title: Speed/accuracy trade-offs in target-directed movements.
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.
authors: Département de génie électrique et de génie informatique, Ecole Polytechnique, Montréal, Québec, Canada. rejean@scribens.polymtl.ca
authors: R
authors: R
authors: Plamondon
authors: A M
authors: AM
authors: Alimi
mesh_terms: D005260:Female; D006040:Goals; D006801:Humans; D008297:Male; D008954:Models, Biological; D009068:Movement / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology; D009474:Neurons / Q000502:physiology; D013269:Stochastic Processes; D013997:Time Factors