Cardiac Signal

Cardiac signal analysis focuses on extracting meaningful information from heart-related signals like electrocardiograms (ECGs) for diagnostic and biometric purposes. Current research emphasizes developing robust deep learning models, including convolutional neural networks and transformers, to handle the inherent variability and asynchronous nature of these signals, often incorporating multi-view fusion techniques and addressing issues like missing data and signal irregularity. These advancements are improving the accuracy of automated disease prognosis, patient identification in healthcare systems, and remote physiological monitoring, with applications ranging from Huntington's disease detection to contactless monitoring in neonatal intensive care.