Quantified Flu

About reviewed project
Quantified Flu
Can physiological parameters tracked by our wearables predict when we’re getting sick? We're building a citizen science project for this!

by Mad Ball, Bastian Greshake Tzovaras

Participating to challenge(s): Covid19 Diagnostic and Detection, Data analysis and simulation

Created on: March 19, 2020 / Last update: July 12, 2021
Interested in
3Good Health and Well-being
4Quality Education
9Industry, Innovation, and Infrastructure
17Partnership for the Goals
Skills
Webdesign
Crowdsourcing
Community management
Data science
Time series analysis
Data visualization
+ 1
17
Members
7
Needs
  • Short Name: #QuantifiedFlu
  • Status: Active/Ongoing
  • Grant information: Received €2,200.00€ from the OpenCOVID19 Grant Round 2 on 04/19/2020




Introduction

The Problem

Quantified Flu is a collective project in which we explore how to use our wearable devices and symptom self-tracking to create individual insight, to try to predict & understand when we're getting sick. While there are increasing numbers of people that have wearables such as Fitbits, Apple Watches etc, there is so far very little known about whether the sensor data from those devices could be used for gaining a better understanding of infections.


While the current interest in this is spurred by COVID-19, the results of this will relate also to the flu and colds in more general: We expect to see physiological changes – e.g. in resting heart rate, blood oxygen saturation, body temperature, etc. – in all of those cases. By doing a collaborative citizen science project around this we hope to harness the collective intelligence of all participants to quickly get a better understanding of our collective data!