EEG-based brain-controlled lower extremity exoskeleton rehabilitation robot

Brain-computer interfaces (BCIs), based on electroencephalography (EEG), have been proved to play an important role in motor rehabilitation, motor replacement, prosthesis control, and assistive technologies. BCIs can classify EEG signals and translate the brain activities into useful commands for external devices. This paper presents a brain-controlled lower extremity exoskeleton rehabilitation robot with a motor-imagery (MI)-based BCI to enhance active rehabilitation participation. Four healthy individuals performed MI tasks of left and right hand movements to control the speed of gait training. The proposed paradigm could be further implemented by adding motor tasks and promoting MI classification accuracy.