Dynamics of complex systems inferred from multivariate time series

Abstract

In the past decades, society and science have seen an increased popularity of big data, with unsurpassed volumes, resolutions and quality. Especially in medicine there is an increasing role for big data to infer a patients health, his/her functioning, and predicting the response to interventions. These data invite on the one hand for the development of new analysis tools such as machine learning and Artificial Intelligence, but on the other hand for re-investigation of analysis tools that previously were limited by data availability. In this study we investigate two of these formerly proposed analysis tools that have a basis in complex systems dynamics: Dynamical Indicators Of Resilience (DIORs) and complexity quantification tools. We explore their similarities and differences and demonstrate how they both have specific roles when studying the human as a complex dynamical system.