for getting that stable
baseline reading reflecting yourunderlying physiological state,
(03:16):
you really want measurements taken either first thing in the
morning, like right when you wake up.
Before coffee and chaos. Exactly.
Or the other good option is throughout the night while
you're asleep. Daytime measurements, they tend
to bounce around a lot because of, well, everything happening
during the day, Transient stressors, meals, movement.
It makes it harder to see the underlying recovery picture.
(03:37):
OK, morning or night. Got it.
Now the tech how do they actually do this?
ECG versus PPG? Right.
So ECG electrocardiography, that's kind of the gold
standard. It measures the heart's
electrical signals directly. Think chest straps like the
Polar H10 or H9 that serious athletes often use.
Very accurate. Then you have PPG
photopluphysmography. That's the optical one.
(04:00):
Uses little LED lights flashing against your skin.
The green lights on the back of my watch.
Usually green, Yeah. It measures changes of blood
volume under the skin to estimate heart rate and then
calculates HRV from that heart rate data.
This is what most wrist wearables use.
Garmin, whoop or a ultra human? Now there's this perception,
right, that the optical PPG stuff isn't as good as the ECG
(04:21):
chest strap. That's a super common thought,
yeah. But Marco Altini's work and
other independent studies to actually show something
interesting for measuring HRV atrest, which is key here because
that's when morning or night readings haen G can be
suprisingly accurate specifically for the main HRV
metric most wearables use, called RMSSD.
(04:42):
Really as good as a chest strap.Sometimes, yeah, or at least
perfectly adequate for tracking trends.
Some studies even found more variation comparing one ECG
device to another ECG device than comparing an ECG to a good
PPG sensor at rest. I mean think about apps like HRV
for training using just your phone camera, PPG again and
getting results comparable to ECG.
(05:02):
Wow, OK, that changes things so the light can be pretty reliable
when I'm still. For resting HRV, yes it can be.
But, and this is important, PPG has limitations.
It's much more sensitive to movement artefacts.
Like if I toss and turn at night.
Exactly. That movement can mess up the
signal, create errors in the data.
(05:22):
Also, not all wearables are great at telling you if the
signal quality was good or how they handle things like heart
rhythm irregularities which can also throw off HRV.
So the potential is there, but the implementation matters.
Right. How well the specific device
does it? And you mentioned timing before.
It sounds like when they collectthe data overnight is also a big
(05:43):
deal. Huge deal.
Marco really stresses this. You know, the traditional way
was that consistent morning measurement when wearable
started doing it automatically overnight.
Some early versions only took short samples, maybe a few
minutes here and there, or trying to grab a reading during
deep sleep or. Something just little snapshots.
Yeah. And because your nervous system
activity naturally shifts throughout the night, those
short snapshots could give you really different HRV numbers
(06:06):
depending on when they happen tobe taken.
Made the day to kind of noisy, less reliable day-to-day.
OK, so a quick glimpse isn't really enough for a solid
overnight picture. Not ideal, no, but the good news
is most of the current generation devices definitely
Aura, Woop and Garmin. Since around 2022, they've moved
to using data from the entire night that.
(06:28):
Makes more sense, averages it out.
Pretty much. It gives a much more stable and
representative picture of your overall overnight HRV status.
OK, now Marco did this cool experiment wearing like
everything at once ECG or a Garmin woop.
What did he find comparing them?Yeah, it was pretty insightful.
3 months wearing them all. First thing thing he noticed
with the absolute HRV numbers, the actual values reported was
(06:51):
that all the wearables tended toreport slightly higher HRV than
the reference ECG. Higher interesting.
Any differences between them? Rs seemed generally a bit closer
to the ECG in absolute terms. Whoops.
Data looked noisier, more spreadout.
But, and he really emphasises this, focusing on those exact
absolute numbers, probably not that useful for you day-to-day.
(07:12):
OK, so don't obsess over the specific number.
What about resting heart rate? They tracked that to.
He found some quirks there. Yeah, especially with Garmin.
At least the Forerunner 955 he tested.
Instead of an average overnight heart rate, it was reporting the
lowest 30 minute average heart rate from the past 24 hours.
Rate the whole day, not just thenight.
Yeah, which could be misleading.Like when he got sick during the
(07:34):
experiment, his overnight heart rate obviously went up, but the
Garmin reported a much lower number because it was pulling
that lowest 30 minute window from the day before he got sick.
