The combination of those three factors indicated those participants may be at higher risk of having an infection
What if your fitness monitor knew when you were getting sick, well before you even started to feel lousy? That science-fiction scenario might come sooner than you think.
New research from the Stanford University School of Medicine found that fitness trackers may potentially be used to detect illness. Since the biosensors in many of these already monitor heart rate, activity, skin temperature and other variables, they could be tweaked to identify deviations from your norm. And those abnormalities can point to health issues like infection, inflammation and insulin resistance.
In total, the team collected about 2 billion measurements from 60 people, including data from the wearable sensors—things like weight, heart rate, blood oxygen levels, sleep habits, physical activity, and calorie expenditure—as well as from lab tests.
More research still needs to be done to determine how to synthesize these massive datasets into information that’s meaningful to individuals. But, they are making progress.
For example, several participants in the study had higher-than-normal readings for skin temperature and heart rate, and their lab tests showed that many of them had increased levels of an inflammatory marker in their blood.
The combination of those three factors indicated those participants may be at higher risk of having an infection, an autoimmune disease, or developing heart disease or cancer, the scientists say.
Plus, the researchers also created an algorithm taking into account the difference between the participants’ daytime heart rate and nighttime heart rate, as well as their daily step count. From this, they were able to predict which participants were insulin resistant, a condition that can lead to prediabetes or diabetes.
The science is still preliminary, but the researchers believe that wearable sensors may one day play a role in preventive healthcare by detecting illnesses and conditions at an early stage.