Shannon's Index of Difficulty ($SID$), a logarithmic relation between movement-amplitude and target-width, is reputable for modelling movement-time in pointing tasks. However, it cannot resolve the inherent speed-accuracy trade-off, where emphasizing accuracy compromises speed and vice versa. Effective target-width is considered as spatial adjustment, compensating for accuracy. However, for compensating speed, no significant adjustment exists in the literature. Real-life pointing tasks are both spatially and temporally unconstrained. Spatial adjustment alone is insufficient for modelling these tasks due to several human factors. To resolve this, we propose $ANTASID$ (A Novel Temporal Adjustment to $SID$) formulation with detailed performance analysis. We hypothesized temporal efficiency of interaction as a potential temporal adjustment factor ($t$), compensating for speed. Considering spatial and/or temporal adjustments to $SID$, we conducted regression analyses using our own and benchmark datasets in both controlled and uncontrolled scenarios. The $ANTASID$ formulation showed significantly superior fitness values and throughput in all the scenarios.

中文翻译：

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ANTASID：香农难度指数的新时间调整

香农难度指数 ($SID$) 是运动幅度和目标宽度之间的对数关系，在对指向任务中的运动时间建模方面享有盛誉。然而，它无法解决固有的速度-精度权衡问题，即强调精度会影响速度，反之亦然。有效目标宽度被视为空间调整，以补偿精度。但是，对于补偿速度，文献中没有进行重大调整。现实生活中的指向任务在空间和时间上都不受限制。由于多种人为因素，仅空间调整不足以对这些任务进行建模。为了解决这个问题，我们提出了带有详细性能分析的 $ANTASID$（对 $SID$ 的新时间调整）公式。我们假设交互的时间效率作为潜在的时间调整因子（$t$），以补偿速度。考虑到 $SID$ 的空间和/或时间调整，我们在受控和非受控场景中使用我们自己的和基准数据集进行回归分析。$ANTASID$ 公式在所有场景中都显示出显着优越的适应度值和吞吐量。