Abstract
The representations of different fingers in the sensorimotor cortex are largely overlapped, which necessitate a good signal-to-noise ratio (SNR) and high spatial resolution to classify individual finger movements from one hand. Electroencephalography (EEG) recorded with disc electrodes has low SNR and poor spatial resolution. The surface Laplacian has been applied to EEG to improve the spatial resolution and selectivity of the surface electrical activity recording. Tri-polar concentric ring electrodes (TCREs) were shown to estimate the Laplacian automatically with better spatial resolution than disc electrodes. For this work, movement-related potentials (MRPs) were recorded from four TCREs and disc electrodes while 13 subjects performed real and imaginary finger movements. The MRP signals recorded with the TCREs have significantly less mutual information and coherence between neighboring locations compared to disc electrodes. The results also show that signals from TCREs generated higher accuracy compared to disc electrodes. It further shows that TCREs using temporal EEG data as features yield an average accuracy of 70.0 +/- 7.7% and 63.3 +/- 5.8% for real and imaginary finger movements, respectively, which is significantly higher than utilizing EEG spectral power changes in alpha and beta bands as features. Similarly, with the disc electrodes, it achieved highest accuracy of 46.13 +/- 6.77% and 34.03 +/- 5.03% for real and imaginary finger movements, respectively, with temporal EEG data feature.