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Healthcare Looks to Digital Health Tools to Measure Heart Health

The Mayo Clinic announces a 10-year deal with BioSig Technologies to develop mHealth technology that monitors heart rate and rhythm. Meanwhile, AliveCor is expanding its digital health platform to include AI capabilities.

Source: ThinkStock

- Wearable mHealth technology that helps both doctors and patients monitor heart rate is in the spotlight these days.

AliveCor, whose Kardia Mobile was among the first ECG wearables on the market, has announced the release of Kardia Pro, a platform that adds artificial intelligence capabilities to help doctors and patients identify atrial fibrillation, the most common cardiac arrhythmia and an indicator of potential stroke. The San Francisco-based company also announced a Series D funding round of $30 million, led by Omron Healthcare with participation from the Mayo Clinic.

Separately, the Mayo Clinic announced a 10-year partnership with BioSig Technologies, a Minneapolis-based medical device company looking to develop its PURE EP cardiac signal acquisition and display platform for commercial use.

BioSig has been working to create a digital health device that can help electrophysiologists diagnose and treat patients with abnormal heart rates and rhythms, including those suffering from atrial fibrillation and ventricular tachycardia. The company has tested its platform at UCLA’s Cardiac Arrhythmia Center as well as the Mayo Clinic and New York’s Mount Sinai Hospital.

Company officials say the market for market for physiologic signal processing will grow as healthcare providers look for better platforms to monitor patients away from the hospital bed, or doctor’s office.

AliveCor, whose Kardia Mobile enables doctors and patients to track heart activity with a wearable and accompanying phone app, is putting its weight behind an AI platform that’s designed to take a patient’s weight, blood pressure, activity and ECG history and create a unique profile. Mobile ECGs are then matched against that profile, enabling patients and their doctors to spot anomalies earlier.

“During the first month of usage of Kardia Mobile, we learn about a user’s individualized heart profile,” says AliveCor’s CEO, Vic Gundotra. “Your personalized heart profile can be used for two benefits. First, it helps keep the data clean. If a doctor is monitoring your health using Kardia Pro, he or she can be more confident that the data he/she is reviewing is truly her patient’s and not someone else's. Second, and even more exciting, is that in the future, a heart profile may be able to find, and flag to your doctor, important changes in your ECG.”

"These are the kinds of tools that in the future no cardiologist will want to not practice with," Gundotra adds. "AI will supplement a cardiologist’s service, really being able to provide a higher level of service to the patient."

Artificial intelligence and machine learning are making their way quickly into the healthcare space, led by tech giants like Microsoft and IBM, whose Watson Health unit is partnering with health systems and mHealth companies across the globe. In a recent interview, Morgan Reed, executive director of the Washington D.C.-based Connected Health Initiative, said he originally thought healthcare would adopt AI five or ten years down the road.

“The speed that AI is getting into healthcare is surprising,” he said. “It’s having an effect on decision support now.”

“It’s (advancing) personalized healthcare,” says Kyu Rhee, MD, MPP, IBM Watson Health’s chief health officer. “The potential of mHealth in empowering individuals and promoting populations is enormous.”

Aside from working with health systems on cardiac care platforms, one of Watson’s more notable partnership is with Medtronic. The Ireland-based medical device company is embedding AI in its diabetes mHealth platform to help patients and their doctors manage blood glucose levels and even spot a potentially fatal instance of hypoglycemia before it happens.

“Health and healthcare are becoming much more person- and consumer-centric,” Rhee added. Watson is able to take that data” and create “nudges” that push the individual toward a better health outcome, all while the care team is collecting that data and creating an overall health management plan.

Gundotra sees those capabilities being applied to patients at risk of atrial fibrillation, who are five times more likely to suffer a stroke.

“The ECG holds a vast amount of information about a person's overall health, and applying machine learning to millions of ECG recordings is an important enhancement to traditional ECG analysis,” he says. “We look forward to continuing to apply deep machine learning techniques to uncover hidden physiological signals in ECGs to improve heart and overall human health.”

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