Systolic Complex

Systolic complex analysis focuses on understanding the heart's contraction phase, crucial for assessing cardiac function and informing diagnoses. Current research employs deep learning models, including neural networks and U-Net architectures, to analyze various cardiac signals like seismocardiograms and echocardiography data, aiming for automated and robust identification of systolic events and extraction of functional biomarkers. This work is significant for improving the accuracy and efficiency of cardiac assessments, potentially leading to better patient stratification and personalized treatment strategies in cardiology.