Stroke, cerebrovascular accidents and spinal cord injuries are some of the causes of motor impairment associated with the neural system. These disabilities carry out a lower life quality for non able-bodied people, due to the interruption of the sensory and motor connections, and a deficient gait capability. Recently, there have appeared new exoskeletons to be used in rehabilitation therapies. The use of these robotic systems in combination of brain-machine interfaces (BMI), which decode the gait will of the patient through the analysis of his electroencephalographic (EEG) signals, can help the rehabilitation therapies due to the improvement in neural plasticity. However, there are still difficulties for its extended use. First, algorithms need to improve their accuracy which makes necessary the development of more robust and reliable ones. Second, these robotic devices have usually a high cost, over 60.000€, making necessary the look for alternative options at a lower cost.
This new project will develop a new hybrid BMI that will improve previous researches based in motor imagery combining the attention level to gait of the user. The developed BMI will work in real-time with lower-limb exoskeletons and in virtual reality environments associated with a treadmill.
This BMI will improve the cognitive implication of impaired people improving the neural plasticity in future rehabilitation therapies. The comparison of the results with the ones using a virtual reality environment with a treadmill will allow to validate this alternative approach as a lower cost possibility.