the researchers found that overall the health tracker, combined with a computer algorithm, correctly identified 68% of Covid positive people two days before their symptoms appeared.
The international team including from University of Basel (Switzerland) and Imperial College London, pointed out that while a PCR swab test remains the gold standard for confirming Covid-19 infection, “our findings suggest that a wearable-informed machine learning algorithm may serve as a promising tool for presymptomatic or asymptomatic detection of Covid-19”.
Wearable AI Trackers To Detect Covid-19
The team conducted a trial, on a AVA bracelet, and included 1,163 participants all under the age of 51 who wore the tracker at night. The device saves data every 10 seconds and requires at least 4 hours of relatively uninterrupted sleep. The bracelets were synchronized with a complimentary smartphone app on waking.
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All participants took regular rapid antibody tests for Covid infection. Those with indicative symptoms took a PCR swab test as well.
The algorithm was ‘trained’ using 70% of the data from day 10 to day 2 before the start of symptoms within 40 days of continuous monitoring of the 66 people who tested positive for SARS-CoV-2. It was then tested on the remaining 30% of the data.
Some 73% of laboratory confirmed positive cases were picked up in the training set, and 68% in the test set, up to 2 days before the start of symptoms.
The researchers acknowledge that their results may not be more widely applicable.
But “wearable sensor technology is an easy-to-use, low-cost method for enabling individuals to track their health and wellbeing during a pandemic”, they wrote in the paper.
Further, “these devices, partnered with artificial intelligence, can push the boundaries of personalized medicine and detect illnesses prior to (symptom occurrence), potentially reducing virus transmission in communities”.
Source: IANS
