Stanford U: Wearables of the future will be used as early warning system
STANFORD, Calif. — The future of wearables may not only be in self-care, where users collect health data points to help guide their lifestyle choices, but also as a diagnostic tool to diagnose disease earlier in its cycle, according to a study released by Stanford University School of Medicine Thursday.
Wearable sensors that monitor heart rate, activity, skin temperature and other variables can reveal a lot about what is going on inside a person, including the onset of infection, inflammation and even insulin resistance, according the researchers.
Over the course of the study, the Stanford team of researchers collected nearly 2 billion measurements from 60 people, including continuous data from each participant's wearable biosensor devices and periodic data from laboratory tests of their blood chemistry, gene expression and other measures. Participants wore between one and eight commercially available activity monitors and other monitors that collected more than 250,000 measurements a day. The team collected data on weight; heart rate; oxygen in the blood; skin temperature; activity, including sleep, steps, walking, biking and running; calories expended; acceleration; and even exposure to gamma rays and X-rays.
The study demonstrated that, given a baseline range of values for each person, it is possible to monitor deviations from normal and associate those deviations with environmental conditions, illness or other factors that affect health. Distinctive patterns of deviation from normal seem to correlate with particular health problems. Algorithms designed to pick up on these patterns of change could potentially contribute to clinical diagnostics and research.
The work is an example of Stanford Medicine's focus on precision health, whose goal is to anticipate and prevent disease in the healthy and to precisely diagnose and treat disease in the ill.
Anecdotally, the study helped diagnose a significant health issue in lead researcher Michael Snyder long before he would have sought treatment.
On a long flight to Norway for a family vacation last year, lead researcher Snyder noticed changes in his heart rate and blood oxygen levels. As one of the 60 participants in the digital health study, he was wearing seven biosensors. From previous trips, Snyder knew that his oxygen levels normally dropped during airplane flights and that his heart rate increased at the beginning of a flight — as occurred in other participants. But the values typically returned to normal over the course of a long flight and after landing. This time, his numbers didn't return to baseline. Something was up, and Snyder wasn't completely surprised when he went on to develop a fever and other signs of illness.
Two weeks earlier, he'd been helping his brother build a fence in rural Massachusetts, so his biggest concern was that he might have been bitten by a tick and infected with Lyme disease. In Norway, Snyder persuaded a doctor to give him a prescription for doxycycline, an antibiotic known to combat Lyme disease. Subsequent tests confirmed that Snyder had indeed been infected with the Lyme microorganism.
Snyder was impressed that the wearable biosensors picked up the infection before he even knew he was sick. "Wearables helped make the initial diagnosis," he said. Subsequent data analysis confirmed his suspicion that the deviations from normal heart rate and oxygen levels on the flight to Norway had indeed been quite abnormal.
The wearable devices could also help distinguish participants with insulin resistance, a precursor for Type 2 diabetes. Of 20 participants who received glucose tests, 12 were insulin- resistant. The team designed and tested an algorithm combining participants' daily steps, daytime heart rate and the difference between daytime and nighttime heart rate. The algorithm was able to process the data from just these few simple measures to predict which individuals in the study were likely to be insulin-resistant.
During a visit to the doctor, patients normally have their blood pressure and body temperature measured, but such data is typically collected only every year or two and often ignored unless the results are outside of normal range for entire populations. But biomedical researchers envisage a future in which human health is monitored continuously.
"We have more sensors on our cars than we have on human beings," Snyder said. In the future, he said, he expects the situation will be reversed and people will have more sensors than cars do. Already, consumers have purchased millions of wearable devices, including more than 50 million smart watches and 20 million other fitness monitors. Most monitors are used to track activity, but they could easily be adjusted to more directly track health measures, Snyder said.
With a precision health approach, every person could know his or her normal baseline for dozens of measures. Automatic data analysis could spot patterns of outlier data points and flag the onset of ill health, providing an opportunity for intervention, prevention or cure.
Michael Snyder, professor and chair of genetics, Stanford University, is the senior author of the study, which was published online Jan. 12 in PLOS Biology. Postdoctoral scholars Xiao Li and Jessilyn Dunn, and software engineer Denis Salins share lead authorship.