Smartwatches have been touted as a future way to identify COVID-19 patients before testing from pre-symptomatic data. Devices such as the Apple Watch and Fitbit smartwatches have been labelled as a potential future warning system for detecting if people have become infected by viruses such as COVID-19 – before even a test would.
The digitised watches are essentially simply very small computers taking on the form of a watch. Simpler devices such as the Fitbit are closed system items that focus solely on collecting biometric data from their wearer. Apple Watches and other similar brands are more complex, often including phone data, updates on notifications and graphics for their users.
Wearable smartwatches such as the Fitbit as well as other brands such as Garmin, gather biometrics information on their users which is then used to let them know if they are keeping up with their fitness goals. Information collected can include activities such as exercise measured from the number of steps you take, distance travelled and active minutes. Other data could be focused on how much sleep the user is getting and when they are entering specific sleep stages. Females are also able to record menstrual health data, whilst those interested in weight loss can keep track of their calories burned for the day.
Smartwatches such as the Apple Watch and Fitbit have the benefit of measuring user data over long periods of time, making it possible for them to identify unusual inputs in the data such as temperature or heart rate, which could be suggestions of an infection. With pre-symptomatic identification of sick patients potential, it could be possible to isolate and prepare treatment for those infected prior to any testing result.
With global numbers of newly infected cases and deaths from the coronavirus, hopes for ways into the new normal are well received on the global stage. Only time will tell if there can be a technological way forward out of the pandemic that could aid other further spread prevention measures such as vaccination.