Evidence map›Paper›PMID 37571771›Full record

ArticleSensors (Basel, Switzerland)2023

A Comparative Study of the Typing Performance of Two Mid-Air Text Input Methods in Virtual Environments.

Yueyang Wang, Yahui Wang, Xiaoqiong Li, Chengyi Zhao, Ning Ma, Zixuan Guo

Abstract readComparative Study
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yueyang WangThe School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China.
Yahui WangThe School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China.
Xiaoqiong LiThe School of Life Science, Beijing Institute of Technology, Beijing 100081, China.ORCID 0000-0002-2614-4219
Chengyi ZhaoFaculty of Psychology, Beijing Normal University, Beijing 100875, China.
Ning MaDepartment of Design, Kyiv National University of Technologies and Design, 01011 Kyiv, Ukraine.
Zixuan GuoFaculty of Psychology, Beijing Normal University, Beijing 100875, China.

Funding

National Defense Basic Scientific Research program of China 20230313002the Beijing Institute of Technology Research Fund Program for Young Scholars 3320012222316
6 · The paper itself

Abstract

Inputting text is a prevalent requirement among various virtual reality (VR) applications, including VR-based remote collaboration. In order to eliminate the need for complex rules and handheld devices for typing within virtual environments, researchers have proposed two mid-air input methods-the trace and tap methods. However, the specific impact of these input methods on performance in VR remains unknown. In this study, typing tasks were used to compare the performance, subjective report, and cognitive load of two mid-air input methods in VR. While the trace input method was more efficient and novel, it also entailed greater frustration and cognitive workload. Fortunately, the levels of frustration and cognitive load associated with the trace input method could be reduced to the same level as those of the tap input method via familiarity with VR. These findings could aid the design of virtual input methods, particularly for VR applications with varying text input demands.

Indexed as

Virtual RealityWorkloadgestural inputkeyboardspointing devicestext inputusability testingvirtual reality

Identifiers

PMID37571771
PMCPMC10422554

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.