Model-free causality analysis of cardiovascular variability detects the amelioration of autonomic control in Parkinson's disease patients undergoing mechanical stimulation.

We tested the hypothesis that causality analysis, applied to the spontaneous beat-to-beat variability of heart period (HP) and systolic arterial pressure (SAP), can identify the improvement of autonomic control linked to plantar mechanical stimulation in patients with Parkinson's disease (PD). A causality index, measuring the strength of the association from SAP to HP variability, and derived according to the Granger paradigm (i.e.

Entropy-based complexity of the cardiovascular control in Parkinson disease: comparison between binning and k-nearest-neighbor approaches.

Entropy-based approaches are frequently used to quantify complexity of short-term cardiovascular control from spontaneous beat-to-beat variability of heart period (HP) and systolic arterial pressure (SAP). Among these tools the ones optimizing a critical parameter such as the pattern length are receiving more and more attention. This study compares two entropy-based techniques for the quantification of complexity making use of completely different strategies to optimize the pattern length.