New Zealand-based artificial intelligence (AI) company Datamine has created a personal early warning system that detects viral infections, including Covid-19.
Called ëlarm, the early warning indicator tackles the problem of viral spread by asymptomatic individuals who do not know they are infectious.
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By creating personal baselines of biometric data retrieved from smartphones and other devices such as Fitbit, Apple Watch, and Samsung, ëlarm identifies changes to those individual baselines that match Covid-19 patterns when the body starts fighting a viral infection.
Operating in the country since last June, the system was developed to identify Covid-19 cases up to three days before people knew that they were affected.
ëlarm CEO and Datamine founding director Paul O’Connor said: “With ëlarm, you can know you’re sick before you feel sick. Based on our New Zealand success and the extensive data we’ve gathered from clinicians around the world, ëlarm is an accurate predictor of viral symptoms.
“When Covid-19 emerged, we had already created a vault where personal health and wearables data is safely stored and analysed.
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By GlobalData“We saw that we had the expertise and technology to make a substantial contribution in the fight against coronavirus.”
Even though ëlarm is not a test or medical advice, the system warns users on biometric changes that signify viral infection and offers relevant World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) guidelines.
It will help individuals to get tested and self-isolate even before symptoms appear, preventing the disease spread.
ëlarm is ‘device agnostic’ as opposed to developing technology based on specific smartwatches.
As a software service, it uses data from wearable devices and is available globally.
New Zealand epidemiologist professor Michael Baker said: “It’s very encouraging that New Zealand is producing exciting innovations of new surveillance tools for tracking people who are potentially infected by coronavirus and other infectious agents.”
