Quantified Flu: Can wearables predict when we're falling sick with COVID-19 or other infections?
About the Project
Can the various physiological parameters tracked by our wearables help to predict when we’re getting sick? This is not only related to COVID19, but also to the flu and colds in more general, as we'd expect to see some physiological changes – e.g. in resting heart rate, blood oxygen saturation, body temperature – in all of those cases. It could be extremely useful if we could predict falling sick using these data at a point before one is consciously aware of it. We are planning to do a collaborative community science project in which we will try to use both retrospective data and ongoing data collections to address this question. Worst case we'll learn that wearable data signals are too weak to make predictions, best case we'll figure out how to predict sickness some days in advance.
You can read more details at https://app.jogl.io/project/135#about
We got an early prototype in place and hope to launch last week of March!
We already have a small prototype website in place that can access wearable data from different manufacturers and is also used to track when the participants noticed their symptoms. The website is mainly build with Django/Python and tiny bits of JS for the frontend but needs to be expanded: We're looking for help with:
- Backend | Adding support for more wearables (Python)
- Data Science | Help in translating the raw data collected by participants into insights (Python/R/your choice)
- Copy editing | Help us write the copy for the website and other materials to explain to participants and potential participants what's going on
- Who is already working on this
- How to get in touch
- Number of volunteers needed
- Preferred Volunteer location
- Organization status