Brain controlled robotic exoskeleton for neurorehabilitation

Abstract

Robots have been used for decades to enhance productivity, reliability and accuracy for repetitive tasks. More recently robot capabilities have been exploited in medical rehabilitation applications for this same reason. While robots can provide consistent physical therapy there is limited evidence that robot assisted physical therapy has any improved outcomes over human administered therapy. Patient participation is the most important factor for rehabilitating the neural system after injury or stroke and so this research develops a new method for re-connecting the brain to the limbs of a patient. Steady state visual evoked potential (SSVEP) signals are read and decoded to extract the user's intent, and then used to control a robot exoskeleton to move the patient's limbs for therapy. This artificial reconnection of the brain to the limbs allows therapy in a natural way and provides positive reinforcement for learning and so it is believed it will result in improved outcomes. Two different training protocols are proposed and tested to allow real-time brain control of a lower limb rehabilitation device. Results with healthy patients are extremely good with accuracy to within a knee angle of 1° at 100% reliability after simple training. This gives much promise to future development of brain controlled rehabilitation devices.