Control signal for a mechatronic hand orthosis aimed for neurorehabilitation

Individuals with stroke and other central nervous damage, which may cause paresis, are unable to move their affected limb or the movements are inefficient and clumsy. Brain-computer interfaces coupled with robotic assistive technologies such as robotic hand orthosis have the potential to provide rehabilitation strategies that promote brain plasticity for these patients. This paper presents the design of a control signal based on EEG signal processed using common spatial patterns and linear discriminant analysis to identify hand motor imagery. The control signal is implemented on a robotic hand orthosis so that it activates when a healthy subject performs motor imagery of her/his right hand, simulating an online signal acquisition. The mechatronic orthosis performance was always as indicated by the control signal, and the systems online performance for detecting motor imagery was of nearly 80% of correct classification. The system may be improved by using other classification algorithms however results show that it is ready to be tested with motor impaired patients.