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Apple researchers trained a research model called the Wearable Behavior Model (WBM) on long-term patterns in Apple Watch- and iPhone-derived health measurements. It was evaluated on 57 health-related prediction tasks and often added useful information beyond a simple baseline. This is not a feature that diagnoses Apple Watch owners: the research does not announce a consumer rollout or show that using the model improves clinical outcomes.
What Apple’s Wearable Behavior Model does
WBM is a foundation model: a general-purpose system designed to learn patterns that can support multiple later prediction tasks, rather than an algorithm built for only one condition. Instead of relying solely on raw streams such as photoplethysmography (PPG), ECG, or motion-sensor readings, it learns from higher-level measurements that summarize activity and bodily behavior over time.
The research, titled “Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions,” used more than 2.5 billion hours of wearable data from approximately 162,000 participants in the Apple Heart and Movement Study (AHMS). Apple describes evaluation across 57 health-related tasks. The paper appeared as an arXiv preprint on June 30, 2025, and is listed in Apple and ICML 2025 materials.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchThe broader AHMS cohort is described as having more than 278,000 participants and up to five years of longitudinal data. That is not the same as the WBM training group: the model’s reported scale is approximately 162,000 participants. The data came from Apple Watch and iPhone-derived measurements, along with study information—not from Apple Watch alone.
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- A FULL-FEATURED HEALTH TRACKER—Apple Watch Series 11 gives you invaluable insights about your body, right from your wrist. Take an ECG anytime* and get alerts for a high and low heart rate or an irregular rhythm*—so you can stay closer to your heart. You can also view your overnight health tracking metrics with the Vitals app* and be notified of possible sleep apnea.*
- KNOW YOUR SLEEP SCORE—With advanced sleep tracking, Series 11 gives you a daily sleep score. It’s an easy way to help measure and understand the quality of your sleep, so you can make it more restorative.
- GET HYPERTENSION NOTIFICATIONS—Did you know that Series 11 can spot signs of chronic high blood pressure? By analyzing how your blood vessels respond to beats of the heart, it can notify you of possible hypertension.*
- SAFETY FEATURES—A smartwatch that puts your safety first. Series 11 can detect a hard fall or severe car crash, automatically help connect you with emergency services, and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
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What “behavior data” means here
In this study, behavior does not mean messages, browsing history, or an ordinary-language psychological profile. It means measurable patterns in movement, sleep, and bodily signals across time. The researchers used 27 interpretable HealthKit-derived quantities, which include categories such as:
- Activity: active and basal energy, steps, exercise time, standing time, and flights climbed.
- Cardiovascular measures: resting heart rate, walking heart-rate average, heart rate, and heart-rate variability.
- Other vitals: respiratory rate, blood oxygen, and wrist temperature.
- Gait and mobility: walking speed, step length, double-support percentage, asymmetry, steadiness, stair speed, and falls.
- Sleep-related measurements.
These are processed measurements derived from device signals, not the raw sensor streams themselves. That makes the inputs more readily described in everyday terms, though it does not make every model prediction easy to explain.
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- A FULL-FEATURED HEALTH TRACKER—Apple Watch Series 11 gives you invaluable insights about your body, right from your wrist. Take an ECG anytime* and get alerts for a high and low heart rate or an irregular rhythm*—so you can stay closer to your heart. You can also view your overnight health tracking metrics with the Vitals app* and be notified of possible sleep apnea.*
- KNOW YOUR SLEEP SCORE—With advanced sleep tracking, Series 11 gives you a daily sleep score. It’s an easy way to help measure and understand the quality of your sleep, so you can make it more restorative.
- GET HYPERTENSION NOTIFICATIONS—Did you know that Series 11 can spot signs of chronic high blood pressure? By analyzing how your blood vessels respond to beats of the heart, it can notify you of possible hypertension.*
- SAFETY FEATURES—A smartwatch that puts your safety first. Series 11 can detect a hard fall or severe car crash, automatically help connect you with emergency services, and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
- A POWERFUL FITNESS TRACKER—With advanced metrics and motivating features like Pacer, Heart Rate Zones, training load, and Workout Buddy powered by Apple Intelligence from your nearby iPhone*—Series 11 is made to help everyone stay active, from runners and hikers to strength-training enthusiasts.
