Clinical Research Directory

DevelopmentandApplication of a Single Feature Recognition Model for Heart Failure Based onArtificial Intelligence Optimization Algorithms

The goal of this observational study is to develop and validate a single-feature artificial intelligence algorithm based on data from a wearable ECG patch in patients with heart failure (HF). The main question it aims to answer is: Does the algorithm, using synchronized ECG and accelerometer signals from the patch, achieve accurate detection of heart sounds (S1, S2, and in some patients S3, S4) compared to the Eko CORE500 digital stethoscope in patients with acute exacerbation of HF? Participants with confirmed HF (NYHA class II-IV) will undergo two 2-minute sessions of simultaneous ECG patch and digital stethoscope recordings, followed by standard 12-lead ECG. Data will be used for algorithm training and validation, with the primary endpoint being the sensitivity and specificity of heart sound detection against the reference device.