Oh wow OK that could definitely confuse things if you weren't
aware for sure. Something to keep in mind about
how different platforms calculate things.
But despite those quirks, when he looked at the overall HRV
trends, the ups and downs over time, how did they stack up
(07:58):
against the ECG? That's where it gets more
positive. The correlations between the
wearable HRV data and the ECG data were actually pretty high,
like .91 to .96. So pretty strong agreement on
the general pattern. Yeah, it suggests they were all
generally tracking the same physiological changes, the rises
and falls in his HRV. Whoop again seemed a bit
(08:19):
noisier, especially when his HRVwas higher.
But overall they captured the trends.
OK. And this really leads to the
main point. What matters isn't the absolute
number, but the relative change over time for you.
How is your HRV today compared to your normal?
That's what reflects how your body's responding to stress.
Right, so it's all about context.
(08:40):
My personal baseline is the key.Exactly.
Which brings us to the idea of your personal normal range.
This is super critical for making any sense of the daily
numbers. Because a drop might be
meaningful, or it might just be noise.
Precisely. Is that dip just normal
day-to-day fluctuation, or is ita sign of increased stress,
illness, whatever? Without knowing your typical
(09:01):
range, you're kind of flying blind.
And you're saying a lot of the standard acts that come with
these wearables, they don't really give you that
personalised range? That's often the big limitation.
Yeah, they might just give you anumber, maybe compared to
yesterday, or show a generic good or bad, but without
constantly comparing it to your established normal range, it's
really hard to interpret properly.
This is where something like HRV4 training really differs.
(09:25):
It's whole approach is built around defining and updating
that personal normal range for you.
So in Marcos test even with the different absolute values when
he plugged the data from the Garmin aura and whoop into HRV 4
training. Which then analysed it against
his normal range. Did they all show the same
significant changes like when hegot sick?
(09:45):
Yes, exactly. All the devices, when
interpreted within that personalised context using HRV
24 training, clearly show the expected drops in HRV when he
was sick, when dealing with heatstress and the typical responses
to his training load. OK.
So that really underlines it. The raw data capture is pretty
decent across the board for trends.
Generally yes, for resting trends.
(10:06):
But the interpretation layer is where things can fall short
without that personalization. That's a great way to put it.
Marco highlighted a few common issues with typical wearable
interpretations. One is that overly simplistic.
Higher is always better idea. Right, we can assume higher HRV
exile. Good.
And often it is, but Physiology is complex.
(10:26):
Sometimes a very high reading, especially after a period of low
readings, might actually mean your body is working really hard
in recovery mode. Strong parasympathetic push.
Not necessarily that you're primed for a killer workout.
You need context. Makes sense, it's not always
linear. Definitely not.
Then there's the lack of the personalised normal range, which
we just covered makes interpretation difficult.
(10:47):
And another big one is how some platforms calculate these
overall readiness or recovery scores.
They often mix your physiological data like HRV and
heart rate with your behaviour data like how much you slept or
how hard you trained. Why is that a problem?
Because it confounds things. It mixes the input your training
sleep behaviour with the output how your body is actually
(11:10):
responding physiologically. So if you do a hard workout and
your readiness score drops, is because your body is genuinely
stressed and not recovered? Or is it just because the
algorithm knows you did a hard workout and automatically lowers
the score? It makes it hard to isolate the
true physiological response. I see you want to measure the
body's response separately from the reason for the response.
(11:31):
Ideally, yes. You want to see how your
Physiology the output changes inresponse to stressors, the input
without the input directly influencing the output score.
And HRV 4 training takes a different approach here too.
Yes, it focuses interpretation entirely around your
personalised normal range, so itflags values that are unusually
low or high relative to your normal as potentially
(11:54):
noteworthy. Giving context to both ends of
the spectrum. Exactly, and while it does
incorporate subjective feelings,how rested you feel, your mood,
muscle soreness into its advice,it deliberately keeps your
training data separate from the core physiological assessment.
This gives you a clearer pictureof your body's state.
So theoretically someone with say a Garmin or an Aura could
(12:16):
manually enter their nightly HRVand heart rate into the HRV 4
training app and get that more personalised, context aware
interpretation. Precisely.
