Gibson, Raechelle M., Chennu, Srivas, Owen, Adrian M., Cruse, Damian (2014) Complexity and familiarity enhance single-trial detectability of imagined movements with electroencephalography. Clinical Neurophysiology, 125 (8). pp. 1556-1567. ISSN 1388-2457. E-ISSN 1872-8952. (doi:10.1016/j.clinph.2013.11.034) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:54634)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1016/j.clinph.2013.11.034 |
Abstract
Objective
We sought to determine whether the sensorimotor rhythms (SMR) elicited during motor imagery (MI) of complex and familiar actions could be more reliably detected with electroencephalography (EEG), and subsequently classified on a single-trial basis, than those elicited during relatively simpler imagined actions.
Methods
Groups of healthy volunteers, including experienced pianists and ice hockey players, performed MI of varying complexity and familiarity. Their electroencephalograms were recorded and compared using brain-computer interface (BCI) approaches and spectral analyses.
Results
Relative to simple MI, significantly more participants produced classifiable SMR for complex MI. During MI of performance of a complex musical piece, the EEG of the experienced pianists was classified significantly more accurately than during MI of performance of a simpler musical piece. The accuracy of EEG classification was also significantly more sustained during complex MI.
Conclusion
MI of complex actions results in EEG responses that are more reliably classified for more individuals than MI of relatively simpler actions, and familiarity with actions enhances these responses in some cases.
Significance
The accuracy of SMR-based BCIs in non-communicative patients may be improved by employing familiar and complex actions. Increased sensitivity to MI may also improve diagnostic accuracy for severely brain-injured patients in a vegetative state.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.clinph.2013.11.034 |
Uncontrolled keywords: | Motor imagery; Sensorimotor rhythm; Movement complexity; Electroencephalography; Vegetative state |
Subjects: | B Philosophy. Psychology. Religion > BF Psychology |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Srivas Chennu |
Date Deposited: | 13 Apr 2016 10:07 UTC |
Last Modified: | 05 Nov 2024 10:43 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/54634 (The current URI for this page, for reference purposes) |
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