In October 2026, the KTU Biomedical Engineering Institute, in collaboration with research teams from Vilnius University and Taiwan, will launch “Trustworthy deep learning and diagnostic-grade wearable ECG for early detection of acute myocardial infarction (AMI-Sure)”, a research project funded by the Research Council of Lithuania.
The project “AMI-Sure” aims to develop a technology for early detection of heart attack at home. The project’s goal is to improve the diagnostic value of electrocardiograms (ECGs) recorded using a wrist-worn device and to develop a reliable deep learning algorithm for detecting heart attack.
Early detection of heart attack is very important, as every hour of treatment delay increases the risk of death. However, patients often wait 2–3 hours after the first symptoms appear before seeking medical help. One reason for this delay is the lack of simple and reliable diagnostic tools that can be used at home.
The “AMI-Sure” project will develop a wearable technology that allows users to record ECG signals similar to those of a standard 12-lead ECG with a single touch. The project will use personalized ECG reconstruction methods and explainable deep learning algorithms to improve the reliability of heart attack detection. The developed methods will be tested in a clinical study involving 300 participants.
Project Leader Dr. A. Petrėnas
According to the project leader, Dr. Andrius Petrėnas, “Although modern smartwatches allow users to record an ECG on their own, their diagnostic capabilities are still limited. In addition, AI-based algorithms for detecting heart attack often become less reliable when tested on data that were not used during training. Therefore, our goal is not only to improve the capabilities of wearable devices but also to make sure that the information they provide is reliable. We hope that, in the future, such technologies will help people recognize the signs of a heart attack earlier, seek medical help sooner, and reduce the number of serious complications and deaths.”
The project is funded by the Research Council of Lithuania (Agreement No. S-LT-TW-26-13). More information about the project is available here: AMI-Sure
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