Classification of lower limb motor imagery based on iterative EEG source localization and feature fusion

Abstract

Motor imagery (MI) brain–computer interface (BCI) systems have broad application prospects in rehabilitation and other fields. However, to achieve accurate and practical MI-BCI applications, there are still several critical issues, such as channel selection, electroencephalogram (EEG) feature extraction and EEG classification, needed to be better resolved. In this paper, these issues are studied for lower limb MI which is more difficult and less studied than upper limb MI. First, a novel iterative EEG source localization method is proposed for channel selection. Channels FC1, FC2, C1, C2 and Cz, instead of the commonly used traditional channel set (TCS) C3, C4 and Cz, are selected as the optimal channel set (OCS). Then, a multi-domain feature (MDF) extraction algorithm is presented to fuse single-domain features into multi-domain features. Finally, a particle swarm optimization based support vector machine (SVM) method is utilized to classify the EEG data collected by the lower limb MI experiment designed by us. The results show that the classification accuracy is 88.43%, 3.35–5.41% higher than those of using traditional SVM to classify single-domain features on the TCS, which proves that the combination of OCS and MDF can not only reduce the amount of data processing, but also retain more feature information to improve the accuracy of EEG classification.

An EEG channel selection method for motor imagery based on Fisher score and local optimization

“…The probabilities of selecting these channels are higher than the average selection rate of 55% for the β band. This indicates that the channels corresponding to the motor cortex, namely C3, C4, and Cz, play relatively important roles in MI, consistent with previous research [30,56,57]. On the other hand, as observed in figures 8 and 9, although the probability of selecting C3, C4, and Cz in the β band is relatively low, a significant portion of channels are still located near the central cortex.…”