## 4 Discussion  
Contrary to the findings of our previous work on a BMI-controlled treadmill [19], we found significant differences between opened-loop trials in which subjects were standing and when they were walking. It is important to note that walking assisted by an exoskeleton is a more complex task than walking on a treadmill, so subjects must be concentrated. Consequently, it is more difficult for them to perform other brain tasks such as MI or regressive count. In addition, when comparing the results from closed-loop trials, the average percentage of epochs with correct commands was 64.5% with the exoskeleton and 75.6% with the treadmill. A possible explanation for this contrast could be also related to the complexity of the movement with the exoskeleton. On the other hand, the attention paradigm showed worse performance than the MI paradigm in opened-loop trials, which is consistent with the findings of our previous work [19]. However, in line with our previous work with an exoskeleton [15], this difference is not as evident in closed-loop trials. Therefore, future BMI designs could rely more on the attention paradigm for the activation of the exoskeleton. While results from the MI paradigm showed an increasing trend throughout sessions, this pattern is not as evident for the attention paradigm. Our results for the MI paradigm are in consonance with the conclusions from [25]. Performing MI is not an intuitive activity for novel participants and practice could promote the modulation and enhance brain activity patterns. Nevertheless, with regard to the attention of the user, the performance does not seem to improve with practice. The attention is something that people train on daily basis, so this could explain why a few sessions cannot further improve it. There are not many investigations in the literature that developed BMI based on lower-limb MI without other external stimuli [2] and they are usually based on motion intention [3,6,10]. In addition, the works of [4,26] employed upper-limb MI to control a lower-limb exoskeleton. Reference [26] showed a percentage of correct commands issued every 4.5 s of 66% and [4] of 80.16% but the BMI was only employed to start the gait and not to stop it. These values can be compared with the %Commands of the present paper. Although superior results are achieved with upper-limb MI, this paradigm cannot be applied to promote neuroplasticity. \begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline  & & **Trial 1** & **Trial 2** & **Trial 3** & **Trial 4** & **Trial 5** & **Avg.** \\ \hline \multirow{8}{*}{**Session 3**} & \%MI & 63.04 & 46.74 & 52.17 & 48.91 & 46.74 & 51.52 \\  & \%Att & 45.65 & 44.57 & 55.43 & 52.17 & 50 & 49.56 \\  & \%Commands & 67.00 & 81.00 & 75.00 & 63.00 & 63.00 & 69.80 \\  & Acc. commands & 60.00 & 60.00 & 75.00 & 40.00 & 50.00 & 57.00 \\  & TPR & 100.00 & 100.00 & 100.00 & 100.00 & 100.00 & 100.00 \\  & FP & 2.00 & 1.00 & 1.00 & 2.00 & 2.00 & 1.60 \\  & FP/min & 4.62 & 2.31 & 2.31 & 4.62 & 4.62 & 3.69 \\ \hline \multirow{8}{*}{**Session 4**} & \%MI & 53.26 & 64.13 & 45.65 & 58.7 & 58.7 & 56.09 \\  & \%Att & 58.7 & 56.52 & 75 & 55.43 & 71.74 & 63.48 \\  & \%Commands & 57.00 & 64.00 & 57.00 & 78.00 & 65.00 & 64.20 \\  & Acc. commands & 0.00 & 100.00 & 0.00 & 75.00 & 50.00 & 45.00 \\  & TPR & 100.00 & 100.00 & 100.00 & 100.00 & 100.00 & 100.00 \\  & FP & 1.00 & 0.00 & 1.00 & 1.00 & 1.00 & 0.80 \\  & FP/min & 2.31 & 0.00 & 2.31 & 2.31 & 2.31 & 1.85 \\ \hline \multirow{8}{*}{**Session 5**} & \%MI & 59.78 & 56.52 & 59.78 & 59.78 & 61.96 & 59.56 \\  & \%Att & 70.65 & 70.65 & 59.78 & 67.39 & 56.52 & 65.00 \\ \cline{1-1}  & \%Commands & 56.00 & 73.00 & 52.00 & 88.00 & 70.00 & 67.80 \\ \cline{1-1}  & Acc. commands & 40.00 & 66.67 & 100.00 & 100.00 & 33.33 & 68.00 \\ \cline{1-1}  & TPR & 100.00 & 100.00 & 100.00 & 100.00 & 100.00 & 100.00 \\ \cline{1-1}  & FP & 2.00 & 1.00 & 0.00 & 0.00 & 2.00 & 1.00 \\ \cline{1-1}  & FP/min & 4.62 & 2.31 & 0.00 & 0.00 & 4.62 & 2.31 \\ \hline \hline \end{tabular}
\end{table}