A short, easy-to-capture Lead I ECG, read by purpose-built AI models. Each has been developed based on over a decade of experience, a proprietary corpus of physician-annotated ECG data, and multiple clinical research partnerships.
Diagram: a single ECG waveform branching into four labeled applications — heart failure risk, atrial fibrillation risk, stress, and ECG authentication.
Heart failure risk identification and atrial fibrillation identification are both trained to identify heart abnormalities from ECG.
ECG Authentication and Stress Index apply that same single-lead ECG to entirely different purposes, from identity to stress.
A software-only assessment of heart-failure risk from a single Lead I ECG, for early identification in clinic and ongoing monitoring. Designed to help identify heart-failure risk independent of ejection fraction, including HFpEF.
Extending single-lead ECG analysis into atrial fibrillation.
Research pipeline
To analyze a Lead I ECG reliably, we evaluate and reduce noise with proprietary filters before it reaches the AI.
IP
Our information-processing technology for analyzing biological signals such as the ECG is protected by multiple granted patents in Japan and other countries.
Patent claims describe the scope of the underlying technology and intellectual property rights, and are separate from the approved or certified intended use of any specific product.
Covers a technology that combines a Lead I ECG with additional inputs such as heart rate and blood pressure to assess heart-failure risk.
Covers a proprietary method for quantifying heart-failure risk as a numeric score.
Covers risk assessment for HFpEF (heart failure with preserved ejection fraction).
Covers a machine-learning method for detecting atrial fibrillation from segmented ECG waveform data.
Covers a system that authenticates individuals from their unique ECG waveform characteristics, developed with the University of Aizu.
We welcome inquiries from clinicians, researchers, investors, and potential partners.