Reactive Rhythm Activities and Offline Classification of Imagined Speeds of Finger Movements

Abstract

Reactive rhythm bands to imagined speeds of index finger movement and offline classification of imagined speeds were explored in the paper. EEG was recorded when 4 subjects executed motor imagery of two tasks at first-person perspective that involved left index fingers at two speeds (4Hz and 1Hz, trained and paced by metronome). Relatively prominent rhythmic activities around 10-13 Hz and 24~26 Hz over C3, 12~13 Hz over Cz, and 11~13 Hz, 8~10Hz, and 25~26 Hz over C4 were found by spectrum analysis. The most significant band 9-13Hz was used to construct the feature space. The Fisher discriminant analysis method (FDA), multi-layer perceptron neural network (MLP), and distinction sensitive learning vector quantization (DSLVQ) were applied in offline identification of imagined speeds respectively. The best average misclassification rates between fast and slow movement imagination by only three derivations C3, Cz, and C4 with FDA, MLP, and DSLVQ were 27.5±1%, 31.2±3.7%, and 34.6% at 3260 ms respectively. The results showed that FDA in this study was better than MLP and DSLVQ. This study demonstrated that discrimination for imagined speeds of finger movement was possible and feasible. Classification of imagined movement speeds with high accuracy based on EEG is also possible through improving methods in the paper. The study may provide a strategy to realize fine control of robots by brain-controlled robot interface.