It's a way to leverage the data your wearable collects, but
apply a different, arguably morenuanced analytical framework to
it. OK.
That's a really useful option. Now back to morning versus night
(12:36):
measurements. Any final verdict on which is
better? Marco's data suggests they both
track the big picture pretty well.
Long term trends, major stressors like getting sick,
They usually move in the same direction.
But there can be differences day-to-day.
There can be subtle differences,yeah.
Like if you have a really hard workout late in the evening or a
big meal close to bedtime, that could suppress your HRV during
(12:58):
the first part of the night. So your overall nightly average
might end up being lower than your morning reading taken after
several hours of recovery. So the timing of stressors
within the day can impact the nightly average more.
It can, but again, both methods are generally valid for tracking
trends. The best choice often comes down
to personal preference, consistency, what fits your
(13:20):
routine. Some find the quick morning
measurement easier to control and make routine.
Others prefer the passive, automated nature of overnight
tracking. And like you said, you don't
even need a fancy wearable to start the phone.
Camera apps are an option. Exactly.
Something like HRV 4 training lets you use your phone camera
for morning readings, which has been validated against ECG.
(13:40):
So the barrier to entry is actually pretty low if you just
want to explore your HRV. We've mentioned a few brands and
can we sort of categorise them like the sports focused ones
versus the more general Wellnessones, especially regarding HRV?
Yeah, it's a useful distinction,although the lines blur.
You've got wearables like Garmin, Polar, whoops which are
often heavily marketed towards athletes and you had to create
(14:01):
HRV into training load, recoveryscores, workout suggestions,
very performance oriented features.
Right. The context is often athletic
performance. Exactly.
Then you have devices like Aura and Ultra Human, the rings.
They also track overnight HRV very well, often alongside
really detailed sleep tracking. But their overall focus might be
(14:23):
broader General well-being, sleep optimization, stress
management, not just athletic performance.
But in terms of how they collectthat overnight HRV data,
especially the newer versions? The underlying tech in the use
of full night data has become quite similar across many of
them by late 2022, according to Marcos analysis.
So the data collection might be comparable, but the
(14:43):
interpretation and the features built around it often reflect
that sports versus Wellness emphasis.
Got it. Now thinking specifically about
athletes again, like the runnerstuning in may be inspired by the
5K runner. Is there a particular takeaway
for them from all this? Yes, and this is a really
important point that the 5K runner himself added to the
discussion Marco published. Resting Physiology, like
(15:04):
overnight HRV is valuable context.
Absolutely, but it doesn't directly tell you how ready you
are for exercise Physiology demands right now.
Meaning meaning for a more direct assessment of your
readiness to train, especially for higher intensity work, a
short active measurement upon waking might be better.
Like the morning reading we discussed?
Yes, specifically a one or two-minute test, often done
(15:27):
seated or even standing, ideallyusing a reliable chest strap
like a Polar H9H10 and software like HRV 4 training that
analyses that specific type of test.
This snapshot can be more sensitive to your immediate
readiness for exertion than a passive overnight average.
So the overnight average is goodfor overall trends, but the
morning spot check might be better for daily training
(15:48):
decisions. That's the argument, yeah.
Relying only on passive overnight readings for fine
tuning daily training intensity might have limitations.
The OLAR orthostatic test is kind of an exception as it's a
structured morning test built into their system, but the
general recommendation for athletes wanting the most
training relevant HRV data consider that deliberate seated
(16:10):
or standing morning measurement with a chest strap.
OK, that's a key distinction forathletes.
So wrapping this up, the main message seems to be that most
modern wearables can capture good quality resting HRV data,
especially overnight trends. Yes.
The data capture itself for tracking relative changes seems
pretty solid across the board based on Marco's work.
But, and it's a big but, the waythe native apps interpret that
(16:34):
data often falls short. That's the crux of it.
The simplistic higher is better,the missing personalised normal
range, mixing behaviour with Physiology and scores.
These limit how useful the interpretation is.
So the real power comes not justfrom having the number, but from
understanding it within your personal context, looking at
those relative changes against your baseline.
(16:54):
Absolutely. That's where the actionable
insights really come from, understanding how your body
responds to the stresses you encounter.
And exploring tools like HIV 4 training, even using manual
input from your current device, could be a way to get that
deeper, more personalised analysis.
