Enhance decoding of functional lower-limb movements by combining sensory motor rhythm and movement-related cortical potential features

In previous studies, Sensory Motor Rhythm (SMR) and Movement-Related Cortical Potential (MRCP) have been proved to be complementary in decoding a variety of motion information. However, no studies have reported whether they are complementary when subjects perform functional lower limb movements. In this work, we investigate the effect of two features or their combination on classifying three functional lower limb movements (standing, walking, sitting) and rest. MRCP features are extracted by Locality Preserving Projection (LPP) and SMR features are extracted by selecting the best frequency-channel pairs through the Bhattacharyya distance. A Support Vector Machine (SVM) classifier was employed to assess the performance of different features or their combination in six binary classification tasks, where three types of lower limb movements are compared with each other or with rest. The combination of two features achieved the highest accuracy in most classification task. In the classification of standing and walking, the combination of these two features has shown significantly better performance (both p < 0.05) than the classifiers using either MRCP or SMR. Our results suggest that MRCP and SMR features are complementary for decoding the functional lower limb movements, which would benefit the Brain-computer Interface (BCI) system for lower limb rehabilitation.