Week 28: Optical Sensors for Spot Checks
A few options.
Hi there 👋
I hope you are doing well.
As you probably know already, I’m a big fan of morning measurements to assess our resting physiology (e.g. heart rate variability, or HRV).
By measuring intentionally, we can control most confounding factors, and gain insights that we would otherwise miss with automated data collection or data collection during sleep (this is due to the better timing of morning measurements, and also to differences in body position, see some examples here).
On top of the reliability, the morning routine offers a great opportunity to stop, reflect, and improve our self-awareness, e.g. by filling in a subjective questionnaire before looking at our data, as in the HRV4Training app.
Often the opposite happens when looking at wearables data right after waking up, letting the data (and possible inaccuracies or confounding factors) decide how our day will be - and often turning tracking into unhealthy behaviors - this is currently amplified by the overwhelming amount of made-up metrics and various estimates wearables provide, despite no hardware innovations in over a decade.
When it comes to assessing our body’s response to stress and using the data effectively, less is more.
In this context, we keep an eye on sensors that can make it easier to take spot-check measurements, as not everyone likes to use a chest strap (even though the chest strap - e.g. a Polar H10 - remains the only way to actually measure heart rate variability or the electrical activity of the heart, as opposed to pulse rate variability or changes in pulse rate at the periphery, such as the wrist, finger or else).
Unfortunately, most wearables do not implement the standard Bluetooth heart rate profile, meaning that you can use them only via their app, and the wearable cannot communicate with any third party apps, which is obviously a pity as much more could be done with these sensors (or maybe the raw data is so bad that it’s better that you never see it? food for thought).
An alternative that I used to recommend is the Scosche Rhythm24 (not to be confused with the newer Rhythm2 and Rhythm+, which cannot do HRV analysis). This is an older sensor that includes an HRV mode and therefore can be used with HRV4Training and other apps. Make sure not to move at all and not to contract any muscle when using optical sensors for HRV analysis, because otherwise the data is complete garbage, as I’ve shown several times (e.g. here). This is one of the reasons why it makes no sense to use HRV for continuous stress monitoring outside of a spot check or night data (when there is no movement).
Another alternative is the Kyto 2935 which can be connected to the ear or finger, depending on your preference:
Below is some data collected using the Kyto device. Sessions 001 and 003 were collected with the finger sensor, while 002 with the ear sensor, and compared against a chest strap, the Polar H10.
The protocol consisted of either normal breathing at rest, while seated, or deep breathing exercises. For data collection, I used the HRV Logger app to collect RR intervals from the chest strap, and another HRV Logger app to collect RR intervals using the Kyto (my apps are available here).
RR and PP intervals:
We can see that the PP and RR intervals track very well the different phases of the protocol (minutes 1-4 with regular breathing, and minutes 5-6 with deep breathing), and are rather similar.
However, when computing rMSSD from RR and PP intervals for the data above and another two tests, we do have an offset in the data:
Still, we can see that the relative changes within sessions are captured very well, even though for some reason, data from the Kyto sensor seems lower (which is somewhat odd, as typically we get higher variability with PPG). I wonder if there is some form of overcorrection in place.
As my recommendation is never to do anything with absolute values of HRV, but to track changes over time, I consider this device good enough for the task, given the PP intervals above, and the ability to clearly capture relative changes even in a short segment of data.
Just make sure not to compare data collected with this sensor, with data collected with a different device (this is the case for any sensing modality, as there can always be differences based on where the sensor is placed, the technology used, artifact correction, etc.).
As always, I do not have any commercial affiliation with the company/device, but this is what I ended up using for long biofeedback sessions using the HRV4Biofeedback app, where I prefer not to use the camera for obvious reasons.
To recap, in terms of optical sensors:
Phone camera, supported on iPhone and most Android phones, to be used only when Optimal signal quality is consistently reported (validation here).
Scosche Rhythm 24 (not the + or the 2), a bit older and harder to find these days, but still very accurate.
Kyto 2935, which includes a finger and an earlobe module, depending on your preference, could be a valid alternative.
Whoop, should still have a broadcasting mode that allows you to measure with a third-party app, something I had covered here. No other wearable implements the standard Bluetooth heart rate profile and therefore no other wearable (Oura, Garmin, Coros, etc.) can be directly linked to a third-party app to collect RR (PP) intervals for HRV analysis independently of the wearable’s manufacturer software.
These days, my recommendation is not to use wearables and avoid the distraction of continuous data, made-up metrics, inaccurate estimates, conflicting information, and so on, and if possible, simply get a sensor that provides the required data (RR intervals) without any of the additional confusion, and then use it with a tool that allows you to measure your resting physiology and assess how it is changing with respect to your historical data, as we do in HRV4Training.
A Polar H10 strap or a Kyto 2935 are great options in this context, as is the phone camera.
Recent articles and updates [June 2025]
Below is a new recap of articles, research, and updates from the past month. I hope you’ll find the articles useful, and I would like to take the opportunity to thank you for your support.
Discount for HRV4Training Pro: 20% off 🖥️
HRV4Training Pro is the ultimate platform to help you analyze and interpret your physiological data, for individuals and teams.
You can find a guide and overview here.
Try HRV4Training Pro for free at HRVTraining.web.app or use promo code SCIENCE for 20% off.
While we really appreciate the pledges on Substack, our writing here will always remain free, and Pro is the best way to support our work.
I thank you for that.
When using Pro, the app will also automatically recognize your account and add the Normal Range to the Baseline view, together with detected trends and additional annotations, which can help contextualizing longer-term changes.
You will also be able to pick rMSSD as the parameter to see on the homepage of the app.
See you next week!
Marco holds a PhD cum laude in applied machine learning, a M.Sc. cum laude in computer science engineering, and a M.Sc. cum laude in human movement sciences and high-performance coaching. He is a certified Ultrarunning Coach.
Marco has published more than 50 papers and patents at the intersection between physiology, health, technology, and human performance.
He is co-founder of HRV4Training, Endurance Coach at Destination Unknown, advisor at Oura, guest lecturer at VU Amsterdam, and editor for IEEE Pervasive Computing Magazine. He loves running.
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Hi Marco. Thanks for the valuable insights, in fact I am somewhat struggling between hrv4training data and then, Oura recommendations. This summer deep sleep apparently hasn’t been so easy (Oura says) - but then HRV morning measures give me green light, so I go for it since I feel good. What is your opinion on accuracy for time in sleep phases measurements a ring does with PPG? I really appreciate your criteria and work. Thanks
Hi Marco, I really enjoy reading your insights. This last post and sensors reminded me to ask you if you have any experience with https://www.movesense.com (or products based on this sensor/white labeled)? Given it is ECG based I figure it should be as accurate as the polar H10? Movesense is on my radar personally because I'm interested in building a self-tracker system that also includes movement and temperature + HR/HRV and does not depend on a phone. I'm thinking about getting a development kit to learn more.