It's definitely an option worth considering if you want to move
beyond the basic interpretations.
(17:15):
So for you listening, maybe takea critical look at how your
wearable presents your HRV. Is it giving you the context you
need? Checking out resources like HRV
fourtraining.com or the 5K runner.com could offer some new
perspectives. Yeah.
And maybe the final thought to leave you with is this.
How could really understanding your unique HRV patterns empower
(17:35):
you? Could it help you train smarter,
recover better, maybe hit those goals you're chasing, whether
it's a faster 5K or just feelingmore resilient day-to-day?
Something to Mull over.
It really is amazing how much info we get from these little
things on our wrists now isn't? It totally.
I mean, everywhere you look people are sharing sleep scores,
readiness scores. Exactly.
And you know, for people really trying to dial in their
performance, like the folks overat the 5K runner.com, this thing
called HRV heart rate variability has become, well,
(00:20):
kind of huge. It really has.
It used to be pretty niche, you know, just elite athletes.
But now, well, anyone can track it, and that's what we're really
going to dig into today. We'll get into what HRV actually
is, how wearables like say Garmin, Polar and WOOP measure
it, and maybe touch on how they differ a bit from the Wellness
ones like Aura or Ultra Human. Right.
(00:42):
And to help us make sense of allthis, we're leaning pretty
heavily on the work of Marco Altini.
He's the brain behind HRV fourtraining.com.
Yeah, a real leader in this space.
For sure, and his insights were recently featured on the 5K
runner.com, which by the way, isa great site if you're into
running, triathlon, that kind ofthing, run by someone really
focused on performance. Definitely worth checking out.
(01:02):
So our mission for you today really is to kind of demystify
HRV, yeah. Cut through the noise.
Exactly explain what it is, how your device might be tracking
it, and probably most importantly, how you can
actually use that data. You know, get real insights and
distress recovery. And maybe train smarter, feel
better, whether you're casing A5KPB like the 5K runner, or just,
(01:24):
you know, optimising your general well-being, that's the
goal. OK, let's start unpacking it
then. Heart rate variability.
HIV sounds complex. It sounds technical, yeah, but
the basic idea is pretty simple.It's just the natural variation
in time between your heartbeats.So not just how fast it's
beating, but the rhythm. Precisely.
The consistency, or rather the inconsistency of the rhythm and
(01:45):
why that little fluctuation matters is, well, it gives us a
window into your autonomic nervous system.
The automatic stuff like breathing digestion, right?
That system has two main branches, the sympathetic think
fight or flight, and the parasympathetic rest and digest.
When you're stressed, could be ahard workout, a tough day at
work, even bad sleep, your sympathetic system tends to ramp
(02:09):
up. That usually makes your
heartbeat faster and more regularly, so less variability,
lower HRV. Got it.
So lower HIV might mean more stress on the system.
Generally, yeah, it suggests your body's in that fight or
flight mode. Conversely, when your
parasympathetic system is dominant your rest and digest
system, it slows your heart rateand increases that variability.
(02:31):
So higher variability, higher HIV is usually better, more
recovered. Usually indicates better
recovery. Yeah, more adaptability.
Your system isn't stuck in OverDrive.
It's more relaxed and resilient.OK.
That makes sense. It's about the flexibility of
the rhythm. Exactly, and tracking this over
time gives you a really valuablepicture of your sort of chronic
physiological stress level, Not just the one off bad day, but
(02:53):
the accumulated effect of everything.
Which can help you make adjustments right, manage
training lifestyle. Precisely spot trends, see how
you're responding to different stressors, and potentially
improve health or, you know, athletic performance.
So when's the best time to measure this?
My watch seems to track it all day.
Yeah, a lot too. But for getting that stable
baseline reading reflecting yourunderlying physiological state,
(03:16):
you really want measurements taken either first thing in the
morning, like right when you wake up.
Before coffee and chaos. Exactly.
Or the other good option is throughout the night while
you're asleep. Daytime measurements, they tend
to bounce around a lot because of, well, everything happening
during the day, Transient stressors, meals, movement.
It makes it harder to see the underlying recovery picture.
(03:37):
OK, morning or night. Got it.
Now the tech how do they actually do this?
ECG versus PPG? Right.