Why patterns over days may matter
A single heart-rate reading captures a moment. A sustained shift in walking, sleep, exercise tolerance, or mobility can reveal a different kind of information—one that develops over hours, days, or weeks. For some health questions, a persistent change in routine may be more useful than an isolated sensor measurement. Behavioral measurements may also capture aspects of function, such as how much someone moves, that a single physiological signal cannot show on its own.
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This is the study’s rationale, not a claim that behavior data are always better. The results indicate that behavioral and raw-sensor representations can be complementary; combining them generally improved performance across tasks. Raw signals may remain important for questions that depend on detailed physiology, while longer-term patterns can add context. The research also explored ways to represent irregular time series with gaps. Its paper reports a state-space-model approach based on Mamba-2 among the effective design choices. See the paper abstract and full paper for technical details.
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- GET SMARTER HEALTH INSIGHTS—Apple Watch SE 3 is an advanced health tracker that helps you better understand your body. The smartwatch sends alerts for an irregular heart rhythm, or an unusually high or low heart rate.* You can view your overnight health tracking metrics with the Vitals app,* track your sleep score, and get sleep apnea notifications.*
- A GREAT FITNESS TRACKER—SE 3 can track your workouts in a healthy number of ways—from running and strength training to simply achieving your 10K steps a day. With real-time metrics and Workout Buddy powered by Apple Intelligence from your nearby iPhone,* you’ll hit your goals like never before.
- KEEP HELP CLOSE AT HAND—SE 3 is a smartwatch that can detect a hard fall or severe car crash and automatically help connect you to emergency services and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
- WOMEN’S HEALTH INSIGHTS—SE 3 has advanced sensors that track your wrist temperature while you sleep. With this smartwatch, you can log your periods and symptoms, get period predictions, and get notified of cycle deviations.*
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What the results show—and what “92% accurate” leaves out
The 57 tasks covered a range of study-defined health-related outcomes, including baseline conditions, medication-related outcomes, demographic and individual-level classification, sleep-related predictions, and changing health states. Results varied by task; they should not be condensed into one accuracy score.
For 47 baseline outcomes, WBM outperformed a simple supervised baseline on 39, with a median AUROC improvement of about 0.017 among those outcomes. It significantly improved on 30 of the 47. On the eight outcomes where the baseline did better, WBM remained close, with a median AUROC deficit of about 0.008. The paper also reports significant improvement over the baseline for all eight time-varying health-detection tasks it describes.
Rank #4
- GET SMARTER HEALTH INSIGHTS—Apple Watch SE 3 is an advanced health tracker that helps you better understand your body. The smartwatch sends alerts for an irregular heart rhythm, or an unusually high or low heart rate.* You can view your overnight health tracking metrics with the Vitals app,* track your sleep score, and get sleep apnea notifications.*
- A GREAT FITNESS TRACKER—SE 3 can track your workouts in a healthy number of ways—from running and strength training to simply achieving your 10K steps a day. With real-time metrics and Workout Buddy powered by Apple Intelligence from your nearby iPhone,* you’ll hit your goals like never before.
- KEEP HELP CLOSE AT HAND—SE 3 is a smartwatch that can detect a hard fall or severe car crash and automatically help connect you to emergency services and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
- WOMEN’S HEALTH INSIGHTS—SE 3 has advanced sensors that track your wrist temperature while you sleep. With this smartwatch, you can log your periods and symptoms, get period predictions, and get notified of cycle deviations.*
- GREAT BATTERY LIFE AND FASTER CHARGING—Enjoy a smartwatch with all-day, 18-hour battery life* from sunup to sundown. Then charge up to twice as fast as SE 2* and get up to 8 hours of battery in just 15 minutes.*
AUROC measures how well a model ranks examples with an outcome above examples without it across possible decision thresholds. It is not the percentage of people correctly diagnosed, and a small AUROC change does not by itself establish clinical value. The study’s task-specific metrics depend on the outcome, cohort, available data, and comparison model.
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Some secondary coverage has used “up to 92% accuracy” framing. That is not a fair summary of the entire study: neither Apple’s research summary nor the paper abstract presents one universal 92% accuracy figure for WBM. A best-case or task-specific number cannot be applied to every health condition or Apple Watch owner. The sound conclusion is that the model showed useful, variable predictive performance across many research tasks—not that it diagnoses conditions with 92% accuracy.
