To find out how prediction of motor intention in the posterior parietal cortex(PPC) correlates with motor imagery EEG signal, this study joints movement-related potentials(MRPs) and the ERS/ERD features of mu/beta rhythm, in the first instance, wavelet packet decomposition(WPD) is proposed to reconstruct characteristic frequency band for feature vector of wavelet packet decomposition coefficients; moreover, spatial features vectors are extracted by common spatial patterns(CSP); in the end, support vector machine(SVM) as classifier is utilized to serve for predicting motor intention．Combining MRPs and mu/beta rhythm during motor imagery EEG signal, the classification accuracy is up to 85%. The result indicates that: 1) the brain nerve mechanism of movement readiness and movement planning stages can be characterized by MRPs; 2) the ERS/ERD features of mu/beta rhythm on low frequency components below 10Hz carry information about intended movement direction. And the conclusions further offer a technological support for predicting meticulous movement intention including direction, speed and so on of movement parameters.