首页> 外文会议>Human Factors and Ergonomics Society;Human Factors and Ergonomics Society annual meeting >Interaction of Movement Difficulty due to the Misalignment Effect and Response Latency: Connections to Fitts’ Law and Implications for System Latency Requirements
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Interaction of Movement Difficulty due to the Misalignment Effect and Response Latency: Connections to Fitts’ Law and Implications for System Latency Requirements

机译:错位效应和响应延迟导致运动困难的相互作用:与菲茨定律的联系以及对系统延迟要求的影响

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In previous reports we measured and analyzed the Misalignment Effect Function, a function describing the decrementin human performance due to rotation between operators’ display and control axes. This prior work allowed us todetermine difficulty-matched sets of rotations for a generalized 3D Fitts-like movement task. We consequently arenow able to study the interaction of system latency and movement difficulty in a highly generalized way in a virtualtelerobotic environment using wide variety of conditions and targets. Our targets are located on a spherical shell nearour participants’ starting point in a high dynamic fidelity virtual environment. Analysis of participants’ ability tomake movements to these targets has revealed a purely multiplicative interaction between control latency and taskdifficulty. Interestingly, we show that this the observed interaction supports work on Fitts’ Law by E.R. Hoffmannand that it depends upon accounting for an internal human processing latency of ~250 ms. Our data suggest that theinteraction varies nonlinearly due to task difficulty in a manner consistent with Hoffmann’s results. We propose a descriptiveequation to reflect the observed interaction that can be seen as a spatiotemporal generalization of Fitts’ Law.Our results provide a basis for generalizing latency requirements for reference tasks that may be varied in difficulty ina manner analogous to the Fitts’ Index of Difficulty.
机译:在以前的报告中,我们测量并分析了“未对准效应”函数,该函数描述了减量。 由于操作员的显示轴和控制轴之间的旋转而对人的行为产生影响。这项先前的工作使我们能够 确定类似于3D Fitts的广义运动任务的难度匹配的旋转集。因此,我们是 现在可以在虚拟环境中以高度通用的方式研究系统延迟和运动难度之间的相互作用 使用各种条件和目标的远程机器人环境。我们的目标位于附近的球形外壳上 参与者在高动态保真度虚拟环境中的起点。分析参与者的能力 向这些目标移动表明控制延迟和任务之间存在纯粹的乘法相互作用 困难。有趣的是,我们表明观察到的这种相互作用支持E.R. Hoffmann对费茨定律的研究。 并且这取决于内部人为处理时间约为250毫秒的等待时间。我们的数据表明 由于任务困难,交互作用以非线性方式变化,与霍夫曼的结果一致。我们提出一个描述性的 反映观察到的相互作用的等式,可以看作是菲茨定律的时空泛化。 我们的结果为概括参考任务的延迟要求提供了基础,参考任务的难度可能会有所不同。 类似于Fitts的难度系数的方式。

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