Using dimensional analysis, we demonstrate that it is possible to quantify changes in the topological structure of cardiac dynamics over long periods of time. A method was developed to calculate a dimension-like measure (referred to here as apparent dimension) from a correlation algorithm within a data window of 500 heart beats which is moved in equidistant steps over the time series of the RR intervals over 24 hours. The correspondence between the apparent dimension and the correlation dimension was tested using artificial data sequences. Furthermore 24 hour electrocardiographic recordings of two healthy subjects and of a patient with acute myocardial infarction were examined. The reliability of the analysis could be demonstrated and changes in dimension reflecting physiological as well as pathophysiological changes were observed.