Heart sound is a kind of non-stationary and nonlinear signal with typical chaotic characteristics. As everyone knows, exercise and age can influence heart function, will they also influence the chaotic characteristics of heart sound? This problem is studied based on the correlation dimension and Kolmogorov entropy. Firstly, discuss calculation methods of correlation dimension and K entropy of heart sound signal. Secondly, introduce the experimental methods, and use a self-made wireless heart sound acquisition device to collect heart sound signals in different move status and at different ages. The effects of exercise on correlation dimension and K entropy were discussed in three status of rest, in and after exercise. Then carry out phase plane analysis of heart sound signals, and analyze change rules of correlation dimension of heart sound signals with aging. Finally, the prediction model of heart sound is proposed according to the relationship between age and correlation dimension. The results show that: (1) There were significant differences in correlation dimension and K entropy of heart sound signals under different move status. (2) Affected by cardiac inefficiency and pathological murmurs, correlation dimensions of heart sound decrease with the increases of age. Therefore, senescence is a process in which the chaotic characteristics of heart sounds gradually change to zero. (3) According to the prediction model of heart sounds, we can try to obtain heart sounds for many years to come, which can be used to assist in predicting the risk of human-related diseases in a certain sense.
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