Digital health technologies for cardiac care are cropping everywhere, including Apple’s very own Apple Watch with ECG reading capability, but a Berkeley, California startup believes its product targets both consumers and clinicians effectively
Last week Eko Devices raised $20 million in a Series B funding round that will go toward its work on machine-learning algorithms that the company believes will offer early diagnosis of heart problems.
The algorithms are currently under review by the U.S. Food and Drug Administration, said Connor Landgraf, CEO of Eko. He is hoping for a decision by the end of the year.
“We would be one of the very first applications of a non-invasive, low-cost machine-learning tool,” he said, noting that the tool would be relatively easy for clinicians to use.“This isn’t some fancy pie-in-the-sky machine learning but is applicable on a day-to-day basis.”
The algorithms are designed to work in conjunction with the company’s software and digital devices, the Core Stethoscope and the Duo, a combined stethoscope and electrocardiogram reader, which can be used in both home and clinical settings. The software and devices are in use by tens of thousands of clinicians in the U.S. and Europe, Landgraf said, and can be bought directly from the company’s website.
Other companies are developing heart-monitoring software and hardware, as well as artificial intelligence applications to go along with them. They include San Francisco-based Qardio and Australia-based M3DICINE. Apple, meanwhile, has been touting the ECG reader on its watches.
But Landgraf said Eko’s devices and algorithms – and their ability to parse both electrical signals and the sounds of blood flow – would set the company apart, particularly in clinical usage. The data from Eko can go right to physicians, who can modify treatment plans in response, if necessary.
“The direct-to-consumer products haven’t yet closed that loop,” Landgraf said, adding: “Keeping the physician and the data and the patient connected through a software system like ours, we think, will be more impactful.”
The company also is planning to invest more in the clinical research it has been undertaking with academic partners like the Mayo Clinic in Rochester, Minnesota. Mayo and Eko are collaborating on an algorithm that would screen patients for what is known as low ejection fraction, a sign of a weak heart pump. The goal is earlier identification of the condition, which is a risk factor for heart failure.
In addition, Eko has been working with Northwestern Medicine’s Bluhm Cardiovascular Institute in Chicago to study the company’s technology in screening for valvular heart disease.
Doctors have long listened to the heart for signs of trouble. By adding machine-learning algorithms, Eko hopes to identify subtle signals that may be hard to pick up other than through expensive and time-consuming studies, Landgraf said.
“What this can open up is a massive new opportunity to help identify patients who might have heart failure or an inefficient heart pump with a non-invasive 15-minute test and ensure proper follow-up more quickly,” Landgraf said.