Analysis of physiological networks from EEG and PPG signal analysis using causality measures in a decision making context.

Understanding the complexity of interactions within the human body through the analysis of physiological networks is important to understand their dynamics. The quantification of these interactions corresponds to the most important challenge, because they open possibilities for clinical applications (8), where the study of diseases related to these networks involved (brain-heart), understanding the functioning of the mind and the cardiovascular system in a decision making process, where new useful tools can be proposed to support the diagnosis or propose more specific and measurable treatments (18-20).
Another important aspect is the fusion of fields such as engineering, medicine and psychology, working together to generate new tools for this type of studies, which in recent years have allowed the interrelation of basic sciences such as biology and mathematics (8). Advances have already been obtained within the biomedical engineering research group, where they have been applied to signals previously from PSG recordings, which have allowed the mastery of the causality determination technique (21). Thus, the interdisciplinary teamwork will allow a better use of these techniques in the proposed decision making context.

Physiological networks, biosignal analysis, Granger Causality, Transfer, Transfer, Entropy, Biosignal Processing, Decision Making