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Using a FitBit Wearable to Predict a Possible Flu-esque illness

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If you have a FitBit wearable with heart sensor, you can be a part of a study that will predict illnesses resembling influenza.

The Scripps Research Transnational Institute is a non-profit facility for research founded back in 2007. This institute focuses specially on a concept of individual healthcare with the help of data collected through wearables and development in genomics of human bodies. FitBit has collaborated with this outfit for a long time now and their partnership spans over a many research projects.

One of these projects is focused on using data collected from fitness trackers to detect any kind of illnesses which resemble influenza. Scripps just published a research which supports the fact that a FitBit wearable with Heart rate monitor can predict the development of influenza. The main target of this study is to assist the medical officials in moving quickly against any outbreaks relating to influenza like illnesses.

Resting heart beat is one of the major signs of this illness. This goes hand in hand with our personal experience which portrays the beginning of a common cold with increased heart beat and more sleep. Other researches have touched this topic as well which have evidently shown that fitness wearables can prove to be an efficient way of diagnosing influenza and similar conditions.

In light of the ongoing flu season and the global pandemic of COVID-19, we see enormous opportunity to improve disease tracking for improved population health,” said Jennifer Radin. Jennifer is a PhD epidemiologist and works for Scripps Research Translational Institute. She is also acting as the head of this research.

This may be the most relevant time to be working on a study like this as danger of CVOID-19 looms around the world. We all can see what viral conditions like these are capable of as Corona Virus spread globally causing heavy damage and hopefully we with studies like these may be we will be more resourceful in fighting pandemics like these.

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