Wireless Brain-Robot Interface: User Perception and Performance Assessment of Spinal Cord Injury Patients. (31st December 2017)

• Record Type: Journal Article
• Authors: Athanasiou, Alkinoos; Arfaras, George; Pandria, Niki; Xygonakis, Ioannis; Foroglou, Nicolas; Astaras, Alexander; Bamidis, Panagiotis D.
• Other Names: Kalimeri Kyriaki Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2017(2017)
• Publication Date: 2017-12-31
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2017/2986423
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : Patients suffering from life-changing disability due to Spinal Cord Injury (SCI) increasingly benefit from assistive robotics technology. The field of brain-computer interfaces (BCIs) has started to develop mature assistive applications for those patients. Nonetheless, noninvasive BCIs still lack accurate control of external devices along several degrees of freedom (DoFs). Unobtrusiveness, portability, and simplicity should not be sacrificed in favor of complex performance and user acceptance should be a key aim among future technological directions. In our study 10 subjects with SCI (one complete) and 10 healthy controls were recruited. In a single session they operated two anthropomorphic 8-DoF robotic arms via wireless commercial BCI, using kinesthetic motor imagery to perform 32 different upper extremity movements. Training skill and BCI control performance were analyzed with regard to demographics, neurological condition, independence, imagery capacity, psychometric evaluation, and user perception. Healthy controls, SCI subgroup with positive neurological outcome, and SCI subgroup with cervical injuries performed better in BCI control. User perception of the robot did not differ between SCI and healthy groups. SCI subgroup with negative outcome rated Anthropomorphism higher. Multi-DoF robotics control is possible by patients through commercial wireless BCI. Multiple sessions and tailored BCI algorithms are needed to improve performance.