Large-Scale Dimension Densities for Heart Rate Variability Analysis

摘要

We analyse the heart rate variability data (HRV) using the concept of large-scale dimension densities (LAS-DID). This method enables to analyse very short and non-stationary data, such as HRV, and, hence, also short parts of the data and to look for differences between day and night. The circadian changes in the dimension density enable to an almost completely distinction between real data and computer generated data from CiC 2002 challenge using only one parameter. Furthermore, we analyse the data of 15 patients with atrial fibrillation (AF), 15 patients with congestive heart failure (CHF), 15 elderly healthy subjects (EH) as well as 18 young and healthy persons (YH). With our method we are able to separate completely the AF group from the others and the CHF patients show significant differences to the young and elderly healthy volunteers.