Spinal Cord · 2012 · 174 citations · 34 references
MedicineNeurosurgeryRehabilitation MedicineAssistive TechnologyNeural EngineeringRehabilitationBrain-computer InterfacesElectroencephalographyNeurological RehabilitationRehabilitation RoboticsRobotic RehabilitationSpinal Cord InjuryArm Movement ControlBrain-computer Interface Performance EvaluationBrain-computer Interface RehabilitationElectroencephalography-based Brain-computer InterfacesHuman-robot Interaction In RehabilitationMotor Imagery ClassificationMotor Imagery RehabilitationRehabilitation Robots
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-up-custom questionnaire based-including 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-value=0.025); 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.
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David Mackay · Neural Computation · 1992 · 4.4K citations · Full text
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Jose M. Carmena, Mikhail Lebedev, Roy E. Crist et al. · PLoS Biology · 2003 · 1.8K citations · Full text