A question that occasionally comes up is whether you could use heart rate variability (HRV) continuously, during the day, to identify mental stress with e.g. a wearable

In my opinion, the short answer is no

Here, truly less is more

For the long answer, see below 🧵👇
Normally, when we talk about stress, we consider all sources (mental and physical), as physiologically, there is ~no difference (see slides 23-24 here: slideshare.net/marcoalt/heart…)

This means that you cannot separate mental stress from physical stress in HRV, in the "real world"

This is also why HRV measurements should be taken in certain well-defined conditions, for example, first thing in the morning or during the night, so that baseline physiological stress can be captured in a repeatable context (more details here: medium.com/@altini_marco/…)

During the day, many transient stressors will play a role, from diet to light exercise to mental stressors, etc.

Many of these transient stressors will have no long-term impact, while others will pile up and impact your baseline physiology

Thus, morning or night measurements will be highlighting periods of high stress (both mental and physical) in response to strong acute stressors, or chronic ones, as shown here: )

While some devices try to use daytime data to look into stress, the nature of what is being measured (i.e. the autonomic nervous system activity) makes it so that in my opinion, the limitations are huge and practical applicability very limited

For example, you could think of building a model in which your own HR / HRV during the day is compared only to your own history at the same time of the day (to account for individual variability and the effect of the circadian rhythm), and also only when you are at rest ....

... however HR / HRV will react dynamically to everything: the time of your lunch, or the macronutrients in there, or if you had a hard workout, or were just chatting with a friend, your HR will also be high and HRV suppressed, without any movement or 'dangerous' stressor

Plus, stress can be good. The goal should not be to get warned about any physiological change that resembles stress

Some stressors have a "negative" acute impact on the body but then lead to improved health (e.g. exercise)

Continuous measurement trivializes these aspects

My point is that these metrics are useful when properly contextualized, e.g. morning or night measurements or even just before / after a stressor, during aerobic exercise, etc., but when looking more broadly at daytime data (automatically) with consumer wearables, not really

Note that certainly larger stressors can be identified (e.g. sickness), but there would be too many false positives (periods in which you are not actually stressed), for this to be effective, in my opinion

HRV is insightful in the context of mental stress of course, but continuous measurement and analysis without overinterpreting any minor change is a hardly solvable challenge unless the user is constantly in the loop (which would be alienating, talking about mental health..)

Less measurements, more insights

One data point per day is really all you need to assess physiological stress and do something about it, whenever possible

Plus, this approach leads to a healthier relationship with technology, wrt continuous measurement (in my opinion)


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More from @altini_marco

12 Oct
Baseline at the top end of the normal range and daily heart rate variability (HRV) looking really good (for my standards at least)

Looks like some intensity is on the menu for today's run Image
Took a minor hit after last Thursday's track session (8 x 800) + double on the bike

Re-added intensity more systematically recently, but keeping it at a low frequency (once every 7-10 days) and very flexible

Health brings fitness Image
Definitely a good day

Plus, the "100 km del Passatore" was just confirmed for next May. Better keep this up

cc coach @dwrowland

Read 4 tweets
2 Oct
I measure my resting physiology in two ways, which I consider equivalent (with some nuances):

• Morning measurement: 1 minute using the phone camera and HRV4Training
• Night data: average of the full night using the Oura ring (which I also pull in HRV4Training)

A 🧵👇

I use both for obvious reasons (see bio), and have discussed previously in more detail night data: medium.com/@altini_marco/… - covering also the main differences with morning measurements

I always like to back up the theory with real-life data, so here are 6 months of data

The data I am showing is the same I had shown a few days ago

I want to highlight how the data is extremely similar when there are no disruptions in heart rhythm, and how depending on your preference or constraints, you can pick whichever tool

Read 13 tweets
10 Mar
There's a new independent validation out looking at the accuracy of commercially available HRV apps and sensors

Lowest median error:

🥇 HRV4Training + H10 (3%)
🥈 Oura ring (4%)
🥉 HRV4Training PPG (5%)

I'll take it. Some thoughts below


The full text is available here: frontiersin.org/articles/10.33…

Had mixed feelings at the beginning as we had an issue on iPhone 8, which was fixed for HRV4Training, but not for Camera HRV (showing poor results). This is most likely reflected in the reported quality though

another important point is that at this point it should be clear that PPG vs ECG is not what the conversation should be about. PPG works great and can easily outperform ECG (see Firstbeat + chest strap ranking poorly)

Why? Because HRV is all about how you handle artifacts

Read 4 tweets

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