Implicit and explicit model-based signal processing for the analysis of short-term cardiovascular interactions

The paper stresses the importance of model-based signal processing in the analysis of the cardiovascular regulation mechanisms. It is remarked that even traditional signal processing implicitly assumes a model and interprets data according to it. Therefore, traditional signal processing is here referred to as implicit model-based signal processing in contrast with explicit model-based signal processing directly stemming from modeling considerations. The paper points out the advantages that can be achieved by rendering explicit the underlying model structure when it is implicit and by jointly applying implicit and explicit model-based signal processing approaches when dealing with complex, interacting, closed-loop biomedical systems. These advantages are rendered practical over several examples derived from the study of the short-term cardiovascular regulation performed by the autonomic nervous system. Keywords—Autonomic nervous system, biomedical signal processing, cardiovascular control, cardiovascular variability, physiological modeling