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Researchers have found that wrist-worn health devices can be combined with machine learning to detect COVID-19 infections as early as two days before symptoms appear, and this could open the door to applying the use of wearable health tech for the early detection of other infectious diseases. The “COVI-GAPP” study was conducted by researchers from Hamilton’s own McMaster University, as well as the Dr. Risch Medical Laboratory, the University of Basel and Imperial College London.
The study collected data from 1,163 participants over a one year period between 2020 and 2021. Participants wore an AVA fertility tracker, which is a commercially available and FDA approved bracelet that monitors breathing rate, heart rate, heart rate variability, skin temperature and blood flow at night while sleeping. Over the course of the study, 127 of the participants tested positive for COVID-19. The bracelet recorded noticeable changes in all five physiological indicators during all stages of the infection.
For the full article, click here : https://brighterworld.mcmaster.ca/articles/researchers-use-wearable-tech-to-detect-covid-19-before-onset-of-symptoms/