AliveCor hit a major turning point for its smartphone-based ECG technology with FDA clearance for a new algorithm that helps patients diagnose their own heart rhythms.
The new test uses AliveCor’s existing heart monitor to capture real-time heart rhythm readings via a mobile electrocardiogram system that snaps onto the back of the phone like a case. The new algorithm analyzes readings on the spot and tells patients if the system detects signs of atrial fibrillation.
Patients can take the readings to their doctors for confirmation or use AliveCor’s in-app ‘over-read’ service to request further review of their data. The new service will hit the market in September, according to a company announcement.
The latest FDA milestone is an important part of of AliveCor’s larger vision to turn data into insight by gathering more lifestyle and environmental information from patients as they take their heart rhythm readings.
"What nobody has been able to do up until now is to analyze whether the nature of the atrial fibrillation or the frequency of the atrial fibrillation can be related to certain circumstances, or does it represent a natural progression of this particular illness?" AliveCor CEO Euan Thomson told MassDevice.com in an in-depth interview earlier this year. "Do the characteristics of the atrial fibrillation and that change over time correspond to certain changes in the patient that should be monitored or should impact the type of treatment that they get? As we continue to develop this stream of data, what we will be able to do is to investigate and experiment with that type of concept – can we predict atrial fibrillation? Can we even, for example, in a patient whose ECG or a person or a consumer whose ECG is apparently normal, if we monitor that over a period of time can we spot characteristics that nobody has been able to see before and predict that atrial fibrillation is imminent and be more proactive in the ways in which they are treated and merged? Those are the long-term gains for a company of this sort, developing new insights from very large quantities of data."
