An article published on a study from Stanford in PLOS Biology on January 12, 2017, indicates that it is possible for your smart watch to detect when you are becoming sick.

Stanford researchers followed 60 people through their everyday lives and found that personal biosensor devices including smart watches can help flag when people have colds. These devices can even detect and signal the onset of complex conditions like diabetes and Lyme disease. Michael Snyder, PhD, Professor and Chair of Genetics at Stanford is senior author of the study, while lead authorship is shared by postdoctoral scholars Jessilyn Dunn, PhD and Xiao Li, PhD, and researcher Denis Salins. Snyder explains that they set out to determine when people are healthy and catch illnesses at their earliest stages.

Although measuring steps and physiological parameters are commonly done by smart watches and similar portable devices, these devices are not generally used to sense illness. Taking advantage of the ease of use and portability of wearable devices, Snyder’s team collected numerous measurements from participants for up to two years. They used the data to detect deviations from the normal baseline for measurements such as skin temperature and heart rate. As the devices record these parameters continuously, they could provide a rapid means to detect the onset of diseases that cause changes in physiology.

Many of these abnormalities happen when people became ill. Snyder noted that skin temperature and heart rate tends to rise when people become sick. The team developed a software program to analyze the data from a smart watch. The program is called ‘Change of Heart’ and it detects these deviations and senses when people become ill. The devices were able to detect common colds. Snyder participated in the study and, in his case, the program helped detect Lyme disease.

Snyder explains that he had an elevated heart rate and decreased oxygen at the start of his vacation. From these symptoms, he knew something was not quite right. Snyder visited a physician after running a low-grade fever for several days and the illness was confirmed. The symptoms disappeared after Snyder took the antibiotic doxycycline. The presence of Lyme was confirmed by subsequent tests. An oxygen sensor and the smart watch were useful in detecting the earliest signs of illness.

This research opens up possibilities for smart phones to serve as a health dashboard, monitoring health and sensing early signs of illness, possibly even before the person wearing it knows that something is wrong.

The study had several other interesting findings apart from detecting illness. Individuals with indications of insulin resistance are at high risk for Type 2 diabetes and are often unaware that they have this risk factor. Personal biosensors performing a simple test could possibly be developed for those at risk for Type 2 diabetes. Heart rate patterns variations could be detected, as these tend to differ from those not at risk.

An effect that affects many of us was also found during the study. The team found that during airplane flights, blood oxygenation decreases. Although this has been known for a while, the team managed to characterize it in more detail than has previously been reported. Snyder’s team demonstrated that reduced blood oxygenation typically occurs for a big portion of a flight and showed that this is associated with fatigue. Many people report feeling tired on airplane flights. This may sometimes be attributed to a hectic work schedule, staying up late, or the stress of travel. It is however likely that reduced oxygen and cabin pressure also are contributors.

Snyder points out that the information collected could aid physicians, although he expects some initial challenges in how to integrate the data into clinical practice. Patients may want to, for example, protect the privacy of their physiologic data or may only be willing to share some of it.

Physicians and third-party payers will certainly demand robust research to help guide them on how this comprehensive longitudinal personal data should be used in clinical care. Snyder is very optimistic in the long-term and believes that personal biosensors will help maintain healthier lives.