Skewed Dual Normal Distribution Model: Predicting 1D Touch Pointing Success Rate for Targets Near Screen Edges

Fuente: arXiv
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Main Authors: Kasahara, Nobuhito, Yamanaka, Shota, Miyashita, Homei
Format: Preprint
Published: 2026
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author Kasahara, Nobuhito
Yamanaka, Shota
Miyashita, Homei
author_facet Kasahara, Nobuhito
Yamanaka, Shota
Miyashita, Homei
contents Typical success-rate prediction models for tapping exclude targets near screen edges; however, design constraints often force such placements. Additionally, in scrollable UIs any element can move close to an edge. In this work, we model how target--edge distance affects 1D touch pointing accuracy. We propose the Skewed Dual Normal Distribution Model, which assumes the tap coordinate distribution is skewed by a nearby edge. The results of two smartphone experiments showed that, as targets approached the edge, the distribution's peak shifted toward the edge and its tail extended away. In contrast to prior reports, the success rate improved when the target touched the edge, suggesting a strategy of ``tapping the target together with the edge.'' By accounting for skew, our model predicts success rates across a wide range of conditions, including edge-adjacent targets, thus extending coverage to the whole screen and informing UI design support tools.
format Preprint
id arxiv_https___arxiv_org_abs_2602_22454
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Skewed Dual Normal Distribution Model: Predicting 1D Touch Pointing Success Rate for Targets Near Screen Edges
Kasahara, Nobuhito
Yamanaka, Shota
Miyashita, Homei
Human-Computer Interaction
Typical success-rate prediction models for tapping exclude targets near screen edges; however, design constraints often force such placements. Additionally, in scrollable UIs any element can move close to an edge. In this work, we model how target--edge distance affects 1D touch pointing accuracy. We propose the Skewed Dual Normal Distribution Model, which assumes the tap coordinate distribution is skewed by a nearby edge. The results of two smartphone experiments showed that, as targets approached the edge, the distribution's peak shifted toward the edge and its tail extended away. In contrast to prior reports, the success rate improved when the target touched the edge, suggesting a strategy of ``tapping the target together with the edge.'' By accounting for skew, our model predicts success rates across a wide range of conditions, including edge-adjacent targets, thus extending coverage to the whole screen and informing UI design support tools.
title Skewed Dual Normal Distribution Model: Predicting 1D Touch Pointing Success Rate for Targets Near Screen Edges
topic Human-Computer Interaction
url https://arxiv.org/abs/2602.22454