We’re all going to die eventually—but what if you knew when you’d be at risk for dropping dead, based solely on the way you walk? A new study shows that measurements taken with wrist-worn motion sensors can be used to predict one’s mortality risk up to five years later. As one of the largest validations of wearable technology to date, the research raises the possibility of one day using the motion detection system in smartphones to survey patient health without the need for in-person visits to the doctor’s office.
The study, published Thursday in the journal PLOS Digital Health, was run using data from over 100,000 Britons from the massive UK Biobank project, which began collecting health and biometric information from participants in 2006 and will follow them for another 14 years. From a week of wrist sensor data, researchers at the University of Illinois at Urbana-Champaign designed a model that pares down a person’s acceleration and the distance they traveled into six-minute chunks. According to study author Bruce Schatz, a University of Illinois computer science researcher, the scientists chose this duration to mimic the six-minute walk test: a measurement of heart and lung function commonly taken during a medical appointment that tasks participants with walking at a normal pace for six minutes and compares their total distance traveled to benchmarks according to their age.
The test is “a very good external measure of what’s going on internally,” and could easily be replicated using the accelerometer present in a wrist sensor or a cheap phone, Schatz told The Daily Beast. “I know for a fact that these kinds of models will work with cheap phones.”
Predictions of future death made by the researchers’ model were correct 72 percent of the time after one year, and 73 percent after five years—a similar rate of accuracy found in a study published last year that analyzed the same data set but used hours, rather than minutes, of data. This new study, argued Schatz, is a more promising demonstration of passive monitoring technology like phone and wrist sensors as his team’s model requires less data and affords a great degree of privacy to the user.