Hamilton College, Clinton, NY, USA.
Exp Brain Res. 2010 Nov;207(1-2):133-8. doi: 10.1007/s00221-010-2431-z. Epub 2010 Oct 8.
According to Fitts' Law, the time (MT) to move to a target is a linear function of the logarithm of the ratio between the target's distance and width. Although Fitts' Law accurately predicts MTs for direct movements, it does not accurately predict MTs for indirect movements, as when an obstacle intrudes on the direct movement path. To address this limitation, Jax et al. (2007) added an obstacle-intrusion term to Fitts' Law. They accurately predicted MTs around obstacles in two-dimensional (2-D) workspaces, but their model had one more parameter than Fitts' Law did and was merely descriptive. In this study, we addressed these concerns by turning to the mechanistic, posture-based (PB) movement planning model. The PB-based model accounted for almost as much MT variance in a 3-D movement task as the model of Jax et al., with only two parameters, the same number of parameters as in Fitts' Law.
根据菲茨定律,移动到目标的时间 (MT) 是目标距离和宽度之比的对数的线性函数。尽管菲茨定律准确地预测了直接运动的 MT,但它不能准确地预测间接运动的 MT,例如当障碍物侵入直接运动路径时。为了解决这个限制,Jax 等人。(2007 年)在菲茨定律中增加了一个障碍物入侵项。他们准确地预测了二维(2-D)工作空间中障碍物周围的 MT,但他们的模型比菲茨定律多一个参数,而且只是描述性的。在这项研究中,我们通过转向基于姿势的(PB)运动规划模型来解决这些问题。基于 PB 的模型在 3-D 运动任务中对 MT 变化的解释与 Jax 等人的模型几乎相同,只有两个参数,与菲茨定律的参数数量相同。