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Hundreds of simulated Matteos
Simulated versions
Each digital version tests a what-if: if this changes now, a certain health condition develops in 10 years or it doesn't, and the biological age ends up at a certain number.
The customer's twin
Within months, customers are meant to get their own longevity digital twin, which simulates their life and predicts what happens to their health in 10, 20, and 30 years. The AI can already predict the coming night before someone goes to sleep, based on their latest biometrics. The app's homepage is also due to become AI driven, surfacing different information to each person.
More data, more versions
As more data comes in, including from other platforms people connect, the plan is for thousands of simulated versions to run on a daily and yearly basis. The models are starting to triangulate across data and spot the chance of a health condition the team hadn't thought of. Sleep and heart rate alone might even predict diabetes.
How do digital twins predict future outcomes?
A digital twin is a computer model that is updated with real data from the thing it mirrors. Engineers run the model forward under different what-if scenarios and watch where each one ends up. Michael Grieves of the University of Michigan introduced the concept around 2002 for managing product lifecycles. NASA used the term in its 2010 technology roadmap for modeling spacecraft.
How can wearable data reveal illness early?
Illness changes resting heart rate and skin temperature before symptoms appear in some people. In a 2017 study in PLOS Biology, Stanford researchers led by Michael Snyder tracked participants with smartwatches. Shifts in heart rate and skin temperature showed up around the onset of illness in a small group of participants. The work helped launch research into using wearables as early warning systems.
How is biological age estimated?
Biological age is calculated from measurements that change as the body ages. The best-known method is the epigenetic clock, introduced by Steve Horvath of UCLA in 2013, which reads chemical tags called DNA methylation at hundreds of sites in the genome. Other estimates use blood markers such as cholesterol and inflammation levels. Different methods can give different ages for the same person.