New Study finds Cardiorespiratory fitness (VO2 Max) measured from activity data on your iPhone to be quite accurate

Apple's HealthKit

A new study published today in the Nature Journal (scientific reports) examined results from smartphone-recorded physical activity for estimating cardiorespiratory fitness and observed that the results were fairly accurate when compared with laboratory-based VO2 max testing.

Fitness estimates can also be used to identify those at risk for diabetes, obesity, and falls to target with preventive measures such as exercise programs, nutrition programs, and fall prevention.

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Monitoring of cardiorespiratory fitness should not require expensive lab equipment or wearables but can be accurately estimated using movement data that is already available on our smartphones.

Researchers from Beth Israel Deaconess Medical Center, Boston, used smartphone derived physical activity data to estimate fitness among 50 older adults. 

The team exclusively focussed on recruiting iPhone owners who were undergoing cardiac stress testing and collected their recent iPhone physical activity data.

Cardiorespiratory fitness was measured as peak metabolic equivalents of task( METs). VO2 max is often expressed in metabolic equivalents of task, which are multiples of normal baseline oxygen uptake at rest.

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Testing of functional aerobic capacity is classically measured in a lab by functional exercise testing, such as with a treadmill, where oxygen uptake is measured as the workload is incrementally increased.

Smartwatches such as the Apple Watch have made it easier to measure and monitor cardio-fitness levels (VO2 max) in recent years but many people do not have the latest smartwatches.

Since smartphones are ubiquitous these days, the researchers wanted to develop a model to estimate a person cardio fitness level using smartphone data. 

The advent of smartphones has introduced physical activity measurement as a common staple as most smartphones integrate accelerometers and gyroscopes which can track owner motion. These measurements are passive and do not require the smartphone owner’s intervention.

Your Apple iPhone Health app keeps track of various mobility metrics including gait distance, speed and walking asymmetry. 

The team used a predictive model to estimate cardiorespiratory fitness. Such models may input anthropometric data (i.e. age, sex, and body-mass index) and day-to-day physical activity, which itself is associated with physical fitness.

The researchers exported the data out of Apple Health app and used specialized multi-variate regression models to estimate cardiorespiratory fitness.

Cardiorespiratory fitness as peak metabolic equivalents of task (METs) was estimated by maximal treadmill stress testing using the extensively validated Bruce protocol

The team found the results to be very accurate. 

“Our model using smartphone physical activity estimated cardiorespiratory fitness with high performance. Our results suggest larger, independent samples might yield estimates accurate and precise for risk stratification and disease prognostication.”

Accuracy was higher when compared to results from HRV4Training app.

Accurate estimates of cardiorespiratory fitness available at the point of care have enormous potential value. Estimated fitness could be used to estimate mortality and guide end-of-life planning.

Smartphone estimated fitness could also guide decisions for risky medical interventions such as chemotherapy and surgery. Individuals with low fitness and high baseline mortality may be less inclined to take on additional risk.

The promising results from this new study demonstrate that the incremental predictive utility of smartphone data, combined with its ready accessibility, open new exciting opportunities for clinical and research estimation of cardiorespiratory fitness.

Source: Smartphone recorded physical activity for estimating cardiorespiratory fitness 

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Sudz Niel Kar
I am a technologist with years of experience with Apple and wearOS products, have a BS in Computer Science and an MBA specializing in emerging tech, and owned the popular site AppleToolBox. In my day job, I advise Fortune 500 companies with their digital transformation strategies and also consult with numerous digital health startups in an advisory capacity. I'm VERY interested in exploring the digital health and fitness-tech evolution and keeping a close eye on patents, FDA approvals, strategic partnerships, and developments happening in the wearables and digital health sector. When I'm not writing or presenting, I run with my Apple Watch Ultra or Samsung Galaxy Watch and closely monitor my HRV and other recovery metrics.


  1. It would be great to provide an example of an (imaginary) person’s VO2, showing the calculation. Suppose a person is 75 years old, weight 170 lbs and is 5’9″.

    Suppose the person’s resting heart rate is 47 BPM and a fast mile walk results in an average heart rate of 125 BPM.

    Is this adequate information to provide a VO2? (This is me, with a slightly lower age given. My Fitbit Charge 2 tells me my cardio fitness score is 51-55 and that this is excellent for my age and weight, etc.)

    I’d love to see a rough calculation.

    • HI Steve,

      Those are excellent numbers!

      The simplest formula to calculate your VO2 max is VO2 max = 15 x (HRmax/HRrest). So for your example, your HRrest is 47 and your HRmax is 145 (220-75.)

      So using the simple calculation your VO2 max = 15 (145/47) which is 46 (46.27)

      This particular study used the Bruce Protocol to estimate VO2 max (maximal treadmill stress test) which requires has the user get on a treadmill with speed and incline increasing every three minutes until you reach 85% of your maximum heart rate (based on age.)


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