What’s Your next move? Detecting movement intention for stroke rehabilitation

Abstract

BCIs have recently been identified as a method to promote restorative neuroplastic changes in patients with severe motor impairment, such as after a stroke. In this chapter, we describe a novel therapeutic strategy for hand rehabilitation making use of this method. The approach consists of recording brain activity in cortical motor areas by means of near-infrared spectroscopy, and complementing the cortical signals with physiological data acquired simultaneously. By combining these signals, we aim at detecting the intention to move using a multi-modal classification algorithm. The classifier output then triggers assistance from a robotic device, in order to execute the movement and provide sensory stimulation at the
level of the hand as response to the detected motor intention. Furthermore, the cortical data can be used to control audiovisual feedback, which provides a context and a motivating training environment. It is expected that closing the sensorimotor loop with such a brain-body-robot interface will promote europlasticity in sensorimotor networks and support the recovery process.