Comparative Analysis of Heart Rate Variability for ECG Groups Based On Correlation Dimension

摘要

The beat-to-beat variation in Heart rate is termed as the Heart Rate Variability (HRV). HRV signal can be used as a reliable indicator of heart diseases. HRV is an important index to express the tensility and balance of the parasympathetic - sympathetic nerve, and it is valuable to diagnose heart and blood diseases in clinical diagnosis. This paper reports nonlinear analysis of ECG R-R interval time series obtained from healthy and Cardiovascular Groups i.e. Normal Sinus Rhythm (NSR) group, Stress Recognition in Automobile Drivers (SRAD) group, BIDMC Congestive Heart Failure Database (CHF) group, Long-term ST Database (ST) group & MIT-BIH Arrhythmia Database (Arrhythmia) group. HRV signal possessing nonlinear characteristic, the analysis of HRV signal can be made by nonlinear dynamic parameter, such as correlation dimension. This reports the Grassberger-Procaccia algorithm and its modified version, to reduce computation time in particular, to avoid dynamic correlation, and to determine the scaling region, correlation dimension of the HRV time series. Since the correlation dimension has the advantage of being straightforward and quickly calculated. NSR group, SRAD group, CHF group, ST group and Arrythmia group samples correlation dimension were calculated, and statistical results are compared. It is found that correlation dimensions of SRAD, CHF, ST and Arrhythmia groups are averagely less than NSR group.