So ECG electrocardiography, that's kind of the gold
standard. It measures the heart's
electrical signals directly. Think chest straps like the
Polar H10 or H9 that serious athletes often use.
Very accurate. Then you have PPG
photopluphysmography. That's the optical one.
(04:00):
Uses little LED lights flashing against your skin.
The green lights on the back of my watch.
Usually green, Yeah. It measures changes of blood
volume under the skin to estimate heart rate and then
calculates HRV from that heart rate data.
This is what most wrist wearables use.
Garmin, whoop or a ultra human? Now there's this perception,
right, that the optical PPG stuff isn't as good as the ECG
(04:21):
chest strap. That's a super common thought,
yeah. But Marco Altini's work and
other independent studies to actually show something
interesting for measuring HRV atrest, which is key here because
that's when morning or night readings haen G can be
suprisingly accurate specifically for the main HRV
metric most wearables use, called RMSSD.
(04:42):
Really as good as a chest strap.Sometimes, yeah, or at least
perfectly adequate for tracking trends.
Some studies even found more variation comparing one ECG
device to another ECG device than comparing an ECG to a good
PPG sensor at rest. I mean think about apps like HRV
for training using just your phone camera, PPG again and
getting results comparable to ECG.
(05:02):
Wow, OK, that changes things so the light can be pretty reliable
when I'm still. For resting HRV, yes it can be.
But, and this is important, PPG has limitations.
It's much more sensitive to movement artefacts.
Like if I toss and turn at night.
Exactly. That movement can mess up the
signal, create errors in the data.
(05:22):
Also, not all wearables are great at telling you if the
signal quality was good or how they handle things like heart
rhythm irregularities which can also throw off HRV.
So the potential is there, but the implementation matters.
Right. How well the specific device
does it? And you mentioned timing before.
It sounds like when they collectthe data overnight is also a big
(05:43):
deal. Huge deal.
Marco really stresses this. You know, the traditional way
was that consistent morning measurement when wearable
started doing it automatically overnight.
Some early versions only took short samples, maybe a few
minutes here and there, or trying to grab a reading during
deep sleep or. Something just little snapshots.
Yeah. And because your nervous system
activity naturally shifts throughout the night, those
short snapshots could give you really different HRV numbers
(06:06):
depending on when they happen tobe taken.
Made the day to kind of noisy, less reliable day-to-day.
OK, so a quick glimpse isn't really enough for a solid
overnight picture. Not ideal, no, but the good news
is most of the current generation devices definitely
Aura, Woop and Garmin. Since around 2022, they've moved
to using data from the entire night that.
(06:28):
Makes more sense, averages it out.
Pretty much. It gives a much more stable and
representative picture of your overall overnight HRV status.
OK, now Marco did this cool experiment wearing like
everything at once ECG or a Garmin woop.
What did he find comparing them?Yeah, it was pretty insightful.
3 months wearing them all. First thing thing he noticed
with the absolute HRV numbers, the actual values reported was
(06:51):
that all the wearables tended toreport slightly higher HRV than
the reference ECG. Higher interesting.
Any differences between them? Rs seemed generally a bit closer
to the ECG in absolute terms. Whoops.
Data looked noisier, more spreadout.
But, and he really emphasises this, focusing on those exact
absolute numbers, probably not that useful for you day-to-day.
(07:12):
OK, so don't obsess over the specific number.
What about resting heart rate? They tracked that to.
He found some quirks there. Yeah, especially with Garmin.
At least the Forerunner 955 he tested.
Instead of an average overnight heart rate, it was reporting the
lowest 30 minute average heart rate from the past 24 hours.
Rate the whole day, not just thenight.
Yeah, which could be misleading.Like when he got sick during the
(07:34):
experiment, his overnight heart rate obviously went up, but the
Garmin reported a much lower number because it was pulling
that lowest 30 minute window from the day before he got sick.
Oh wow OK that could definitely confuse things if you weren't
aware for sure. Something to keep in mind about
how different platforms calculate things.
But despite those quirks, when he looked at the overall HRV
trends, the ups and downs over time, how did they stack up
(07:58):
against the ECG? That's where it gets more
positive. The correlations between the
wearable HRV data and the ECG data were actually pretty high,
like .91 to .96. So pretty strong agreement on
the general pattern. Yeah, it suggests they were all
generally tracking the same physiological changes, the rises
and falls in his HRV. Whoop again seemed a bit
(08:19):
noisier, especially when his HRVwas higher.
