The present disclosure relates to the field of computer technologies, and provides a brainprint signal recognition method and a terminal device. The method includes: acquiring a brainprint signal to be classified, mapping the brainprint signal to be classified into a vector space, and determining a coefficient vector of the brainprint signal to be classified； acquiring class centers and distance thresholds of respective existing classes in the vector space, where each of the existing classes corresponds to a brainprint signal set； and determining, according to the coefficient vector of the brainprint signal to be classified and the class centers and the distance thresholds of the respective existing classes, the class to which the brainprint signal to be classified belongs.
