Wearable devices such as smartwatches and activity trackers have resuscitated extensively over the past few years about their potential to monitor our health. During the pandemic, attention has been focused on whether these wearable devices could detect physiological changes that might indicate a COVID infection. This may also assist with early isolation and testing, reducing the spread of the virus.
What is the evidence? Could these technologies be a great tool to assist you in dealing with the pandemic?
Let''s get to the bottom of the page.
A higher respiratory rate, or breathing rate, has been shown to be a useful biomarker for early detection of COVID. Respiratory rates can be estimated using a technique known as photoplethysmography, which requires only a single contact point (for example, your finger or wrist).
Photoplethysmography is often exposed to external influences such as ambient light, pressure, or motion. So, most studies that seek to investigate COVID have focused on observing individuals during sleep.
Fitbit, an electronic company, analyzed the nocturnal respiratory rates of tens of thousands of people on their devices in order to discern whether this strategy might assist in COVID detection.
A portion of individuals with COVID showed at least one measure of an elevated respiratory rate within a seven-day period (from one day before symptom onset, or one day before a positive test for participants without symptoms).
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Although this was observed in only one-third of symptomatic COVID patients and one-quarter of asymptomatic patients, this study suggests that commercial wearables may be a non-invasive method to detect potentially COVID infections and obtain them tested.
Another study looked at the possibility of a Whoop, a US company that develops a fitness tracker to detect COVID risk.
A group of people with COVID used data to predict infection on respiratory rate and other indicators of cardiac function.
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The model was then tested on a group of individuals with COVID, some with COVID, and others without COVID, although it has similar symptoms.
The technology was able to identify 20 percent of COVID-positive cases in the two days preceding the symptoms'' outbreak, and 80 percent of cases by the third day of symptoms based on the respiratory rate during sleep.
A recent survey uncovered that a fertility tracking tool called Ava, which is also worn around the wrist, might identify physiological changes up to two days before COVID symptoms.
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A machine-learning technique was similar to that used by data from COVID-positive patients.
Testing revealed that it was able to detect 68% of positive cases up to two days before symptoms became apparent.
Other forms of digital detection Outside wearables, digital technologies might be utilized in other ways to detect COVID. High-quality microphones are already embedded in smartphones and other devices, paving the way for audio analytics.
COVID is usually associated with the upper respiratory tract and vocal cords, thus affecting a person''s voice. A mobile app designed to accurately detect whether a person has the virus 99% of time.
My colleagues and I have developed an app that aims to identify if you have COVID due to your coughing.
The technology is currently under discussion.
Tracking illness Research has also explored the possibility for smart technology and wearable devices to monitor individuals during a COVID infection.
In high-risk individuals managing COVID at home, one team used an in-ear device to measure oxygen saturation, respiratory rate, heart rate, and temperature every 15 minutes.
A trained team monitored the data and was used to identify who might need additional medical treatment before being detected. Smartphones were proposed as a suitable solution to detect hypoxia via the user''s fingertip.
Hypoxia refers to low oxygen levels in the body tissues and occurs silently in some COVID patients with more serious diseases.
Wearable technologies have also been used to map COVID''s impact on a greater scale. For example, data from tens of thousands of Fitbits revealed changes in sleep during the pandemic (early in the pandemic people were generally sleeping for longer).
Additional line of defense Most wearable and other technology being investigated for their potential to detect COVID rely on artificial intelligence (AI) techniques, particularly machine learning, and deep learning.
In order to identify useful body signs, the AI can effectively scan a large amount of data in depth.
Although biological signals may vary greatly between patients and within, so there may be limitations to these AI models in the real world. It''s also worth noting that off-the-shelf wearable devices haven''t specifically been designed to continuously monitor infectious disease symptoms.
Deshalb besteht rumours that the technology and algorithms may be improved.
As part of this research, we will conduct extensive research to address these challenges, as well as close scrutiny of possible privacy concerns linked to collecting biological data.
Wearables and other digital methods may provide an additional line of defense to help keep COVID and other infectious diseases at bay.