HeartBeam Partners with Mount Sinai to Develop AI-Powered Home Cardiac Monitoring Platform
Key Insights
HeartBeam and Mount Sinai (search)'s Icahn School of Medicine (search) announced a strategic collaboration to develop next-generation AI-ECG algorithms for home-based cardiac monitoring.
The partnership leverages HeartBeam's patented 3D ECG technology that captures 12-lead ECG data from patients anywhere, extending cardiac assessment beyond traditional clinical settings.
The collaboration aims to create personalized AI algorithms for wellness applications and clinical assessments, including heart attack risk evaluation, using longitudinal real-world ECG data.
HeartBeam, Inc. (NASDAQ: BEAT) has announced a strategic collaboration with the Icahn School of Medicine (search) at Mount Sinai (search) to accelerate development of AI-powered cardiac monitoring technology that brings clinical-grade heart assessment into patients' homes. The partnership combines HeartBeam's patented 3D ECG platform with Mount Sinai's clinical expertise and AI capabilities to develop next-generation algorithms for cardiac care.
Revolutionary 3D ECG Technology Platform
HeartBeam's platform represents a breakthrough in cardiac monitoring by capturing the heart's electrical activity from three non-coplanar dimensions without cables. The technology synthesizes these signals into a 12-lead ECG, making it the only platform capable of collecting 12-lead ECG data from patients anytime, anywhere, over time. This capability extends cardiac assessment beyond traditional clinical settings into real-world environments.
The company's 3D ECG technology received FDA clearance for arrhythmia assessment in December 2024, with the 12-Lead ECG synthesis software cleared in December 2025. HeartBeam holds over 20 issued patents related to its technology enablement.
AI-Driven Personalized Cardiac Intelligence
The collaboration creates a foundation for developing increasingly personalized algorithms by leveraging HeartBeam's ability to generate longitudinal, high-fidelity synthesized 12-lead ECG datasets from patients in home settings—data that has historically been inaccessible to AI development. This approach enables 12-lead ECG assessments in real-world settings, supporting both wellness use cases and clinically relevant assessments, such as heart attack risk evaluation.
"We believe expanding access to 12-lead ECG data assessment beyond the clinic is one of the biggest opportunities," said Robert Eno, Chief Executive Officer of HeartBeam. "By pairing our ability to gather high-fidelity real-world ECG data with Mount Sinai (search)'s extensive clinical data resources and AI expertise, we are creating a differentiated cardiac intelligence engine that can scale beyond traditional care settings and broaden the reach of predictive cardiology."
Clinical Leadership and Scientific Expertise
Under the collaboration, HeartBeam's in-house AI team led by Lance Myers, PhD, a leading authority on AI applications in biosensor technologies, will work closely with Mount Sinai (search) researchers to develop, train and validate advanced AI-ECG algorithms for deployment on the HeartBeam platform.
The Mount Sinai (search) team includes Joshua Lampert, MD, FACC, a pioneer in AI-ECG and cardiovascular deep learning research; Vivek Reddy, MD, an internationally renowned electrophysiologist and Director of Cardiac Arrhythmia Services for Mount Sinai Health System; and Girish N. Nadkarni, MD, MPH, Chief AI Officer of the Mount Sinai Health System and Chair of the Windreich Department of Artificial Intelligence and Human Health.
Addressing Current AI-ECG Limitations
Dr. Lampert highlighted the collaboration's potential to overcome existing challenges in the field: "While AI-ECG has rapidly progressed as a field over recent years, there is room for improvement in the portability and scalability of such algorithms beyond acquisition devices that require complex multi-electrode systems. Additionally, current approaches struggle to leverage deep learning inference opportunities outside of traditional health care settings, which is where dynamic changes to cardiovascular health first start before patients present for care."
The partnership addresses these limitations by combining deep learning tools with the ability to record full 3-dimensional cardiac electrical activity without cables, providing clinically meaningful and operationally pragmatic models at scale regardless of environment.
Expanding Clinical Applications
"Heart disease doesn't only show up during a brief visit to the clinic," said Dr. Nadkarni. "This collaboration gives us an opportunity to bring powerful clinical-grade heart monitoring into patients' daily lives. By combining advanced AI with HeartBeam's ability to capture full 12-lead ECG signals from home over time, we can study the heart in ways that simply haven't been possible before—helping clinicians detect risk earlier and guide care more precisely."
The collaboration aims to develop AI models that may include patient-relevant wellness insights, condition-focused assessments, and applications for chronic condition management. By enabling AI models to operate on longitudinal, real-world synthesized 12-lead ECG data rather than isolated clinical snapshots, the partnership has the potential to significantly expand the addressable market for AI-driven cardiac monitoring.
Strategic Market Positioning
The collaboration positions HeartBeam to expand from symptom-based cardiac rhythm monitoring into AI-enabled disease assessment and management. Dr. Reddy noted that the partnership "addresses an important need by leveraging deep learning and 3-dimensional waveform data for scalable diagnostic and predictive purposes, allowing insights beyond even expert human ability."
The combination of HeartBeam's continuously expanding dataset and Mount Sinai (search)'s clinically annotated 12-lead ECG data is expected to accelerate the training and validation of various AI models, creating a data engine that supports the development of increasingly personalized algorithms. This approach could unlock new opportunities in preventive cardiology, chronic disease management, and remote patient monitoring, further reinforcing HeartBeam's position as a leader in cardiac intelligence platforms.