Evidence for Composite Cost Functions in Arm Movement Planning: An Inverse Optimal Control Approach

doi:10.1371/journal.pcbi.1002183

Evidence for Composite Cost Functions in Arm Movement Planning: An Inverse Optimal Control Approach

Figure 9

Comparisons between models and real data, for relevant parameters.

A and B depict the reached point (RP) and movement vector (MV) parameters, which are the relevant parameters for the finger path. An analysis confirms that energy and angle jerk models, as well as the hybrid model, are quite efficient in predicting the terminal point on the bar and the movement direction (upward or downward). C and D depict the signed index of path curvature (sIPC) and joint coupling (), and are reported for the sake of completeness. However, they are not relevant when the final point is poorly predicted by a model. It is apparent that only the hybrid model is able to predict successfully these additional parameters (sIPC and joint coupling ). Parameters reported on the graphics: parameter is the cumulative error across all starting positions : , with being one of the following parameters: RP, MV, sIPC, or joint coupling; parameter is the correlation coefficient between the simulated and measured data.

doi: https://doi.org/10.1371/journal.pcbi.1002183.g009