Purdue University and physIQ develop an algorithm for smartwatches to detect early signs of viral infections, including COVID-19

Smartwatch COVID

Purdue University engineers and physIQ, a leader in digital medicine, have developed a viral detection algorithm for smartwatches. The innovation will be commercialized by physIQ. (Purdue University photo/John Underwood)

WEST LAFAYETTE, Ind. — Purdue University and digital medicine company physIQ announced on Thursday that they had co-developed a smartwatch algorithm designed to detect viral infections.

The algorithm will be commercialized by physIQ, and the research was led by Craig Goergen, an associate professor of biomedical engineering.

“Smartwatches are well-suited for the detection of early viral infection, including COVID-19,” Goergen said in a press release. “Infections can happen at any time, making the continuously tracked data available through an individual’s smartwatches uniquely suited to identify the earliest signs of illness. In particular, knowledge of a person’s usual heart rate and respiratory during sleep and activity over long periods of time is especially valuable for detecting subtle changes from normal.”

The research had involved a study of 100 participants, including Purdue students and staff, to determine if wearing a smartwatch to collect data was practical, inconspicuous and user-friendly. They were given a smartwatch with a pre-loaded physIQ app to collect data, along with adhesive chest-based biosensors to capture data such as heart rate, respiration rate and heart rate variability.

“The algorithms for enabling early detection are built off physiological features derived from the biosensor data collected by the smartwatches,” said Stephan Wegerich, physIQ’s chief science officer. “Generating accurate and robust physiological features forms the input to subsequent viral detection algorithms.  This requires the development of sophisticated signal processing and machine learning algorithms. Combined, these make the most out of smartwatch biosensor data, which is a big part of our collaboration with Purdue.”

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