Study on brain computer interface combined tactile enhancement and time-varying features

Neuroplasticity plays an important role in the recovery of injured nervous system. Both motor imagery (MI) and functional electrical stimulation (FES) can promote plasticity by activating the sensorimotor cortex. Specifically, MI as control strategy to activate FES in a brain computer interface (BCI) is a promising approach for motor functions recovery. This study demonstrated the efficiency of somatosensory input provided by electrical stimulation (ES) on cortical activation during MI. And the performance of classifiers with time-varying electroencephalography (EEG) features also be probed. We inspected the cortical activation by EEG for three experiment conditions, i.e. ES during MI, MI and ES. And the classification accuracy of three conditions were discussed respectively. Results showed that the ES during MI could induce stronger cortical activation than the other two conditions, and the classifier with time-varying EEG features had a higher classification accuracy. The results demonstrated that MI-based BCI combined MI and ES which fulfills two properties of somatosensory input and time-varying features is an available approach for motor neural rehabilitation.