Your calendar tells you how long you’ve been alive. It doesn’t tell you how well.
Biological Age does. It’s built on a foundation model trained on 2.7 million hours of nightly recordings from over 100,000 people, the largest raw-waveform bio-signal dataset assembled for this kind of work to date. That model turns your Pod’s nightly data into a number that can run younger or older than your actual years, and unlike the calendar, it moves as your habits do.
Eight Sleep developed Biological Age in collaboration with Bryan Johnson, founder of Immortals and one of the world’s most prominent voices in longevity. It updates every week. Here is what actually goes into it, how the science holds up, and how to put it to work.
The two numbers on your screen
Open the feature and you will see two figures working together.
Biological Age is your Speed of Aging translated into an age you can hold up against your calendar age. If your Pod reads 27.3 years old against a calendar age of 30, the app tells you plainly: you are reading a few years younger than your age.
Speed of Aging (sometimes called Pace of Aging) is the multiplier behind that number. It sits on a scale where 1.0x means you are aging exactly in step with the calendar. Above 1.0x, your body is aging faster than your years. Below 1.0x, slower. A 0.86x reading means your body is racking up roughly 86 days of biological wear for every 100 calendar days. Small differences in that multiplier compound into real years over time, which is exactly why the app also shows you where you land against people like you: “you’re aging slower than 91% of men in their 30s”.
Both numbers update every seven days. Neither is a verdict handed down once. They are built to move, on purpose, as your habits move.
Measured continuously from the Pod and integrations
Brings together sleep, recovery, cardiovascular, and respiratory data from your Pod, plus connected apps and health records.
Here’s the part that tends to surprise people: none of the Pod’s side of that data comes from a wearable.
Built into your Pod is a sensor that feels the tiny mechanical recoil of your body with every heartbeat and every breath, a signal called ballistocardiography, BCG for short. Think of it as your mattress noticing the faint kick your body gives each time your heart contracts. Nothing to strap on, nothing to charge before bed. You just sleep, and the Pod listens all night, isolating the signals that track most closely with aging:
- Resting heart rate
- Heart rate variability
- Breathing rate
- Sleep structure, how much time you spend in deep and REM sleep versus lighter stages
That’s the nightly, automatic layer. Connect Apple Health and, for eligible U.S. members, HealthEx, and the picture widens to your daytime activity and clinical history too, which is what turns a strong sleep-based estimate into a fuller, whole-body read (more on that below).
The science behind the science
The foundation model behind your Biological Age was pretrained on 2.7 million hours of nightly recordings from over 100,000 individuals, the largest raw-waveform biosignal pretraining corpus built for this kind of work to date.¹ That scale translated directly into performance: the resulting embeddings produced the most accurate biological age estimate yet reported for any contactless, ambient sensing method, edging out other passive approaches that try to do the same thing without a wearable.¹ From there, Eight Sleep fine-tuned the model specifically to capture how physiological patterns shift as people age, and it continues to draw on Eight Sleep’s full dataset of more than 1 billion hours of sleep data as broader context.
Instead of grading everyone against one universal definition of healthy, the model weighs three things at once: your own history and baseline, patterns from people who share your age and gender, and signals from that much larger population dataset. That combination is what makes the number personal instead of a generic scorecard.
What’s actually feeding your score
Your Biological Age breaks down into contributing factors, split into what your Pod measures directly and what you choose to connect.
Measured by your Pod, every night, automatically:
- Sleep duration, benchmarked against a goal like 8 hours
- Sleep consistency, how steady your bedtime and wake time are night to night, with a goal around 95 percent
- Deep sleep, both the raw time and the percentage of your night, since deep sleep drives most of your physical repair
- Resting heart rate, where lower generally signals a more efficient, well-recovered heart
- Heart rate variability (HRV), where a higher number relative to your peers suggests a nervous system that adapts well to stress and rest
Each factor gets a clear read: in range or out of range against your goal, with a 7-day average so one rough night does not tank the picture.
External factors, once you choose to connect them:
- Apple Health adds your daytime layer: steps and exercise minutes, checked against benchmarks like 10,000 steps a day and 150 minutes of exercise a week. This is the part your Pod literally cannot see on its own; it knows what happens in bed, not what happens at the gym.
- HealthEx, for eligible U.S. beta members, adds clinical context: glucose, cholesterol, and more, pulled from your actual medical records. This is opt-in, fully consented, and something you can disconnect at any time.
The logic is straightforward: your Pod sees the night. It cannot see your workouts, your bloodwork, or how your body is actually built. Connect more, and your estimate stops being a strong sleep-based guess and becomes a fuller, whole-body read.
The coaching layer: weekly insights
Every week, the app does not just hand you a number and walk away. It surfaces the one or two things actually moving your score right now, drawn from wherever you are furthest from your own targets.
On a good week, that might read:
“Sleep is your strongest contributor. Keep it up. With an average of 7h 48m a night, your biological age is tracking younger than your actual age.”
On a tougher week, the framing stays constructive rather than alarming:
“Sleep length is working against your biological age. With an average of 5h 52m a night, it’s negatively impacting your HRV and resting heart rate.”
Even the “aging faster” framing leans on where you sit against your peer cohort rather than dropping a blunt, deflating verdict, because the whole point is to keep you motivated to act, not anxious.
That is the real trick of this feature: you are not just tracking a stat, you are watching cause and effect play out on a weekly loop.
How to actually use it, week to week
- Judge the trend, not the moment. One dip after a rough travel week or a hard training block is normal and expected. What matters is where the line is heading over a month or a season.
- Read your weekly insight first. It is built to point you at the single highest-leverage thing to change right now, so you are never guessing where to focus.
- Open your contributing factors when something shifts. If your Speed of Aging ticks up, this is where you will find out whether it was sleep duration, consistency, deep sleep, resting heart rate, or HRV driving it.
- Connect Apple Health if you have not already. It is the fastest way to move from a sleep-only estimate to one that reflects your full day.
- Consider HealthEx if you are eligible. Add in your medical records to your Eight Sleep app account. Only available in the US.
- Treat it as a feedback loop, not a report card. Earlier bedtimes, workouts you actually finish, recovery you do not skip: these are the levers, and the app will keep telling you which ones matter most for you specifically.
Who can use it
Biological Age is available to Eight Sleep members worldwide with an active membership and a Pod 4 or later generation, on the latest version of the Eight Sleep app for iOS or Android. It will arrive in China in fall 2026. HealthEx integration is rolling out first to a beta group of U.S. members, with broader availability to follow.
The Pod is not a medical device, and Biological Age is not intended to diagnose, treat, cure, or prevent any disease. For anything medical, talk to a qualified healthcare provider.
¹ Source: BCG-FM: A Foundation Model for Ambient Cardiac Health Sensing, arXiv:2606.07692. https://arxiv.org/abs/2606.07692
