Adaptation to random and systematic errors: Comparison of amputee and non-amputee control interfaces with varying levels of process noise
Fig 2
Hierarchical Kalman model describes adaptation behavior of subjects using joint angle-based control.
The model was used to predict behavior on the protocol described in the methods (Tables 1 and 2), and a linear regression was used to analyze the factors that determined adaptation on each trial: Error(n+1)-Error(n) = b0 + b1Error(n) + b2Perturb(n) +b3Feedback(n) x Error(n) + b4Feedback(n) x Perturb(n) (Eq 2). This plot shows the linear regression coefficients of the model predictions (+/- standard deviation) compared to the observed linear regression coefficients of subjects using the joint angle control interface (+/- standard error of the mean).
