A Feedback Information-Theoretic Transmission Scheme (FITTS) for Modeling Trajectory Variability in Aimed Movements

TL;DR

This paper models human aimed movement trajectories as a communication problem, revealing how information transmission limits influence movement variability and speed-accuracy tradeoffs, including Fitts' law, through an information-theoretic framework.

Contribution

It introduces a novel Shannon-like communication model for aiming movements, linking trajectory variability to channel capacity and feedback, and re-analyzes existing data to validate the approach.

Findings

Positional variance decreases exponentially with rate equal to channel capacity C.

First movement phase duration is constant across conditions.

Fitts' law is derived from the information-theoretic model.

Abstract

Trajectories in human aimed movements are inherently variable. Using the concept of positional variance profiles, such trajectories are shown to be decomposable into two phases: In a first phase, the variance of the limb position over many trajectories increases rapidly; in a second phase, it then decreases steadily. A new theoretical model, where the aiming task is seen as a Shannon-like communication problem, is developed to describe the second phase: Information is transmitted from a source (determined by the position at the end of the first phase), to a destination (the movement's end-point) over a channel perturbed by Gaussian noise, with the presence of a noiseless feedback link. Information-theoretic considerations show that the positional variance decreases exponentially with a rate equal to the channel capacity C. Two existing datasets for simple pointing tasks are re-analyzed and observations on real data confirm our model. The first phase has constant duration and C is found constant across instructions and task parameters, which thus characterizes the participant's performance. Our model provides a clear understanding of the speed-accuracy tradeoff in aimed movements: Since the participant's capacity is fixed, a higher prescribed accuracy necessarily requires a longer second phase resulting in an increased overall movement time. The well-known Fitts' law is also recovered using this approach.