EEG-Based Recognition Method of Intentional and Unintentional Hand Movement

We present an electroencephalogram (EEG) signals-based method to distinguish intentional and unintentional hand movements by using the optimized linear discriminant analysis (LDA) algorithm by combining the particle swarm optimization (PSO) with the traditional LDA. We design a novel experimental paradigm to validate the proposed method. Experimental results of seven participants show that the proposed method perform well. Furthermore, the performance of the PSO-LDA algorithm which is 86.4% are better than that of the traditional LDA algorithm. This work advances the field of hand movement recognition and gives some insights into the study on human-robot interaction.