Brain-computer interface (BCI) based on motor imagery (MI) has been applied to the plasticity rehabilitation of limb motor function in recent years. Visual assistant stimulus can improve the classification performance of MI-BCI. However, for users with impaired visual system, visual assistant stimulus cannot be used. Therefore, this paper designs ASMI-BCI based on auditory assistant stimulus. It has been found that dynamic acoustic assistant stimulus could improve the excitability of motor related cortex, and enhanced the separability features of related frequency bands. The average classification results of the three experimental paradigms (C-SW, CDA, C-DV ) for 10 college students (5 males and 5 females, with an average age of 22. 6 years old) showed that the classification accuracy of C-SW paradigm was the lowest, followed by C-DA, and the accuracy of C-DV paradigm was the highest. The optimal classification accuracy of the auditory assistant stimulus paradigm was 76. 03% and the average classification accuracy was significantly improved by 8. 83% compared with the traditional MI-BCI paradigm. For 60% of the subjects, the classification accuracy of this paradigm can reach higher than 70%. The dynamic auditory assistant stimulus paradigm can provide a new pattern and method of feature modulation and BCI performance enhancement for patients with visual impairment.