Body machine interface: remapping motor skills after spinal cord injury.

The goal of a body-machine interface (BMI) is to map the residual motor skills of the users into efficient patterns of control. The interface is subject to two processes of learning: while users practice controlling the assistive device, the interface modifies itself based on the user's residual abilities and preferences. In this study, we combined virtual reality and movement capture technologies to investigate the reorganization of movements that occurs when individuals with spinal cord injury (SCI) are allowed to use a broad spectrum of body motions to perform different tasks. Subjects, over multiple sessions, used their upper body movements to engage in exercises that required different operational functions such as controlling a keyboard for playing a videogame, driving a simulated wheelchair in a virtual reality (VR) environment, and piloting a cursor on a screen for reaching targets. In particular, we investigated the possibility of reducing the dimensionality of the control signals by finding repeatable and stable correlations of movement signals, established both by the presence of biomechanical constraints and by learned patterns of coordination. The outcomes of these investigations will provide guidance for further studies of efficient remapping of motor coordination for the control of assistive devices and are a basis for a new training paradigm in which the burden of learning is significantly removed from the impaired subjects and shifted to the devices.