Viable usage of Brain-Computer Interface (BCI) in real-time applications significantly relies on the pre-processing techniques applied on the detected electroencephalography (EEG) signals. In EEG, sensorimotor (SMR)/oscillatory signals, such as mu and beta rhythm based BCIs, can be used to restore motor function by neuro-plasticity applied to re-establish normal brain function. This study is based on the evaluation of the foot motor execution (ME) and motor imagery (MI), in order to design a BCI neurorehabilitation system. Because foot ME and MI reflect the user's physical and imagination state of foot movement respectively, in order to be used as control signals, their appropriate translation is the basic challenge. This paper mainly focuses on the quantification and investigation of mu-beta event-related desynchronization (ERD) and event-related synchronization (ERS), for inter and intra-subject variability, making use of the available design tools in open-source platforms such as the OpenViBE software. Results show that the frequency of the most reactive components for mu was 8.8±0.5 Hz and 21.3±0.4 Hz for beta. Interestingly a contralateral dominance was visible at electrode position C3 during right foot ME/MI tasks. The results have enabled the implementation of a good platform for left-right foot ME/MI discrimination based BCI applications.