Bracelet ‘can diagnose COVID 48 hours before symptoms develop’

According to new research, a fertility bracelet can diagnose COVID up to 48 hours before symptoms develop. The AVA device can reduce the spread of the virus by acting as an early warning system.

Worn like a watch, its common use is to help women get pregnant by identifying the most promising days in their menstrual cycle. The information is based on skin temperature, pulse, blood flow, sleep patterns, breathing and heart rate – and is sent to a smartphone app.

Scientists say that this measurement has detected early symptoms of the coronavirus – such as fever. Corresponding author Dr. Lorenz Risch and his colleagues predicted about 70 percent of cases – up to two days in advance.

He said: “To our knowledge, this is the first prospective study to measure physiological changes in respiratory rate, heart rate, skin temperature and perfusion to develop an algorithm for the detection of pre-symptomatic COVID-19 infection. “

These patients are likely to ignore safety precautions – which could lead to increased transmission of the virus, he said. Early isolation will limit exposure to susceptible individuals.

The findings, published in the BMJ Open, are based on 1,163 Under 50s in Liechtenstein tracked between March 2020 and April 2021. Participants wore bracelets at night. It delivers data every 10 seconds and requires at least four hours of relatively uninterrupted sleep.

The devices were synchronized with a complementary smartphone app that recorded the consumption of alcohol, prescription or recreational drugs and possible COVID symptoms. Routine rapid antibody tests for the virus were also conducted. People with suggestive symptoms also took PCR swab test.

All provided personal information about age, gender, smoking status, blood group, number of children, household contacts or exposure to work colleagues who tested positive for COVID, and vaccination status.
Some 127 people (11 percent) developed the infection, of whom 66 had worn their bracelet for at least 29 days before the onset of symptoms.
They were confirmed by a PCR swab test – so they were included in the final analysis.

Surveillance data revealed significant changes in all five physiological indicators. The symptoms of Kovid lasted for an average of 8.5 days. The algorithm was ‘trained’ using 70 percent of the data from day 10 to day two before the onset of symptoms within a 40-day period of continuous monitoring of 66 people who tested positive. After this it was tested on the remaining 30 percent.

Some 73 percent of laboratory confirmed positive cases were picked up in the training set and 68 percent in the test set – up to two days before the onset of symptoms.

‘A promising tool’

Dr Risk, from Dr Risk Medical Laboratory, Vaduz, said: “Wearable sensor technology may be able to detect COVID-19 during the pre-symptom period. Our proposed algorithm detects COVID-19 positive two days before symptom onset Identified 68% of the participants.”

“Recent studies have highlighted the need to identify potential cases before symptoms begin to prevent virus transmission. Our findings suggest that a wearable-informed machine learning algorithm can be used to detect pre-symptomatic or asymptomatic cases of Covid-19. may serve as a promising tool for detection.”

Dr. Risch said: “Wearable sensor technology is an easy-to-use, low-cost method to enable individuals to track their health and wellbeing during a pandemic. Our research shows that partnering with artificial intelligence How these devices can push the limits of personalized medicine and the detection of diseases before the occurrence of symptoms, potentially reducing transmission of the virus in communities.”

It is now being tested in a large group of 20,000 people in the Netherlands. The result is expected by the end of this year.

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