Heart sound is an importa nt physiological signal, and it contains a large number of physiological and pat hological information. According to the characteristics of heart sound, the symb ol entropy based on probability distribution is proposed. The algorithm makes a breakthrough at linear constraints. On the one hand, it distributes more symbols for the region where the amplitude distribution of the first heart is dense and distributes relatively less symbols for the sparse region, so as to achieve the reduction of redundancy of data; On the other hand, it uses an adaptive method t o determine the size of the symbol set. Then the symbol entropy becomes more sen sitive to the changes of the heart sound signal and can rapidly capture the no nlinear abnormal state of heart signal. Thus the algorithm can make little or no impact of the non-stationary mutation interference and the sequence probabilit y distribution on the entropy. Simulation results show that the algorithm not onl y has significant feasibility and effectiveness but also provides a new way for the rapid diagnosis of heart failure.