We exist in an era where the dependency on fancy tech is the new trend. Strapping on a smartwatch before going for a run seems like a routine that didn’t exist a decade ago, but now is everyone’s lifestyle.
With that being said a new study reveals how population-level models of health and mortality risk can be built using passive smartphone monitoring of people’s walking activities.
See How The Experiment Measuring Mortality Risk Unfolds
A total number of 100,000 people who wore activity trackers with motion sensors for a week participated in the study. To replicate smartphone monitoring, the predictive algorithms solely used walking intensity.
The team just needed 6 minutes per day of steady walking data acquired by the sensor, along with conventional demographic factors, to adequately validate predictive models of mortality risk.
What Happens Next?
The equivalent gait speed determined from this passively obtained data was a predictor of 5-year death independent of age and sex.
These findings demonstrate that passive motion sensor measurements of gait speed and walk tempo can be as accurate as active measuring methods.
In the future, this approach may be scalable, granted the popularity of passive smartphone activity tracking makes population-level analysis utilizing similar measures possible.