Figure 7

Online EEG classification illustrated on training data. (A) A goniometer trace delineating idling and dorsifiexion states. (B) The corresponding EEG signal trace recorded at the Cz electrode. (C),(D) One-dimensional spatio-spectral EEG features extracted using Eq. (1) shown in the subspaces corresponding idling $\left(\mathcal{I}\right)$ and dorsifiexion $\left(\mathcal{D}\right)$ states, respectively. The pink and green bands represent the mean ± 2 standard deviations (SD) of features corresponding to idling and dorsifiexion training data, respectively. (E) The average posterior probability of dorsifiexion given feature, f^⋆. Dashed lines correspond to the thresholds, T₁ (green) and T₂ (red) as determined in the Calibration section. As outlined in Fig. 4, when the average posterior probability $\bar{P}\left(\mathcal{D}|f^{\star }\right)>T_1$, the BCI-FES system transitions to dorsifiexion state (shown as green block). Conversely, when $\bar{P}\left(\mathcal{D}|f^{\star }\right)<T_2$, the BCI-FES system transitions to idling state (pink block).