A four-class BCI based on motor imagination of the right and the left hand wrist

Abstract

This paper presents a new concept for a four-class Brain Computer Interface (BCI) classifier based on motor imagination of the left and the right hand wrist. The noninvasive BCI combines classification of movements of the same limb (wrist flexion and extension) with classification of movements of different limbs, i.e. left and right hand wrist. Results were obtained on four right-handed neurologically intact volunteers. Mean classification accuracy for four different classes was 69% (between 62% and 76%) For the given task, a two-steps two-classes classifier showed significantly better classification results that a single four class classifier.