Paper Info
Title
A Feedback Information-Theoretic Transmission Scheme (FITTS) for Modelling Aimed Movements.
Abstract
We build on the variability of human movements by focusing on how the stochastic variance of the limb position varies over time. This implies analyzing a whole set of trajectories at once rather than a single trajectory. We show, using real data previously acquired by two independent studies, that in a tapping task, the positional variance profiles are unimodal. The first phase, where positional variance increases steadily, is followed by a second phase where positional variance decreases until it reaches some small level. We show consistency of this two-phase description with two-component models of movement of the literature. During the second phase, the problem of aiming can be reduced to a Shannon-like communication problem where information is transmitted from a source (determined by the distance between current and target position), to a destination (the movementu0027s endpoint) over a channel perturbed by Gaussian noise, with the presence of a feedback information from the current position. We obtain an optimal solution to this problem, re-derive the so-called Elias scheme, and determine that the fastest rate of decrease of variance during the second component is exponential. This leads to a new, local Fittsu0027 law, from which the classical global Fittsu0027 law is also re-derived. The validity of the model is assessed on real data; the rate at which variance is decreased, i.e., at which information is transmitted over the channel, is about 5 bit/s on average.
Year
Venue
Field
2018
arXiv: Human-Computer Interaction
Exponential function,Communication channel,Algorithm,Tapping,Gaussian noise,Mathematics,Trajectory
DocType
Volume
Citations 
Journal
abs/1804.05021
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Julien Gori193.16
Olivier Rioul29223.54