On the feasibility of using motor imagery EEG-based brain-computer interface in chronic tetraplegics for assistive robotic arm control: A clinical test and long-term post-trial follow-up

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Abstract

Study design:Survey and long-term clinical post-trial follow-up (interviews/correspondence) on nine chronic, post spinal cord injury (SCI) tetraplegics.Objective:To assess feasibility of the use of Electroencephalography-based Brain-Computer Interface (EEG-BCI) for reaching/grasping assistance in tetraplegics, through a robotic arm.Settings:Physical and (neuromuscular) Rehabilitation Medicine, Cardiology, Neurosurgery Clinic Divisions of TEHBA and UMPCD, in collaboration with Brain2Robot (composed of the European Commission-funded Marie Curie Excellence Team by the same name, hosted by Fraunhofer Institute-FIRST), in the second part of 2008.Methods:Enrolled patients underwent EEG-BCI preliminary training and robot control sessions. Statistics entailed multiple linear regressions and cluster analysis. A follow-upcustom questionnaire basedincluding patients perception of their EEG-BCI control capacity was continued up to 14 months after initial experiments.Results:EEG-BCI performance/calibration-phase classification accuracy averaged 81.0%; feedback training sessions averaged 70.5% accuracy for 7 subjects who completed at least one feedback training session; 7 (77.7%) of 9 subjects reported having felt control of the cursor; and 3 (33.3%) subjects felt that they were also controlling the robot through their movement imagination. No significant side effects occurred. BCI performance was positively correlated with beta (13-30 Hz) EEG spectral power density (coefficient 0.432, standardized coefficient 0.745, P-value0.025); another possible influence was sensory AIS score (range: 0 min to 224 max, coefficient -0.177, standardized coefficient 0.512, P=0.089).Conclusion:Limited but real potential for self-assistance in chronic tetraplegics by EEG-BCI-actuated mechatronic devices was found, which was mainly related to spectral density in the beta range positively (increasing therewith) and to AIS sensory score negatively. © 2012 International Spinal Cord Society All rights reserved.

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Onose, G., Grozea, C., Anghelescu, A., Daia, C., Sinescu, C. J., Ciurea, A. V., … Popescu, F. (2012). On the feasibility of using motor imagery EEG-based brain-computer interface in chronic tetraplegics for assistive robotic arm control: A clinical test and long-term post-trial follow-up. Spinal Cord, 50(8), 599–608. https://doi.org/10.1038/sc.2012.14

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