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Wearable sensors can tell when you are getting sick


Key points from article :

Analysed nearly 2 billion measurements from 60 people, including continuous data from wearables and periodic data from laboratory tests.

Collected data on weight; heart rate; oxygen in the blood; skin temperature; activity, including sleep, steps, walking, biking and running; calories expended; acceleration; and even exposure to gamma rays and X-rays.

Given a baseline range of values for each person, it is possible to monitor deviations and associate them with environmental conditions, illness or other factors that affect health.

Distinctive patterns of deviation seem to correlate with particular health problems.

Algorithms could potentially contribute to clinical diagnostics and research.

The study was published in the PLOS Biology journal.

Mentioned in this article:

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Eric Topol

Founder and director of the Scripps Research Translational Institute, American cardiologist, scientist and author

Michael Snyder

Professor of Genetics and Chair at Stanford University

PLOS Biology

Journal providing information from all aspects of biology.

Stanford University School of Medicine

Medical school that improves health through discoveries and innovation in health care, education and research