SINGLE FEEDBACK MODEL OF HUMAN GOAL-DIRECTED MOVEMENT

Two prominent models frequently used to explain targeted human movement are the stochastic optimized-submovement model and the minimum variance model. Both successfully explain the speed-accuracy tradeoff known as Fitts' law, but neither is complete. The former cannot predict movement trajectory between the endpoints, while the latter is not congruent with the multiple movement segments often observed in human motion. In this paper, a new model is proposed in which an aimed movement consists of two submovements and a single feedback instant, with the trajectory; of each submovement being individually optimized. Simulations using the proposed model show that the optimal transition between two submovements occurs at an early stage of the movement, and produces a sharp peak in the acceleration profile. This result is consistent with psychophysical data. Also observed in numerical simulation is the bell-shaped positional variance curve that is in agreement with psychophysical data.