Quantifying Touch: New Metrics for Characterizing What Happens During a Touch

Quantifying Touch: New Metrics for Characterizing What Happens During a Touch
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量化触摸:描述触摸过程中发生的情况的新指标

DOI:
10.1145/3517428.3544804
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发表时间:
2022
期刊:
Proceedings of the ACM Conference on Computers and Accessibility
影响因子:
--
通讯作者:
Wobbrock, Jacob O.
Wobbrock, Jacob O.
中科院分区:
--
文献类型:
--
作者:
Kong, Junhan;Zhong, Mingyuan;Fogarty, James;Wobbrock, Jacob O.

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对基于触摸的系统的人类表现的测量主要集中在触摸准确性和目标获取速度等总体指标上。但是触摸并不是原子性的,它们会随着时间和空间的推移而展开,特别是对于那些精细运动功能有限的用户来说,他们很难进行快速,准确的触摸。为了深入了解触摸过程中发生的情况,我们提供了15个目标不可知的触摸指标,其中大部分尚未在文献中进行数学形式化。它们是触摸方向、可变性、漂移、持续时间、范围、绝对/符号面积变化、面积可变性、面积偏差、面积范围、绝对/符号角度变化、角度可变性、角度偏差和角度范围。这些度量将触摸视为椭圆的时间序列,而不仅仅是(x,y)坐标。我们提供了我们的指标的数学定义和视觉解释,并考虑当多个手指执行重合触摸时计算我们的指标的策略。为了实现我们的指标,我们收集了27名参与者的触摸数据,其中15人报告说精细运动功能有限。我们的研究结果表明,我们的指标有效地表征触摸行为,包括精细运动的挑战。我们的指标对于理解用户和评估基于触摸的系统以告知他们的设计都很有用。
Measures of human performance for touch-based systems have focused mainly on overall metrics like touch accuracy and target acquisition speed. But touches are not atomic—they unfold over time and space, especially for users with limited fine motor function, for whom it can be difficult to perform quick, accurate touches. To gain insight into what happens during a touch, we offer 15 target-agnostic touch metrics, most of which have not been mathematically formalized in the literature. They are touch direction, variability, drift, duration, extent, absolute/signed area change, area variability, area deviation, area extent, absolute/signed angle change, angle variability, angle deviation, and angle extent. These metrics regard a touch as a time series of ovals instead of a mere (x, y) coordinate. We provide mathematical definitions and visual depictions of our metrics, and consider policies for calculating our metrics when multiple fingers perform coincident touches. To exercise our metrics, we collected touch data from 27 participants, 15 of whom reported having limited fine motor function. Our results show that our metrics effectively characterize touch behaviors including fine-motor challenges. Our metrics can be useful for both understanding users and for evaluating touch-based systems to inform their design.
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