Systolic and Diastolic Time Interval Variability Analysis and Their Relations with Heart Rate Variability
Heart rate variability (HRV) has been proved an efficient measure for evaluating the function of cardiovascular system under the autonomic nerve control. In fact, HRV includes two types of variability: systolic time interval variability (STIV) and diastolic time interval variability (DTIV). Towards a better understanding of STIV and DTIV, this study uses the methods of spectrum analysis with autoregressive (AR) model and sample entropy (SampEn) analysis to compare the differences of STIV, DTIV and HRV under three physiological states: rest, deep breathing, and immediately after exercise. The experiment results show that: 1) As the existence of HRV, systolic time interval (STI) and diastolic time interval (DTI) sequences still have the variability (i.e., STIV and DTIV); 2) DTIV is more obvious than STIV and it has a better ability to follow the change of HRV; 3) from the state of rest to deep breathing, LF powers in the power spectrum density (PSD) of HRV and DTIV are enhanced obviously, while both LF and HF powers in the PSD of STIV are enhanced; 4) after exercise, the SampEn of STIV, DTIV, and HRV all increase obviously because the exercise evokes the change of cardiovascular nonlinear dynamics.
heart rate variability (HRV) systolic time interval variability (STIV) diastolic time interval variability (DTIV) autoregressive (AR) model sample entropy (SampEn)
Chengyu Liu Changchun Liu Liping Li Qingguang Zhang Bin Li
School of Control Science and Engineering Shandong University Jinan,P.R.China
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）