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What is the context of this research?

The common cold is the most common type of illness. Adults get colds 3-5 times a year. 111 million work hours are lost in the US every year due to the common cold. Science has yet to come up with a way to treat the common cold and all the current medicine are only good for reducing symptoms. Aside from external viruses, everybody has a dormant infection that begins to rear its head as soon as the body’s immune system is weakened due to hypothermia, chronic stress, fatigue and etc. The objective of our research is to identify changes in HRV indicators that would predict the risk of getting a common cold. If we can figure out ways to predict colds, we can figure out how to prevent them! HRV indicators we use to track patterns.

What is the significance of this project?

In the US, people spend over $4.6 million on flu-related medicine annually. We start to infect others one day before we feel any symptoms, which is why the virus spreads so quickly. Preventing colds is all about changing our lifestyle habits. HRV technology is already available to everybody, since people can now take measurements with their cellphone cameras. As apps and devices that track heart rate variability become increasingly more available, every person will be able to reduce the frequency of common colds simply by tracking their measurement results. Everybody can get a quick assessment of their health by taking daily measurements. At Welltory we will be able to evaluate trends and predict the onset of a cold before the appearance of any symptoms.



What are the goals of the project?

The goal of our research is to identify changes in heart rate variability indicators that would predict the risk of getting a common cold and to develop a formula for calculating the risk of getting a cold. The researches which were conducted earlier typically run into problems collecting data and getting a large enough sample size. We already have a database of HRV measurements (over 40,000 users and over 250,000 measurements) that are connected to data about people’s lifestyles. The process of research: We will select people who have had an ARVI, analyze regular HRV measurements and lifestyle factors 1-2 weeks before the person got sick. We'll detect common patterns for research subjects and come up with a formula that predicts the likelihood of getting sick