The National Institutes of Health’s (NIH) Department of Health and Human Services (HHS) awarded the grant. The grant will fund the development of a machine learning algorithm, according to a news release.
Eko said the algorithm detects and stratifies pulmonary hypertension (PH). It uses phonocardiogram (PCG) and electrocardiogram (ECG) data from Eko’s smart stethoscopes. To address challenges of ECG-based AI models for detecting PH, Eko partnered with Lifespan Health System’s Cardiovascular Institute.
The partnership collects real-world PCG and ECG data using the Eko Duo ECG + digital stethoscope. Eko plans to use the data to develop an algorithm that can detect PH and stratify its severity. Early identification can diagnose PH earlier and more accurately, leading to potentially life-saving interventions.
“The major goal of this study is to determine whether an Eko algorithm based on phonocardiography coupled with electrocardiography can identify the presence and severity of pulmonary hypertension when compared to the current gold standard,” said Dr. Gaurav Choudhary, principal investigator and Ruth and Paul Levinger professor of cardiology and director of cardiovascular research at the Alpert Medical School of Brown University and Lifespan Cardiovascular Institute. “This machine learning algorithm has the potential to be a low cost, easily implementable, and sustainable medical technology that assists healthcare professionals in identifying more patients with pulmonary hypertension.”
NIH backs Eko again
The funding marks the fourth SBIR grant from the NIH for Eko, bringing its total NIH funding to $6 million. The company picked up a $2.7 million grant in July 2020 to validate heart disease detection algorithms. That grant contributed to the FDA clearance Eko garnered in July of this year.
“This SBIR grant is a testament to our focus on developing pioneering AI for early detection and management of cardiopulmonary diseases,” said Connor Landgraf, co-founder & CEO of Eko. “Early detection and intervention play a critical role in preventing the progression of heart disease. Our focus is to make AI-powered tools cost-effective, easily accessible, and scalable that support clinical decision-making, so millions of patients will get information sooner that could extend their lives. This is how we change the standard of cardiac care.”
