ABSTRACT
This target article presents a critical survey of the scientific literature dealing with the speed/accuracy trade-offs in rapid-aimed movements. It highlights the numerous mathematical and theoretical interpretations that have been proposed in recent decades. Although the variety of points of view reflects the richness of the field and the high degree of interest that such basic phenomena attract in the understanding of human movements, it calls into question the ability of 'many models to explain the basic observations consistently reported in the field. This target article summarizes the kinematic theory of rapid human movements, proposed recently by R. Plamondon (1993b; 1993c; 1995a; 1995b), and analyzes its predictions in the context of speed/accuracy trade-offs. Data from human movement literature are reanalyzed and reinterpreted in the context of the new theory. It is shown that the various aspects of speed/accuracy trade-offs can be taken into account by considering the asymptotic behavior of a large number of coupled linear systems, from which a delta-lognormal law can be derived to describe the velocity profile of an end-effector driven by a neuromuscular synergy. This law not only describes velocity profiles almost perfectly, it also predicts the kinematic properties of simple rapid movements and provides a consistent framework for the analysis of different types of speed/accuracy trade-offs using a quadratic (or power) law that emerges from the model.
Subject(s)
Goals , Movement/physiology , Female , Humans , Male , Models, Biological , Muscle, Skeletal/physiology , Neurons/physiology , Stochastic Processes , Time FactorsABSTRACT
In this paper we compare 23 different models that can be used to describe the asymmetric bell-shaped velocity profiles of rapid-aimed movements. The comparison is performed with the help of an analysis-by-synthesis experiment over a database of 1052 straight lines produced by nine human subjects. For each line and for each model, a set of parameters is extracted that minimizes the error between the original and the reconstructed data. Performance analysis on the basis of the mean-square-error clearly reflects the superiority of the support-bounded lognormal model to globally describe the velocity profile characterizing rapid movements.
