The invention relates to an extraction method of EEG characteristics of imagination of single-side limb motion in a brain-computer interface device. The classification of the characteristics of imagination of single-side motion has stronger pertinence, which is decided by the nature of excluding same tasks and extracting different tasks of a CSP space filtering method; at the same time, due to the combination of CSP algorithm and FDA characteristics extraction, the dimension of input vectors is reduced, and the marketability of a classifier is enhanced; therefore, the classification accuracy rate is enhanced to a certain extent; adopting Fisher Differentiation and Analysis (FDA), ten-dimension input vector v1, v2(v1 is four-dimension, and v2 is six-dimension) are reduced into two one-dimension input vectors f1, f2, and then classification is carried out by a support vector machine, thereby not only improving classification accuracy rate, but also avoiding the problem of dimension disaster caused by too high dimension ,as well as being beneficial to the popularization of the classifier.