Motor imagery-induced EEG patterns in individuals with spinal cord injury and their impact on brain-computer interface accuracy.
OBJECTIVE
Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no 'cure' at the present time. Brain-computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI.


METHODS
Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups.


RESULTS
It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%).


CONCLUSIONS
The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals.
Laboratory of Brain-Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology, Austria.
G R
GR
Müller-Putz
I
I
Daly
V
V
Kaiser
D000328:Adult; D000368:Aged; D000465:Algorithms; D062207:Brain-Computer Interfaces; D002574:Cervical Vertebrae / Q000503:physiopathology; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor; D006801:Humans; D007092:Imagination; D008875:Middle Aged; D009044:Motor Cortex / Q000503:physiopathology*; D010243:Paralysis / Q000209:etiology / Q000503:physiopathology* / Q000534:rehabilitation; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013119:Spinal Cord Injuries / Q000150:complications / Q000503:physiopathology* / Q000534:rehabilitation; D013647:Task Performance and Analysis; D013904:Thoracic Vertebrae / Q000503:physiopathology; D014584:User-Computer Interface