Motor imagery based brain-computer interface (MI-BCI) is one of the most common paradigms utilized in neurofeedback training (NFT) for rehabilitation engineering. Specifically, finding an appropriate feedback protocol is significantly important to improve the effectiveness of the motor training system. To this end, we investigated the electroencephalography(EEG) oscillatory patterns measured by event-related desynchronization (ERD) when sixteen participants accepted the visual and proprioceptive stimulation achieving the kinematic hand grasping movements at three different speeds (i.e. 1/3 Hz, 2/3 Hz and 1 Hz). The EEG results indicated that the ERD patterns showed no significant difference in sensorimotor cortex (i.e. C3 and FC3 channels) by comparing the three conditions. Nevertheless, the 2/3 Hz stimulation speed could achieve a significantly better classification performance than the other two conditions across all participants. Therefore, the visual and proprioceptive electrical stimulation achieving the kinematic hand grasping at 2/3 Hz speed might provide an available approach for the online MI-BCI system based NFT system in the future.