Investigating a Force-Based Selection Method for Smartwatches in a 1D Fitts’ Law Study and Two New Character-Level Keyboards

Yuanjun Ren, A. Arif
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引用次数: 1

Abstract

Selecting small targets is difficult on tiny displays due to the “fat-finger problem”. In this paper, we explore the possibility of using a force-based approach to target selection on smartwatches. First, we identify the most comfortable range of force on smartwatches. We then conduct a 1D Fitts’ law study to compare the performance of tap and force-tap. Results revealed that force-tap is significantly better in selecting smaller targets, while tap outperforms force-tap for bigger targets. We then developed two new force-based keyboards to demonstrate the feasibility of force input in practical scenarios. These single-row alphabetical keyboards enable character-level text entry by performing slides and variating contact force. In a user study, these keyboards yielded about 4 wpm with about 2% error rate, demonstrating the viability of force input on smaller screens.
基于力的智能手表选择方法在一维Fitts定律研究和两种新的字符级键盘
由于“胖手指问题”,在微型显示器上选择小目标很困难。在本文中,我们探讨了在智能手表上使用基于力的方法进行目标选择的可能性。首先,我们确定智能手表上最舒适的力度范围。然后,我们进行了一维菲茨定律研究,以比较丝锥和力丝锥的性能。结果表明,在选择较小的目标时,力击优于力击,而在选择较大的目标时,力击优于力击。然后我们开发了两个新的基于力的键盘来演示在实际场景中力输入的可行性。这些单行字母键盘通过执行滑动和改变接触力来实现字符级文本输入。在一项用户研究中,这些键盘产生了大约4个wpm,错误率约为2%,证明了在更小的屏幕上进行力输入的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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