Stanford geneticist Michael Snyder’s research into wearable biosensors has turned into a case study demonstrating the promise of predictive medicine – with Snyder as the star subject.
Snyder had himself and 59 other people hooked up with an array of up to seven biosensors that are designed to monitor heart rate, skin temperature, oxygen uptake, body activity and other health metrics.
The continuous sensor readings were supplemented by periodic lab tests, focusing on factors ranging from blood chemistry to gene expression. It’s similar to the personalized approach to wellness that’s being pioneered by Seattle-based Arivale.
“We want to study people at an individual level,” Snyder explained in a report on the study from the Stanford University School of Medicine.
The study, published today in PLOS Biology, shows that it’s possible to associate deviations from a health baseline with environmental conditions, illnesses or other factors that affect a person’s health. Once those deviations are distilled into algorithms, wearable sensors could provide an early warning about conditions ranging from common infections to the early signs of diabetes.