The Apple Watch’s initial medical device accessory has been cleared by the U.S Food and Drug Administration. Known as KardiaBand, the device that has been developed by AliveCor is an electrocardiogram reader which is capable of detecting atrial fibrillation and abnormal heart rhythm when paired with an app. AliveCor’s current chief executive officer is Vic Gundotra, a former boss of Google+.

The KardiaBand comes equipped with a sensor which when touched by a user gets the EKG reading in under half a minute. Users can choose whether the reading should be forwarded to a physician. KardiaBand also makes use of artificial intelligence to analyze as well as predict the heart rate of a user based on data obtained from both healthy and sick people.

Continuous monitoring

Portable EKG readers capable of working with smartphones have existed for almost as long as long as mobile devices and they have allowed users to check the electrical activity of their heart at will. The problem however has always been knowing the right time to get a reading. With the KardiaBand that issue is now solved.

“This is continuously monitoring your heart rate to let you know if something is potentially off track. That’s the big difference,” Eric Topol, Scripps Translational Science Institute’s director and a molecular medicine professor, said.

The KardiaBand is available at a price of $199 and users have to take up an AliveCor premium service subscription which costs an annual fee of $99. KardiaBand only works with Apple Watch Series 3 of which the lowest priced version, the non-cellular one, costs $329.

Apple Heart Study

KardiaBand’s approval by the U.S. Food and Drug Administration comes in the wake of Apple announcing a research initiative where an app known as Apple Heart Study was launched. The initiative aims at identifying users of the Apple Watch who might be suffering from atrial fibrillation and consequently in danger of getting a stroke.

A sensor attached to the Apple Watch collects signals from four different spots and this way it is able to detect how much blood is flowing via the wrist. That information is analyzed along with data coming from software algorithms in order to identify irregularities.