SBIR/STTR Research Award
Saving Airmen by identifying Hidden Features in ECGs
Award amount
$109,941Program and phase
STTR · Phase IAward year
2025Award details
- Awarding agency
- Department of Defense
- Branch
- Air Force
- Recipient company
- Ainthoven, Inc.
- Proposal award date
- 2025-02-06
- Contract end date
- 2025-05-06
- UEI
- L2EQJ25PLC91
- Solicitation number
- X24.E
- Topic code
- AFX24E-TPCSO1
Research abstract
For this effort, Ainthoven and the University of Washington will explore if the team can find hidden features in otherwise normal electrocardiograms (ECGs) of hidden hypertrophic cardiomyopathy (HCM) and/or issues that lead to Sudden Cardiac Arrest (SCA). Ainthoven will examine our AI ECG technology can be developed to adjust and improve current ECG interpretation approaches by identifying features that are currently “hidden” (i.e., unknown) to humans in the ECG data.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- Artificial Intelligence Computer Vision and Object Detection in Full Motion Video in support of High Value Target Dynamic Targeting
- Identification and classification of small-UAS in the msec range
- Project ARES (Advanced Reconfigurable & Evolving Swarm) A Quantum-Secure Generative AI for Robust and Adaptive Drone Swarms
- Autonomous Robotic Trimming with Precision Operations for Base Maintenance
- Orbital Staging of Assets
Research funding history
2 SBIR/STTR records share this UEI (2024–2025). Reported award amounts total $184,854. Reported amounts are not federal obligations.
Phases: Phase I
Agencies: Department of Defense