Measurements of Cardiovascular Signal Complexity for Advanced Clinical Applications

Over the last decades, there has been an increasing interest in the analysis of Heart Rate Variability (HRV). Many parameters were proposed to properly describe the complex systems controlling the heart rate, while involving neural mechanisms (through the Autonomic Nervous System), as well as mechanical and humoral factors. After a first effort to rationalize all these parameters in 1996 (the \u201cHRV Task Force\u201d), a second paper in 2015, reported the consensus reached on the critical review of the new methods. The latter tried in particular to address the clinical impact of the nonlinear techniques, considering only studies with sufficiently sized populations. In this chapter, we relax the constrain on the number of patients and try to identify all those techniques which resonated in the scientific community and were applied and studied more than others. To guide our analysis, we considered a different set of objective criteria, based mainly on the number of citations received. Our analysis show that all the parameters which were clinically relevant in the 2015 paper, proved also to have a significant impact in the methodological literature. However, other parameters received much more methodological interest than the clinical results they were capable to provide. Among these: several entropy measures and the metrics derived from nonlinear dynamical systems, multifractality and wavelets. The reasons of this lack of clinical results might be many, but the complexity of these techniques and the disconnection, which frequently happens between bioscientists/biomedical engineers and medical centers, are likely possible explanations