Motor-Model-Based Dynamic Scaling in Human–Computer Interfaces

This paper presents a study on how the application of scaling techniques to an interface affects its performance. A progressive scaling factor based on the position and velocity of the cursor and the targets improves the efficiency of an interface, thereby reducing the user's workload. The study uses several human-motor models to interpret human intention and thus contribute to defining and adapting the scaling parameters to the execution of the task. Two techniques addressed to vary the control-display ratio are compared, and a new method for aiding in the task of steering is proposed.