Best Value
- A FULL-FEATURED HEALTH TRACKER—Apple Watch Series 11 gives you invaluable insights about your body, right from your wrist. Take an ECG anytime* and get alerts for a high and low heart rate or an irregular rhythm*—so you can stay closer to your heart. You can also view your overnight health tracking metrics with the Vitals app* and be notified of possible sleep apnea.*
- KNOW YOUR SLEEP SCORE—With advanced sleep tracking, Series 11 gives you a daily sleep score. It’s an easy way to help measure and understand the quality of your sleep, so you can make it more restorative.
- GET HYPERTENSION NOTIFICATIONS—Did you know that Series 11 can spot signs of chronic high blood pressure? By analyzing how your blood vessels respond to beats of the heart, it can notify you of possible hypertension.*
- SAFETY FEATURES—A smartwatch that puts your safety first. Series 11 can detect a hard fall or severe car crash, automatically help connect you with emergency services, and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
- A POWERFUL FITNESS TRACKER—With advanced metrics and motivating features like Pacer, Heart Rate Zones, training load, and Workout Buddy powered by Apple Intelligence from your nearby iPhone*—Series 11 is made to help everyone stay active, from runners and hikers to strength-training enthusiasts.
Is WBM on your Apple Watch now?
No consumer feature is announced in the cited research materials. The study does not establish that WBM is integrated into watchOS or Apple Health, and there is no indication here that owners can activate it or receive its predictions today. A research model is different from a product feature: deployment would raise questions of validation, user-facing interpretation, privacy, and, where applicable, regulatory review. This work also does not establish that WBM is a medical device or provides medical diagnoses.
Study consent is not the same as future product data use
According to the paper, AHMS participants enrolled through Apple’s Research app, provided informed consent, and controlled which categories of data they shared. That describes governance for this research cohort; it does not settle how a future commercial version would handle data.
The cited study materials do not establish whether a future product would process predictions on-device or in the cloud, whether third-party apps could access them, or what sharing and deletion controls would apply. Nor should the research pipeline be treated as evidence that WBM runs privately on a watch. If a consumer feature were introduced, readers would need to assess its specific disclosures and permissions rather than assume that research consent governs commercial use.
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- Who enrolled: AHMS participants were U.S. adults who joined through an iPhone research app. People with compatible devices, reliable access, and motivation to participate may differ from the broader population. Performance may not transfer equally across age, sex, race, disability, health status, or socioeconomic circumstances.
- Missing and irregular measurements: Watches are removed, not worn overnight, or used inconsistently. The research addresses irregular sampling and gaps, but results do not guarantee equally reliable predictions for someone with sparse data.
- Correlation is not cause: A model can learn that a pattern accompanies an outcome without identifying why. Reduced activity, for example, could reflect illness, injury, a medication, a job change, or other circumstances.
- Labels can be imperfect: Outcomes may rely on surveys, medical records, or study-derived information. Such labels can be incomplete, delayed, or affected by access to care.
- Device and population shifts: The model was built around Apple-derived HealthKit measurements. Different devices, sensors, processing methods, or usage patterns may change input distributions and undermine direct transfer.
- Prediction is not clinical benefit: The study reports predictive performance, not evidence that acting on WBM predictions improves treatment, prevents disease, reduces hospitalizations, or extends life.
- Individual errors remain possible: A statistically useful model can still be wrong for a particular person. A false positive may cause anxiety or unnecessary care; a false negative may create false reassurance.
More consistent wear and clean data may offer richer context, but they cannot eliminate these limitations. A change in walking or sleep can be useful information to discuss with a clinician; it is not, by itself, a diagnosis or a reason to change treatment.
What the work could mean next
If models like WBM are validated in broader populations and tied to clear, safe actions, long-term wearable patterns could support research into passive monitoring, personalized baselines, and earlier recognition of changing health states. Hybrid systems that combine behavioral patterns with raw sensor signals may be more useful than either input type alone for some tasks. Those are possibilities, not announced Apple Watch capabilities. Until clinical utility and product details are established, WBM is best understood as a research result about the potential information in everyday behavior—not a feature users can rely on for health decisions.
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