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Revealing the Dynamic Correlation between Cardiac and Respiratory Hemodynamic Signals Using Time-Dependent Panel Co- Integration Analysis

Samir Ghouali, Mohammed Feham, Yassine Zakarya Ghouali

Panel Co-integration is one of the most popular methods to reveal and evaluate the influence and the interactions that may exist between long-term variables; Co-integration is used in different field and enjoying unprecedented popularity due reliability, clarity and robustness. In this article, we conducted an investigation using very powerful mathematical model to verify if a long-term relationship exists between Cardiorespiratory hemodynamic signals, the methodology we applied in this paper is mainly based on four basic parts, in first part we applied unit root tests to assess the stationarity of series, the second step is to apply the test of Co-integration model and quantify this long-term relationship. Finally we applied the Granger causality tests to the entire panel that consists of 186 patients taken from Montreal Hospital / General MF (Massachusetts General Hospital / Marquette Foundation) database. The results found in this study show the long-term interaction between the Cardiorespiratory hemodynamic signals, and reveals how the understanding of these interactions can help the doctors to understand the risks that may exist between these interactions. The originality of this article is the number of variables incorporated in our model study. Unlike the majority of studies that are conducted with only two variables, our study is specified by its multidimensionality. The main advantage of a multidimensional and multivariate model is to solve a multitude of problemsthatprevent doctors to treat the patients betterandis not the case for studies in two dimensions.