Implantable loop recorders play a significant role in detecting atrial fibrillation. But many of the technologies yield false positives – which can be burdensome for clinicians who need to sift through the noise to get a proper diagnosis. 

Implicity is employing the power of artificial intelligence to help analyze ECG data from ILR technology in hopes of helping electrophysiologists and their teams avoid wasting time reviewing these false positives.

The Cambridge, MA-based company won FDA clearance for a medical algorithm that can interpret Medtronic’s ILR ECG data. Implicity said Medtronic recently announced an AI algorithm to address the false positive issue, but it is only for use with the LINQ II model. Implicity's solution is compatible with all previous Medtronic models (i.e. Reveal LINQ, Reveal XT, and Reveal DX), which are implanted in the majority of patients.   

“Most of the devices have a lot of high false positives because they don’t want to miss an arrythmia – which makes sense,” Arnaud Rosier, CEO and founder of Implicity told MD+DI. “So, you have false positive episodes over things that don’t matter.”

He added, “We use AI in a way that it can assess how to diagnose the episodes. We used all of the cloud computing power that we had  … in order to reprocess the signals that we’re getting from the device in the cloud.”

Implicity's ILR ECG Analyzer applies AI to the heart rhythm data collected by the specified Medtronic models. The digital medical device will be integrated into Implicity's cardiac remote monitoring platform to deliver unique value to electrophysiology teams by laying in additional signal processing and analysis to improve the accuracy of irregular heartbeat detection. The information is then automatically classified to help prioritize true events (i.e., those that warrant further action) – thus providing more meaningful and efficient event management.

To date, the technology has seen success.

A recent study published in the European Heart Journal demonstrated Implicity's novel algorithm reduced the number of false-positive episodes by 79% when analyzing ECG recordings from patients implanted with Medtronic ILRs while maintaining 99% sensitivity.