Can a highly accurate multi-class SSMVEP BCI induce sensory-motor rhythm in sensorimotor area?
Xin ZhangGuanghua XuAravind RaviSarah PearceNing JiangPublished in: Journal of neural engineering (2020)
Different visual stimuli might have different effects on the brain, e.g. the change of brightness, non-biological movement and biological movement. In this study, flicker, checkerboard, and gaiting stimuli were chosen as visual stimuli to investigate whether steady-state motion visual evoked potential (SSMVEP) effected on the sensorimotor area for rehabilitation. The gaiting stimulus was designed as the gaiting sequence of a human. The hypothesis is that only observing the designed gaiting stimulus would simultaneously induce 1) SSMVEP in the occipital area, similarly to an SSVEP stimulus; and 2) sensorimotor rhythm (SMR) in the primary sensorimotor area, because such action observation could activate the mirror neuron system. Canonical correlation analysis was used to detect SSMVEP from occipital EEG, and event-related spectral perturbation was used to identify SMR in the EEG from the sensorimotor area. The results showed that the designed gaiting stimulus-induced SSMVEP, with classification accuracies of 88.9 ± 12.0% in a four-class scenario. More importantly, it induced clear and sustained event-related desynchronization/synchronization (ERD/ERS), while no ERD/ERS could be observed when the other two SSVEP stimuli were used. Further, for participants with a sufficiently clear SSMVEP pattern (classification accuracy > 85%), the ERD index values in the mu-beta band induced by the proposed gaiting stimulus were statistically different from that of the other two types of stimulus. Therefore, a novel BCI based on the designed stimulus has potential in neurorehabilitation applications because it simultaneously has the high accuracy of an SSMVEP (~90% accuracy in a four-class setup) and the ability to activate the sensorimotor area.
Keyphrases
- functional connectivity
- resting state
- machine learning
- deep learning
- endothelial cells
- atrial fibrillation
- diabetic rats
- heart rate
- computed tomography
- multiple sclerosis
- oxidative stress
- white matter
- optical coherence tomography
- magnetic resonance
- brain injury
- high density
- subarachnoid hemorrhage
- induced pluripotent stem cells
- cerebral ischemia