The invention relates to a multi-class motor imagery brain electrical signal classification method based on phase synchronization. According to the method, firstly, phase synchronization features of a training sample and a test sample are calculated respectively through a phase locking value; secondly, correlation coefficients of the training sample and the test sample are calculated and arrayed from large to small after an average value is removed and an absolute value is obtained; thirdly, brain electrical signals are roughly classified according to the arrayed correlation coefficients, and then disaggregated classification is conducted according to the brain electrical signals which are roughly classified, wherein the process is involved in a shared airspace mode feature extraction method and a linear discriminant analysis and classification method. The method comprises the steps of brain electrical signal collection, data pre-processing, filtering, calculation of the correlation coefficients of the phase synchronization features, feature extraction and classification and classification accuracy calculation. Classification results show that by the adoption of the brain electrical signal classification method based on phase synchronization, the classification results are good, the rough class where the test sample belongs can be efficiently and accurately determined through brain electrical signal rough classification based on phase synchronization, and the calculated amount is reduced.