Pulsomics explained: the raw pulses your Ring records for research

What does Pulsomics collect?

Pulsomics collects three things.

The first is what your Ring records: the raw pulse recordings a study collects, alongside the measures your Ring already produces. Your Ring shines a small light into your skin and reads how much of it comes back. Blood absorbs light, so as each heartbeat pushes a pulse of blood through your finger, the reflection dips and recovers. That rising and falling trace is your pulse, read optically. It has a name: PPG, short for photoplethysmography.

PPG is the same signal behind the heart rate and the heart rate variability you already see on the Ultrahuman app. What Pulsomics does differently is keep it raw. Your Ring saves it in short windows rather than one continuous block, spaced across the period a study covers. In the studies opening now that means windows of about 60 seconds, spaced across your detected sleep window. Later studies may record at other times of day, or in windows of a different length.

The second is a short set of questions you answer when you join. They are drawn from six themes: demographics and body measurements, sleep and breathing, medical history and medications, fitness and activity, metabolic health, and lifestyle. Some ask about things that change how a pulse looks, such as an implanted heart device, pregnancy, or medication that alters heart rate. The third is anything you add yourself, such as a recent blood panel or a laboratory fitness test. Both the questions and any reports you upload are essential to making sense of the raw pulse data. Your participant profile sits on the Pulsomics settings page, where you can read and edit it. Nothing is taken from anywhere else on your phone.

Why record the raw pulse instead of a heart rate?

The numbers you see each morning are summaries. Your Ring condenses the PPG trace into one figure per interval, which is what makes heart rate variability and your resting heart rate simple to read. The condensing loses detail by design, because streaming a full waveform off a ring all night is not practical.

What a summary leaves out is the shape of the signal. Each beat has a rise and a fall, the rhythm shifts across a night, and the whole trace drifts gently with each breath.

That shape carries information. In 87 adults aged 21 to 68, the shape of the PPG pulse recorded at the finger tracked large-artery stiffness, a key indicator of cardiovascular health.

That study also read the pulse at the finger with light. It measured one property of the arteries, not anything Pulsomics sets out to predict.

What makes a recording useful is the context stored beside it: who someone is, how they live, and the measured values they already hold. Without that, the same recording teaches very little.

Why do the studies want people across the whole range?

A model can only recognize what it has already seen. Show it a few hundred people who resemble each other, and it learns what is typical for them. Show it many thousands, across ages, body types, fitness levels and skin tones, and it learns what is typical for anyone.

Research of this kind often recruits at the extremes, comparing a pronounced condition against a healthy group. The model that comes out tells those two ends apart and little in between. Ordinary people mostly sit in the middle, and collecting from them lets a model learn the gradations.

Large public research programs are built on the same reasoning. All of Us set out to enroll at least a million people in the United States, deliberately recruiting groups that biomedical research has historically left out.

A recording becomes more useful when it sits beside a real number from the same person, such as an HbA1c or a laboratory VO2 max. Every extra pair means a test somebody had to go and get, which is why such studies are usually small. It is also why a study asks whether you already hold a relevant result.

How will Ultrahuman check the models work for everyone?

Accuracy is usually reported as a single number, averaged across everyone in a study. An average can look excellent while the experience underneath it is uneven. A model that has seen far more of one kind of person does better on that kind of person.

Optical measurement has a documented version of this problem. One review of hospital records covered 1,050 Black and 7,342 White patients. A light-based oxygen reading missed genuinely low blood oxygen in 17.0% of readings from Black patients, against 6.2% from White patients.

Pulsomics is built so this can be checked rather than assumed. Participants share a little context about themselves: age, sex and a self-selected skin-tone band. That makes it possible to look at how a model performs group by group.

Findings from models developed on this data will be published by skin tone, sex and age band, alongside the overall figure. Where a group is too small to draw a conclusion from, we will say so. Saying we cannot yet answer for a group is more useful than an average that hides it.

What do participants get back?

Participants see their own contribution, the nights logged and the studies joined, plus how the research is progressing across the community. When a study closes, the findings are shared with everyone who took part, and published.

Taking part is free, and there is no compensation for it. No diagnosis is returned. What participation builds is the models themselves which generate wellness-focused health scores and insights. Models that hold up become features in the Ultrahuman app that everyone uses.

How is your data handled?

Data is de-identified before it is used. It is never sold, and it is never shared with advertisers, employers or insurers. Access to the raw recordings is limited to the Ultrahuman science team. Anything published externally is grouped across many people rather than about anyone individually.

Your data is not monitored in real time, and nothing you record triggers an alert. Pulsomics is a research study rather than a monitoring service. If you have a health concern, speak to a qualified clinician.

You can pause or withdraw at any point, and neither carries a penalty. On leaving, you can delete what you have contributed, or leave it in for research and stop future collection. The one thing we cannot undo is data already pooled into something published.

Who oversees Pulsomics?

Pulsomics runs under the study code Pulsomics PS 001. It is registered with the Clinical Trials Registry of India as CTRI/2026/08/115584. It was approved on 28 July 2026 by the Medstar Speciality Hospital Ethics Committee in Bengaluru, an independent ethics committee.

Further studies follow, each announced once it has been approved. Questions about the research itself reach the science team at science@ultrahuman.com.

How do you join Pulsomics in the app?

Pulsomics appears on the Ultrahuman app home screen. You need to be 18 or over and an active Ultrahuman Ring user.

Every study page sets out in full what it asks before you join. The full study consent, our Terms of Use and our Privacy Policy stay available in the app, including after you have joined.

After that, a study asks nothing of you beyond answers to a few study-specific questions and the Ring you already wear. Keep it charged and your phone nearby, and the recording happens on its own.