Changing the Cardiac Care Paradigm
Arrhythmia Detection
AHA 2024: “An Innovative, Non-invasive, Credit-Card Sized Device for Ambulatory 12 Lead ECG Recording: First-In-Human Experience Compared to Standard 12 Lead ECG” (presented by Dr. Thomas Deering, Piedmont Healthcare)
Pilot data demonstrating similar performance between HeartBeam system and 12-lead ECGs for arrhythmia detection
Read MoreEHRA 2024: “Performance of a vectorcardiographic deep learning algorithm compared to single-lead and 12-lead ECG for atrial flutter detection: implications for wearable devices” (presented by Dr. Vivek Reddy, Mount Sinai Hospital)
Outperforms single-lead ECG in detecting atrial flutter
Read MoreHRS 2024: “Performance and Interoperability of a Vectorcardiogram Deep Learning Algorithm to Detect Atrial Flutter Compared to Electrocardiogram Analysis By Electrophysiologists” (presented by Dr. Joshua Lampert, Mount Sinai Hospital)
Outperforms expert panel of electrophysiologists in detecting atrial flutter
Read More12-lead synthesis software and HeartBeam AI are not cleared by the FDA. Not available for sale in the United States.
Heart Attack Detection
JACC Advances: “Coronary Artery Occlusion Detection Using 3-Lead ECG System Suitable for Credit Card-Size Personal Device Integration” (Shvilkin, et al, 2023)
Shows HeartBeam technology is comparable to 12-lead ECG in identifying coronary occlusions
Read MoreAHA 2024: Risk assessment for acute MI (presented by Dr. Alexei Shvilkin, Beth Israel Deaconess Medical Center)
Highlights potential of HeartBeam’s technology with a novel risk-assessment algorithm to evaluate chest pain remotely
Read MoreIschemia product not cleared by FDA. Not available for sale in the United States.
HeartBeam Technology Validation*
IEEE Access: “Accurate Reconstruction of the 12-Lead Electrocardiogram From a 3-Lead Electrocardiogram Measured by a Mobile Device” (Miletic, et al, 2024)
Validates synthesis of 12-lead ECG from HeartBeam’s vector-based approach using a personalized transformation matrix.
Read MoreIEEE EMB: “A Morphology-Preserving Algorithm for Denoising of EMG-Contaminated ECG Signals” (Atanasoski et al, 2024)
Validates HeartBeam’s method of removing noise from ECGs while preserving morphology.
Read MoreIEEE: “A Database of Simultaneously Recorded ECG Signals With and Without EMG Noise” (Atanasoski et al, 2023)
Validates HeartBeam’s novel acquisition method that allows for direct recording of ECG signals.
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