Assessing Cardiovascular Function Status with Non-linear Indexes from HRV of Exercise Testing

The purpose of this paper is to study the method to assess function status of cardiovascular system effectively in order to guide prevention and protection. In this study an exercise testing was performed in two groups. 60 elder hypertensives were chosen as a group at relative worse healthy status, and 60 young healthy subjects were chosen as a group at relative good healthy status. By discrete wavelet transform (DWT), exercise heart rate variability (EHRV) was obtained from the primary ECG recorded in exercise testing. Five groups of non-linear indexes in pre exercise stage (PES), after exercise stage (AES) and whole stage (WS) were extracted from EHRV, respectively. They were appropriate entropy, relative complexity, and other three parameters extracted from Poincare dispersed-dot Plot. Discriminant analysis was used to classify two testing groups. Statistical analysis indicates that nine indexes were significantly different between these two groups. A discriminant formula was used to classify the two groups and the classification rate was up to 85%.