Modeling and Evaluation of Human Motor Learning by Finger Manipulandum

Abstract

A finger manipulandum was developed to assess human motor learning in a virtual mirror game. The task is the leader-follower modality in the mirror paradigm. The follower in the virtual dynamic system is controlled by the force generated by the interaction between human and manipulandum due to pinching. One participant played the game for five consecutive days. The player’s kinematic tracking error was found to fit the free energy model leading to motor learning. In addition, the acquired data were processed with a machine learning algorithm to predict the retention data. Both the free energy model and predictors were found to provide promising results for more detailed motor learning models of healthy subjects and stroke patients.