Your ring does not know how last night felt

Nila now reads from Apple Health and Health Connect. When you turn it on, the numbers your phone, watch or ring already collect show up beside the things you log yourself: how you slept, how the day went, what your body did.

Building that took a decision we made early and want to say out loud, because wearables are everywhere in midlife health now, and the research on what these devices can and cannot actually tell you deserves a plain-language airing.

What is a device measuring, and what is it inferring?

That question applies to every device on every wrist and finger, including the data we now bring into Nila. And there is good, peer-reviewed research that answers it, which is more useful than any one company's news cycle.

A ring or a watch measures movement, and it measures signals like heart rate and skin temperature. It does not measure brain activity. Sleep staging, the split into light, deep and REM, is a model built on top of those signals. So is a readiness score. So is a recovery score. Those are interpretations, and they are only as good as the model behind them.

What the validation research actually shows

There is a real and growing literature here, and it is more nuanced than either the marketing or the backlash.

A 2025 study in Scientific Reports put three commercial ring trackers against polysomnography in a university sleep lab with a population that had a mix of sleep disorders. Most earlier validation work had been done in healthy people, which is exactly the group where devices look best. The pattern that shows up across this literature is consistent: agreement is strongest for the crude question of asleep versus awake, weaker for how long you were awake in the night, and weakest for stage-by-stage classification. Performance also degrades in the people who most want an answer, meaning those with a sleep disorder.

A 2024 evaluation of three commercial wearables in healthy adults in Sensors found the same shape of result, and a 2024 report in Frontiers in Sleep on a research-grade study watch reinforced it. This is not a scandal. It is what sensor science looks like when it is being done properly, and it is why the honest framing of a nightly sleep number is "an estimate from a model", not "your sleep".

Where midlife sits in all of this

Here is the part that matters most to us.

Menopause research has been trying to instrument hot flashes for decades. The MsFLASH network compared sternal skin conductance monitors against what women reported, in the lab and in daily life. In the lab, the monitors did reasonably. Out in real life, agreement between what the monitor flagged and what the woman actually experienced dropped off sharply. Work has continued, including a 2025 study in Psychophysiology on predicting hot flash onset from physiological signals to trigger just-in-time cooling, which is a genuinely promising direction.

Two things follow from that history.

First, the signal that a midlife woman cares most about is one of the hardest for a device to catch reliably, and we are not aware of a mainstream consumer wearable that claims validated detection of vasomotor symptoms. Your ring may notice that your temperature and heart rate did something strange at 3 a.m. It does not know you woke up soaked and threw the duvet off.

Second, the fluctuating hormonal physiology of perimenopause is not the physiology most consumer algorithms were tuned on. Baselines move. Sleep fragments. Resting heart rate and temperature shift across the transition. A model that was validated on stable adults and then told to score a body in flux will produce confident numbers with quiet error bars.

So here is what Nila does with your data, and what it refuses to do

We show counts, not verdicts. Steps, resting heart rate, heart rate variability, exercise minutes, whatever your device sends. Rendered exactly as it arrived, on the same grid as the symptoms and moods you logged yourself.

We do not produce a score. No readiness, no recovery, no sleep score, no letter grade. A single number that compresses your night into a verdict is the most persuasive and least defensible thing a health app can put on a screen.

We do not stage your sleep. If your device sends us sleep hours, you see sleep hours. We will not restate a model's guess about REM and deep sleep as though it were a measurement of your brain.

We do not diagnose. No sleep apnea flags, no arrhythmia calls, no "your hormones are doing X". Those are conversations for a doctor or a specialist, with real testing behind them.

We do not claim causation. The Patterns grid puts your numbers next to each other and lets you look. It does not tell you that your poor sleep caused your low mood on Thursday, because with a few weeks of one person's data, nobody can say that honestly.

Your felt experience outranks the device. This is written into the product. If the number on the screen does not match how the night actually went, the night wins. That line appears wherever imported numbers appear, and the long version is on our disclaimer page.

Why we built it that way

Because the thing a woman in perimenopause needs is not another authority telling her how she is doing. She has usually had a decade of that.

What tends to be missing is evidence. Something she can put in front of a doctor that says: here are eleven weeks, here is what I logged, here is what my watch recorded alongside it, here is the pattern. Patterns was designed to make that visible and portable, not to be right about her on her behalf.

The moment we add a score, we take the interpretation away from her and put it in our model. That is a trade we are not willing to make. It is also, generally, the part of this category that ends up being argued about.

An open invitation to device makers

We are not anti-wearable. The opposite. We think this hardware is one of the more useful things to happen to midlife health in a decade, and the constraint right now is not sensing, it is context and validation.

If you build wearables and you are thinking about menopause, we would like to talk. Specifically about:

• Validation cohorts that include perimenopausal and postmenopausal women, and that report performance in that group separately rather than folding it into a general adult sample.
• Nocturnal vasomotor events. The physiological signature is real and the research base exists. What is missing is a validated consumer-grade implementation and, crucially, honest reporting of where it fails.
• Surgical and treatment-induced menopause. Sudden loss of ovarian function is a different curve from a natural transition, and it is almost never modelled.
• Uncertainty as a first-class output. A device that told a woman "this estimate is unreliable for you tonight, here is why" would be more trusted, not less.

We will bring the symptom side, the member context, and a stance on data that will not embarrass anyone. Write to us at hello@hellonila.com.

Sources

• Performance of wearable finger ring trackers for diagnostic sleep measurement in the clinical context. Scientific Reports, 2025. https://www.nature.com/articles/s41598-025-93774-z
• Accuracy of three commercial wearable devices for sleep tracking in healthy adults. Sensors, 2024. https://www.mdpi.com/1424-8220/24/20/6532
• Performance of the Verily Study Watch for measuring sleep compared to polysomnography. Frontiers in Sleep, 2024. https://www.frontiersin.org/journals/sleep/articles/10.3389/frsle.2024.1481878/full
• Laboratory and ambulatory evaluation of vasomotor symptom monitors from the MsFLASH network. Menopause, 2012. https://pmc.ncbi.nlm.nih.gov/articles/PMC3326209/
• Hot flash prediction for the delivery of just-in-time interventions. Psychophysiology, 2025. https://pubmed.ncbi.nlm.nih.gov/40682261/

Nila's Health Bridge is live on iOS and Android. You can see what it does at hellonila.com/track, and read our full position on device data on the disclaimer page.