Fig. 3

Variance explained in the original signals by each of the principal components of the extracted dynamics. (a) To determine the variance explained in the original data by the dynamics: (1) the RNN model was trained, (2) the trained model weights (internal activations) were extracted and the dynamics corresponding to each PC was isolated. (3) For each PC, the original signals were reconstructed across participants. (4) The coefficient of determination was calculated between the measured input signals and the reconstructed signals for each PC. These values were used to construct eigenvalue plots for each signal type. (b) Eigenvalue plots of the cumulative variance explained by increasing number of principal components of the gait signature for each of the four signal types.