Morphology based Cardiac Signal Processing

This research focuses on the electrocardiogram (ECG) which is a well-established and easy to obtain physiological signal of remarkable diagnostic power. It provides a wide spectrum of information regarding a patient's condition. Over the past few years, clinical studies revealed that even subtle ECG changes carry important information for disease detection in neurology as well as in intensive-care medicine. However, this clinically relevant information is often transient or masked by noise and therefore hard – if not even impossible – for the human observer to detect and interpret. In general, consistent interpretation of ECG phenomena is a difficult task due to inter-patient and inter-observer variability. This research aims to develop analysis tools tailored to an ageing population that provide reliable parameters and predictors for distinct diseases, thereby supporting practicing clinicians in their daily business.