http://www.jneuroengrehab.com/content/10/1/106/abstract
Journal of NeuroEngineering and Rehabilitation 2013, 10:106 doi:10.1186/1743-0003-10-106
Published: 12 October 2013
Published: 12 October 2013
Abstract (provisional)
Background
Motor imagery can elicit brain oscillations in Rolandic mu rhythm and central beta
rhythm, both originating in the sensorimotor cortex. In contrast with simple limb
motor imagery, less work was reported about compound limb motor imagery which involves
several parts of limbs. The goal of this study was to investigate the differences
of the EEG patterns between simple limb motor imagery and compound limb motor imagery,
and discuss the separability of multiple types of mental tasks.
Methods
Ten subjects participated in the experiment involving three tasks of simple limb motor
imagery (left hand, right hand, feet), three tasks of compound limb motor imagery
(both hands, left hand combined with right foot, right hand combined with left foot)
and rest state. Event-related spectral perturbation (ERSP), power spectral entropy
(PSE) and spatial distribution coefficient were adopted to analyze these seven EEG
patterns. Then three algorithms of modified multi-class common spatial patterns (CSP)
were used for feature extraction and classification was implemented by support vector
machine (SVM).
Results
The induced event-related desynchronization (ERD) affects more components within both
alpha and beta bands resulting in more broad ERD bands at electrode positions C3,
Cz and C4 during left/right hand combined with contralateral foot imagery, whose PSE
values are significant higher than that of simple limb motor imagery. From the topographical
distribution, simultaneous imagination of upper limb and contralateral lower limb
certainly contributes to the activation of more areas on cerebral cortex. Classification
result shows that multi-class stationary Tikhonov regularized CSP (Multi-sTRCSP) outperforms
other two multi-class CSP methods, with the highest accuracy of 84% and mean accuracy
of 70%.
Conclusions
The work implies that there exist the separable differences between simple limb motor
imagery and compound limb motor imagery, which can be utilized to build a multimodal
classification paradigm in motor imagery based brain-computer interface (BCI) systems.
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