Abstract:

Single variability can not fully reflect the function of cardiovascular system. To overcome this problem, a new variability index, Associated Variability (AV) is proposed. This index is obtained from the weighted summation of Heart Rate Variability (HRV), Pulse Transit Time Variability (PTTV) and Electromechanical Delay Variability (EMDV), which are calculated by the sample entropy algorithm and the weights are determined by the method of analytic hierarchy process. Then, Group Distinction Measure (GDM) is defined. Experiments on heart disease group (25 subjects) and healthy group (35 subjects) show that the GDM values of HRV, PTTV and EMDV are all larger than 1, while that of AV is less than 1, which indicates that AV can fully distinguish the heart disease group from the healthy group. Results show that AV can reflect the function of cardiovascular system more completely than any single index, such as HRV, PTTV or EMDV.

Key words: computer application, associated variability, heart rate variability, sample entropy, group distinction measure