How smart health connected watches help prevent epidemics

February 24, 2020

Health smart health connected watches are now a reality and their use is increasing from year to year. Beyond the fashion effect, they are also real health prevention tools.Indeed, a study published in The Lancet shows the value of using health data collected by Fitbit brand activity trackers (bought by Google in 2019). Cross-checking data collected by watches, in particular heart rate and sleep-related data, with data known to the CDC (Centers for Disease Control and Prevention – USA) would speed up monitoring and anticipate changes in epidemics.

smart health connected watches to anticipate epidemics

Data on resting heart rate and sleep time collected by Fitbit smart health connected devices could help better anticipate epidemiological changes by supplying predictive models with data collected from users.It is the Scripps Research Translational Institute which revealed to have worked on this new way of considering epidemiology by having information collected directly on the wrist of people supposedly sick.

The whole point of this method is to considerably reduce the information processing time. In fact, the CDC has so far only obtained the data within a relatively long period, between one and three weeks, and did not communicate itself on the figures except sometimes several months late. We can therefore hope that a massive collection of health data, processed anonymously in just a few hours, would help to contain the epidemic better and help caregivers to act more quickly if an epidemic wave is suspected.

How to use the data collected in real time

It was by combining the data of more than 47,000 users of smart health connected objects with the data previously collected by the CDC, that the researchers obtained a clear improvement in their prediction model.

This anonymized data was analyzed thanks to measurements carried out on more than 200,000 users of the Fitbit brand. Thus 13.3 million measurements could be studied by the researchers, in particular the FCR (heart rate at rest) and the duration of sleep.The researchers gathered around this study set weekly "alert" thresholds on the increase in the HRF and the level of sleep, most likely indicative of a condition. This cross-tabulation allowed the team to define models.

Big data & public health

This is not the first time that we have tried to cross-reference the personal data of users with epidemiological statistical data. The use of big data in health is very promising, especially since smart health connected health objects have successfully adopted by the general public and are no longer reserved for geeks. Cohorts now make it possible to aggregate very large volumes of data, both in terms of the number of patients and the volume of vital data.

Researchers working in the laboratories of large technology companies – be it Apple, IBM, Google or others – seek to establish the value of big data for public health. Among the best known attempts we can cite Google with the Google Flu Trend but we also know that Facebook and Twitter engage in the exercise by analyzing the research and content of their users.

The marriage of technology and health is well and truly established and tomorrow the data collected may be useful for the benefit of all!

>> Find out more: read the Lancet article