By closely tracking data patterns from wearable devices, it may be possible to detect when a person is getting sick, according to new research from PLOS Biology.
The research team, led by geneticist Dr. Michael Snyder at Stanford University, looked at 2 billion measurements taken from 60 study participants. The measurements included weight, heart rate, skin temperature, sleep, blood oxygen levels, physical activity, caloric burn and exposure to gamma rays and x-rays, and were measured by one or more of seven commercially-available activity trackers. Baseline data for each participant was established at the beginning of the study. The researchers found that data patterns deviated from the established norm for each participant in situations such as changes in environmental conditions (flying in an airplane, etc.), illness or other factors affecting health.
Specific health observations that were detected by the wearables:
- Onset of Lyme disease and inflammation
- Physiological differences between insulin-sensitive and insulin-resistant individuals, which may help to identify those at risk for type 2 diabetes
The researchers say, “Overall, these results indicate that portable biosensors provide useful information for monitoring personal activities and physiology and are likely to play an important role in managing health and enabling affordable health care access to groups traditionally limited by socioeconomic class or remote geography.”