Article

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.

Langue : ANGLAIS