Mouse sensitivity in first-person targeting tasks is a highly debated issue. Recommendations within a single game can vary by a factor of 10× or more and are an active topic of experimentation in both competitive and recreational esports communities. Inspired by work in pointer-based gain optimization and extending our previous results from the first user study focused on mouse sensitivity in first-person targeting tasks (Boudaoud et al., 2023), we describe a range of optimal mouse sensitivity wherein players perform statistically significantly better in task completion time and throughput. For tasks involving first-person view control, mouse sensitivity is best described using the ratio between an in-game rotation of the view and corresponding physical displacement of the mouse. We discuss how this displacement-to-rotation sensitivity is incompatible with the control-display gain reported in traditional pointer-based gain studies as well as other rotational gains reported in head-controlled interface studies. We provide additional details regarding impacts of mouse dots per inch, on reported sensitivity, the distribution of spatial difficulty in our experiment, our submovement parsing algorithm, and relationships between measured parameters, further demonstrating optimal sensitivity arising from a speed-precision tradeoff. We conclude our work by updating and improving our suggestions for mouse sensitivity selection and refining directions for future work.

中文翻译：

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第一人称瞄准任务中的鼠标灵敏度

第一人称瞄准任务中的鼠标灵敏度是一个备受争议的问题。单场游戏中的推荐可能会相差 10 倍或更多，这在竞技和娱乐电子竞技社区中都是一个活跃的实验主题。受到基于指针的增益优化工作的启发，并扩展了我们之前的第一个用户研究的结果，该研究专注于第一人称瞄准任务中的鼠标灵敏度（Boudaoud 等人，2023），我们描述了一系列最佳鼠标灵敏度，其中玩家在统计上表现出色任务完成时间和吞吐量显着提高。对于涉及第一人称视图控制的任务，最好使用游戏中视图旋转与鼠标相应物理位移之间的比率来描述鼠标灵敏度。我们讨论了这种位移到旋转的灵敏度如何与传统基于指针的增益研究中报告的控制显示增益以及头部控制界面研究中报告的其他旋转增益不兼容。我们提供了有关每英寸鼠标点数的影响、对报告的灵敏度、实验中空间难度的分布、我们的子运动解析算法以及测量参数之间的关系的更多详细信息，进一步证明了速度与精度权衡所产生的最佳灵敏度。我们通过更新和改进对鼠标灵敏度选择的建议和完善未来工作的方向来结束我们的工作。