Quantifying task similarity for skill generalisation in the context of human motor control

摘要

In this work, a simple model is used to characterize the learning behaviour of humans. Based on this model, it is possible to define a similarity measure between two tasks in order to quantify skill generalisation during the learning of simple motor tasks by humans. By fully exploring this similarity measure, a sequence of tasks capable of improving the learning efficiency for both healthy subjects and patients with motor impairment may be generated. A validation protocol is introduced and preliminary experimental results with six subjects are presented to validate the learning model and the similarity measure. Results show that the human learning of trajectory tracking tasks can accurately be modelled by an exponential decay of the average tracking error. The model fits well when the task is new or far away from a previously learnt task. Model parameters are used to analyse the learning performances of the subjects and the influence of previous tasks learning. Finally, it is shown that the similarity index can be constructed based on the proposed model to reflect skill generalisation.