09 February 2023 , 17:57
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Fitness tests are useful tools for predicting your risk of heart attack and diabetes – but they can be complicated.
The most accurate ones have been limited to top athletes working out on treadmills in labs. But now we could all measure how fit and healthy we are from the comfort of an armchair.
Cambridge researchers have developed a clever method for measuring fitness with a wearable device, without the need to exercise.
“You don’t need an expensive test in a lab to get a real measurement of fitness – the wearables we use every day can be just as powerful, if they have the right algorithm behind them,” said Professor Cecilia Mascolo from Cambridge’s Department of Computer Science and Technology.
While wearing sensors, 11,000 participants in their study provided data to develop a model that predicts VO2 max – the capacity of the body to do aerobic work.
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“VO2 max isn’t the only measurement of fitness, but it’s an important one for endurance, and is a strong predictor of diabetes, heart disease, and other mortality risks,” said co-author Dr Soren Brage from Cambridge’s MRC Unit. “However, since most VO2 max tests are done on people who are reasonably fit, it’s hard to get measurements from those who are not as fit and might be at risk of cardiovascular disease.” Co-lead author, Cambridge’s Dr Dimitris Spathis, added: “We wanted to know whether it was possible to accurately predict VO2 max using data from a wearable device, so that there would be no need for an exercise test.” Participants wore wearable devices continuously for six days. The sensors gathered 60 readings per second, resulting in an enormous amount of data. The key was to use it to make accurate predictions.
Some smartwatches and monitors on the market claim to give estimates of VO2 max. But it’s very difficult to assess their accuracy as the algorithms that power them can be a bit of a mystery and are
not published.
“Everything on your smartwatch related to health and fitness is an estimate,” said Dr Spathis.
“We’re transparent about our modelling and we did it at scale. We show that we can achieve better results with the combination of noisy data and traditional biomarkers.”
Prof Mascolo added: “Cardio fitness is such an important health marker, but until now we did not have the means to measure it at scale.
“These findings could have significant implications for population health policies, so we can move beyond weaker health proxies such as the body mass index.”