Unifying sensorimotor dynamics in multiclass brain computer interface

Abstract

Unification of spatial brain dynamics in multiclass brain computer interface (BCI) paradigm reduces computational latencies by using lesser number of electrodes from the sensorimotor regions of the brain. We employ reduced number of channels without compromising performance notably. We apply three spatial filtering methods, i.e., Common Spatial Pattern (CSP), Regularized Common Spatial Pattern (RCSP) and Joint Approximate Diagonalization (JAD) as preprocessing. But, we emphasize on selecting specific EEG montages for BCI development. We achieve best 86.7% classification accuracy for subject k3b applying CSP using only 12 channels from sensorimotor regions instead of using 60 channels from the whole brain. Additionally, the average classification accuracies are 64.4% and 61.4% using 60 channels and 12 channels respectively. Also, the average computational latencies are 6.24s and 1.23s in cases of 60 channels and 12 channels respectively.