DissertationAmong the systems mentioned above, especially the cardiovascular system, whose complex behaviour is determined through many overlapping regulatory processes, is an ongoing researchtopic. An important section of this field comprises the interactions between the beat-to-beat intervals and the blood pressure, which on the one hand are at least known partially and on the other hand are controversially discussed.In this work, initially some existing coupling measures and their fields of application are introduced. One trait these measures have in common is the requirement of stationary time series to ensure their applicability. Therefore, in the course of this thesis a possibility to extend these measures is presented, which allows a coupling analysis with a high temporal resolution and thus also the analysis of transient, nonstationary events.The extension is based on the use of ensembles of time series and the calculation of the respective measures across these ensembles instead of across time. This allows for a temporal resolution of the same order of magnitude as the sampling rate in the original signal. The resolution only depends on the kind of coupling analysis method employed.The ensemble extension is applied to different coupling measures already successfully employed under difficult circumstances like high noise levels or short time series. For comparison, two simpler coupling measures are used. To begin with, the regarded tools are tested on various theoretical models and under different conditions. This is followed by a coupling analysis of cardiovascular time series recorded during transient events. The results on the one hand confirm topical study outcomes and on the other hand deliver new insights, which will allow to extend and improve cardiovascular system models in the future. Prediction methods based on these models will then be able to provide new diagnostic techniques and treatment procedures for cardiovascular diseases, thus contributing to health preservation in humans.