Towards non-invasive EEG-based arm/hand-control in users with spinal cord injury

Abstract

Restoring the ability to reach and grasp can dramatically improve quality of life for people with cervical spinal cord injury (SCI). The main challenge in restoring independent reaching and grasping in patients is to develop assistive technologies with intuitive and non-invasive user interfaces. We believe that this challenge can be met by directly translating movement-related brain activity into control signals. During the last decade, we have conducted research on EEG-based brain-computer interfaces (BCIs) for the decoding of movement parameters, such as trajectories and targets. Although our findings are promising, the control is still unnatural. Therefore, we surmise that natural and intuitive control of neuroprostheses could be achieved by developing a novel control framework that incorporates detection of goal directed movement intention, movement decoding, identifying the type of grasp, error potentials detection and delivery of feedback.