But overall they captured the trends.
OK. And this really leads to the
main point. What matters isn't the absolute
number, but the relative change over time for you.
How is your HRV today compared to your normal?
That's what reflects how your body's responding to stress.
Right, so it's all about context.
(08:40):
My personal baseline is the key.Exactly.
Which brings us to the idea of your personal normal range.
This is super critical for making any sense of the daily
numbers. Because a drop might be
meaningful, or it might just be noise.
Precisely. Is that dip just normal
day-to-day fluctuation, or is ita sign of increased stress,
illness, whatever? Without knowing your typical
(09:01):
range, you're kind of flying blind.
And you're saying a lot of the standard acts that come with
these wearables, they don't really give you that
personalised range? That's often the big limitation.
Yeah, they might just give you anumber, maybe compared to
yesterday, or show a generic good or bad, but without
constantly comparing it to your established normal range, it's
really hard to interpret properly.
This is where something like HRV4 training really differs.
(09:25):
It's whole approach is built around defining and updating
that personal normal range for you.
So in Marcos test even with the different absolute values when
he plugged the data from the Garmin aura and whoop into HRV 4
training. Which then analysed it against
his normal range. Did they all show the same
significant changes like when hegot sick?
(09:45):
Yes, exactly. All the devices, when
interpreted within that personalised context using HRV
24 training, clearly show the expected drops in HRV when he
was sick, when dealing with heatstress and the typical responses
to his training load. OK.
So that really underlines it. The raw data capture is pretty
decent across the board for trends.
Generally yes, for resting trends.
(10:06):
But the interpretation layer is where things can fall short
without that personalization. That's a great way to put it.
Marco highlighted a few common issues with typical wearable
interpretations. One is that overly simplistic.
Higher is always better idea. Right, we can assume higher HRV
exile. Good.
And often it is, but Physiology is complex.
(10:26):
Sometimes a very high reading, especially after a period of low
readings, might actually mean your body is working really hard
in recovery mode. Strong parasympathetic push.
Not necessarily that you're primed for a killer workout.
You need context. Makes sense, it's not always
linear. Definitely not.
Then there's the lack of the personalised normal range, which
we just covered makes interpretation difficult.
(10:47):
And another big one is how some platforms calculate these
overall readiness or recovery scores.
They often mix your physiological data like HRV and
heart rate with your behaviour data like how much you slept or
how hard you trained. Why is that a problem?
Because it confounds things. It mixes the input your training
sleep behaviour with the output how your body is actually
(11:10):
responding physiologically. So if you do a hard workout and
your readiness score drops, is because your body is genuinely
stressed and not recovered? Or is it just because the
algorithm knows you did a hard workout and automatically lowers
the score? It makes it hard to isolate the
true physiological response. I see you want to measure the
body's response separately from the reason for the response.
(11:31):
Ideally, yes. You want to see how your
Physiology the output changes inresponse to stressors, the input
without the input directly influencing the output score.
And HRV 4 training takes a different approach here too.
Yes, it focuses interpretation entirely around your
personalised normal range, so itflags values that are unusually
low or high relative to your normal as potentially
(11:54):
noteworthy. Giving context to both ends of
the spectrum. Exactly, and while it does
incorporate subjective feelings,how rested you feel, your mood,
muscle soreness into its advice,it deliberately keeps your
training data separate from the core physiological assessment.
This gives you a clearer pictureof your body's state.
So theoretically someone with say a Garmin or an Aura could
(12:16):
manually enter their nightly HRVand heart rate into the HRV 4
training app and get that more personalised, context aware
interpretation. Precisely.
It's a way to leverage the data your wearable collects, but
apply a different, arguably morenuanced analytical framework to
it. OK.
That's a really useful option. Now back to morning versus night
(12:36):
measurements. Any final verdict on which is
better? Marco's data suggests they both
track the big picture pretty well.
Long term trends, major stressors like getting sick,
They usually move in the same direction.
But there can be differences day-to-day.
There can be subtle differences,yeah.
Like if you have a really hard workout late in the evening or a
big meal close to bedtime, that could suppress your HRV during
(12:58):
the first part of the night. So your overall nightly average
might end up being lower than your morning reading taken after
several hours of recovery. So the timing of stressors
within the day can impact the nightly average more.
