Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2017 (2017), Article ID 5708937, 17 pages
https://doi.org/10.1155/2017/5708937
Research Article

Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms

1Biomedical Electronics Robotics & Devices (BERD) Group, Lab of Medical Physics, Faculty of Medicine, School of Health Sciences, Aristotle University of Thessaloniki (AUTH), 54124 Thessaloniki, Greece
21st Department of Neurosurgery, “AHEPA” University General Hospital, Aristotle University of Thessaloniki (AUTH), 54636 Thessaloniki, Greece
3Robotics Laboratory, Computer Science Department, American College of Thessaloniki (ACT), 55535 Thessaloniki, Greece

Correspondence should be addressed to Alkinoos Athanasiou

Received 22 April 2017; Accepted 5 July 2017; Published 29 August 2017

Academic Editor: Victor H. C. de Albuquerque

Copyright © 2017 Alkinoos Athanasiou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Advances in neural interfaces have demonstrated remarkable results in the direction of replacing and restoring lost sensorimotor function in human patients. Noninvasive brain-computer interfaces (BCIs) are popular due to considerable advantages including simplicity, safety, and low cost, while recent advances aim at improving past technological and neurophysiological limitations. Taking into account the neurophysiological alterations of disabled individuals, investigating brain connectivity features for implementation of BCI control holds special importance. Off-the-shelf BCI systems are based on fast, reproducible detection of mental activity and can be implemented in neurorobotic applications. Moreover, social Human-Robot Interaction (HRI) is increasingly important in rehabilitation robotics development. In this paper, we present our progress and goals towards developing off-the-shelf BCI-controlled anthropomorphic robotic arms for assistive technologies and rehabilitation applications. We account for robotics development, BCI implementation, and qualitative assessment of HRI characteristics of the system. Furthermore, we present two illustrative experimental applications of the BCI-controlled arms, a study of motor imagery modalities on healthy individuals’ BCI performance, and a pilot investigation on spinal cord injured patients’ BCI control and brain connectivity. We discuss strengths and limitations of our design and propose further steps on development and neurophysiological study, including implementation of connectivity features as BCI modality.