Processing EEG signals to detect intention of upper limb movement

Abstract

In the world there is a large number of people who have trouble performing movements that are simple for others, such as people who have suffered a stroke or have damage in the spinal cord. However, thanks to neuroscience, there is knowledge about the cognitive processes that occur in the brain and it is possible to help these people by using brain-computer interfaces. In this paper the movement of the arm of a healthy person is under research. Different processing methods and classifiers are studied in order to obtain the minimum false positive rate with the best true positive rate to detect the intention to make such movement in future real time tests. The ultimate goal is to use this system with an exoskeleton attached to the user arm. Thus, these kind of disabled people will perform movements on their own will by activating the exoskeleton joints. This system could be used in motor rehabilitation processes since it would allow the patient to recover the damaged communication channels of the brain or create new ones due to brain plasticity.