It can, but again, both methods are generally valid for tracking
trends. The best choice often comes down
to personal preference, consistency, what fits your
(13:20):
routine. Some find the quick morning
measurement easier to control and make routine.
Others prefer the passive, automated nature of overnight
tracking. And like you said, you don't
even need a fancy wearable to start the phone.
Camera apps are an option. Exactly.
Something like HRV 4 training lets you use your phone camera
for morning readings, which has been validated against ECG.
(13:40):
So the barrier to entry is actually pretty low if you just
want to explore your HRV. We've mentioned a few brands and
can we sort of categorise them like the sports focused ones
versus the more general Wellnessones, especially regarding HRV?
Yeah, it's a useful distinction,although the lines blur.
You've got wearables like Garmin, Polar, whoops which are
often heavily marketed towards athletes and you had to create
(14:01):
HRV into training load, recoveryscores, workout suggestions,
very performance oriented features.
Right. The context is often athletic
performance. Exactly.
Then you have devices like Aura and Ultra Human, the rings.
They also track overnight HRV very well, often alongside
really detailed sleep tracking. But their overall focus might be
(14:23):
broader General well-being, sleep optimization, stress
management, not just athletic performance.
But in terms of how they collectthat overnight HRV data,
especially the newer versions? The underlying tech in the use
of full night data has become quite similar across many of
them by late 2022, according to Marcos analysis.
So the data collection might be comparable, but the
(14:43):
interpretation and the features built around it often reflect
that sports versus Wellness emphasis.
Got it. Now thinking specifically about
athletes again, like the runnerstuning in may be inspired by the
5K runner. Is there a particular takeaway
for them from all this? Yes, and this is a really
important point that the 5K runner himself added to the
discussion Marco published. Resting Physiology, like
(15:04):
overnight HRV is valuable context.
Absolutely, but it doesn't directly tell you how ready you
are for exercise Physiology demands right now.
Meaning meaning for a more direct assessment of your
readiness to train, especially for higher intensity work, a
short active measurement upon waking might be better.
Like the morning reading we discussed?
Yes, specifically a one or two-minute test, often done
(15:27):
seated or even standing, ideallyusing a reliable chest strap
like a Polar H9H10 and software like HRV 4 training that
analyses that specific type of test.
This snapshot can be more sensitive to your immediate
readiness for exertion than a passive overnight average.
So the overnight average is goodfor overall trends, but the
morning spot check might be better for daily training
(15:48):
decisions. That's the argument, yeah.
Relying only on passive overnight readings for fine
tuning daily training intensity might have limitations.
The OLAR orthostatic test is kind of an exception as it's a
structured morning test built into their system, but the
general recommendation for athletes wanting the most
training relevant HRV data consider that deliberate seated
(16:10):
or standing morning measurement with a chest strap.
OK, that's a key distinction forathletes.
So wrapping this up, the main message seems to be that most
modern wearables can capture good quality resting HRV data,
especially overnight trends. Yes.
The data capture itself for tracking relative changes seems
pretty solid across the board based on Marco's work.
But, and it's a big but, the waythe native apps interpret that
(16:34):
data often falls short. That's the crux of it.
The simplistic higher is better,the missing personalised normal
range, mixing behaviour with Physiology and scores.
These limit how useful the interpretation is.
So the real power comes not justfrom having the number, but from
understanding it within your personal context, looking at
those relative changes against your baseline.
(16:54):
Absolutely. That's where the actionable
insights really come from, understanding how your body
responds to the stresses you encounter.
And exploring tools like HIV 4 training, even using manual
input from your current device, could be a way to get that
deeper, more personalised analysis.
It's definitely an option worth considering if you want to move
beyond the basic interpretations.
(17:15):
So for you listening, maybe takea critical look at how your
wearable presents your HRV. Is it giving you the context you
need? Checking out resources like HRV
fourtraining.com or the 5K runner.com could offer some new
perspectives. Yeah.
And maybe the final thought to leave you with is this.
How could really understanding your unique HRV patterns empower
(17:35):
you? Could it help you train smarter,
recover better, maybe hit those goals you're chasing, whether
it's a faster 5K or just feelingmore resilient day-to-day?
Something to Mull over.
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