Abstract
Why does Fitts’ law fit various human behavioural data well even though it is not a model based on human physical dynamics? To clarify this, we derived the relationships among the factors applied in Fitts’ law—movement duration and spatial endpoint error—based on a multi-joint forward- and inverse-dynamics models in the presence of signal-dependent noise. As a result, the relationship between them was modelled as an inverse proportion. To validate whether the endpoint error calculated by the model can represent the endpoint error of actual movements, we conducted a behavioural experiment in which centre-out reaching movements were performed under temporal constraints in four directions using the shoulder and elbow joints. The result showed that the distributions of model endpoint error closely expressed the observed endpoint error distributions. Furthermore, the model was found to be nearly consistent with Fitts’ law. Further analysis revealed that the coefficients of Fitts’ law could be expressed by arm dynamics and signal-dependent noise parameters. Consequently, our answer to the question above is: Fitts’ law for reaching movements can be expressed based on human arm dynamics; thus, Fitts’ law closely fits human’s behavioural data under various conditions.
Highlights
Speed-accuracy trade-offs (SATs), such as that between movement speed and spatial accuracy, are one of the most common phenomena in human movement
We can further assume that the approximation1/D λ/D2 is possible over the general movement duration range, where λ is the coefficient of approximation, giving: τ(Ds) h1(θ(s))[θ (s)θ (s)]
The relationship between movement duration D and hand endpoint error W—the factors used in Fitts’ law—were modelled based on human arm dynamics and found to follow an inversely proportional form: W = γ/D
Summary
Speed-accuracy trade-offs (SATs), such as that between movement speed and spatial accuracy, are one of the most common phenomena in human movement. SATs have been actively studied since Woodworth, who measured the accuracy of voluntary movement. Fitts applied Shannon’s information theory to the human motor system and proposed an empirical model that relates movement duration to movement distance and target width, called Fitts’ law, based on the following equation: D. where D and A are the movement duration and distance, respectively, W is the target width, Id is a logarithmic term in W and A called the index of difficulty, and a and b are intercept and slope, respectively, which are obtained as regression coefficients using D as an objective variable and Id as an explanatory variable. We hypothesised that Fitts’ law in reaching movement could be determined in terms of human arm dynamics. It is important to clarify the relationship between speed-accuracy and arm dynamics because it enables us to understand human motor performance at a more profound level
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
