Wearable system detects COVID two days before symptoms appear

What if a fitness tracker sitting on your wrist could detect COVID-19 before you even developed symptoms? An impressive new study claims this is not only possible, but preliminary investigations found infections can be detected nearly 48 hours before symptoms appear.

The new research began in early 2020, soon after the pandemic kicked off. A team of researchers wondered whether data from a wrist-worm health tracker could be leveraged to pick up small changes in a person’s vital signs that precede the onset of COVID-19.

Around 1,000 young participants were recruited from an ongoing observational health study and supplied with a commercially available wrist-worn device known as the Ava bracelet. The device is worn at night and every 10 seconds it measured heart rate, breathing rate, skin temperature, heart rate variability and blood flow. It is generally used as a fertility monitor due to its ability for tracking real-time changes to these five health measures.

Over the course of a year-long study 11% of the cohort came down with a lab-confirmed case of COVID-19. Around half of those COVID-positive subjects had a month of good wearable data preceding their infection, helping the researchers develop an algorithm that can detect small changes across the earliest stages of illness.

Noticeable changes in the days before COVID symptoms appeared were detected across all five measures recorded by the wearable. In particular, changes to heart rate, heart rate variability and wrist skin temperature were the most significant early features of COVID-19, preceding noticeable symptoms.

A novel machine-learning algorithm was trained on 70% of the COVID-positive cohort and then tested on the remaining 30%. Remarkably, the algorithm accurately caught 68% of the positive COVID cases two whole days before any symptoms appeared.

“Wearable sensor technology is an easy-to-use, low-cost method for enabling individuals to track their health and well-being during a pandemic,” the researchers concluded in the new study. “Our research shows how these devices, partnered with artificial intelligence, can push the boundaries of personalized medicine and detect illnesses prior to SO [symptom onset], potentially reducing virus transmission in communities.”

The idea that health wearables could detect infectious diseases before any tangible symptoms appear is not new. A fascinating study published last year tested out the idea on influenza and the common cold.

That research actually infected several dozen young volunteers with either rhinovirus or H1N1 and then tracked several health measures using a fitness tracker over the following days. Not only did the study establish that infections could be predicted using wearable health data around 24 hours before symptoms appeared but the severity of the subsequent infections could also be predicted with around 90% accuracy.

David Conen, an author on this new COVID-detection study, said the potential for detecting infections by combining advanced algorithms with real-time health data from wearables is promising. His team is now conducting a larger study testing the COVID-detection system in 20,000 subjects. Results from that investigation are expected later this year.

"That an existing medical device is able to be used in a different meaning [shows] that wearables have a promising future," said Conen. "This is not related only to COVID, in future diseases, it could also lead to preventative treatments and prevent significant complications."

The new study was published in the journal BMJ Open.

Source: McMaster University