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. 2022 Mar 21;9:716545. doi: 10.3389/frobt.2022.716545

FIGURE 3.

FIGURE 3

Mean of all subjects (N = 9) root mean square error (RMSE) of hip, knee and ankle angle and angular velocity predicted by Gaussian process regression models trained by multiple feature sets during five ambulation tasks. Feature sets include surface electromyography (EMG), anterior sonomyography (Ant. SMG), posterior sonomyography (Pos. SMG), Ant. SMG sensor fusion (Ant. Fusion), and Pos. SMG sensor fusion (Pos. Fusion). RMSEs were calculated between sensor-based prediction of joint kinematics and estimated kinematics. Error bars display standard deviations for the respective RMSE. Significance bars indicate significant difference (p < 0.05) between RMSE of (*) EMG and all other sensing modalities, (a) EMG and anterior SMG, (b) EMG and anterior sensor fusion, (c) EMG and posterior sensor fusion (posterior SMG with EMG), and (d) posterior SMG and anterior sensor fusion (anterior SMG with EMG).