Fig. 4. Validation of MGA algorithm in individuals with SCI or stroke.

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Fig. 4. Validation of MGA algorithm in individuals with SCI or stroke. Validation of MGA algorithm in individuals with SCI or stroke. (A) Steps for configuration of the MGA. (B) Stick diagram decomposition of whole-body movements (and walker, blue) for a nonambulatory subject with SCI walking with three ranks of upward force and associated forward force. The position of the feet during stance and their trajectories during swing is indicated (gray) together with the trajectory of the wheels of the walker (blue). A representative sequence of EMG activity recorded from ankle muscles is reported for each condition together with the stance duration of each leg (gray bar). Foot dragging is indicated in brown. The CoM trajectory is displayed at the bottom in blue. (C) Locomotor performance was quantified as the Euclidian distance between gait cycles of each subject in three different conditions of upward assistance versus healthy individuals in the PCA space (fig. S3). Middle blue refers to the gravity-assist condition. Light blue and dark blue correspond to a 10% decrease and increase in the amount of upward force, respectively. *P < 0.05, Friedman test with Tukey-Kramer post hoc tests. (D) Impact of suboptimal force configurations based on locomotor performance. (E) Plots reporting the means of selected gait parameters under the three conditions of upward force. The mean (horizontal orange bar) ± SEM (thickness) measured during locomotion in healthy subjects is represented. *P < 0.05, Wilcoxon signed-rank tests. Data are means per subject, n = 6 pathological subjects. Jean-Baptiste Mignardot et al., Sci Transl Med 2017;9:eaah3621 Published by AAAS