Evidence map›Paper›PMID 36867298›Full record

ArticleBrain informatics2023

Measuring cognitive load of digital interface combining event-related potential and BubbleView.

Shaoyu Wei, Ruiling Zheng, Rui Li, Minghui Shi, Junsong Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Brain informatics, 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

5 authors.

Shaoyu WeiDepartment of Artificial Intelligence, Xiamen University, Xiamen, 361005, Fujian, China.
Ruiling ZhengDepartment of Artificial Intelligence, Xiamen University, Xiamen, 361005, Fujian, China.
Rui LiNational Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, 430079, Hubei, China.
Minghui ShiDepartment of Artificial Intelligence, Xiamen University, Xiamen, 361005, Fujian, China.
Junsong ZhangDepartment of Artificial Intelligence, Xiamen University, Xiamen, 361005, Fujian, China. zhangjs@xmu.edu.cn.

Funding

Aeronautical Science Foundation of China 20165168007National Natural Science Foundation of China 61772440National Natural Science Foundation of China 62007016
6 · The paper itself

Abstract

Helmet mounted display systems (HMDs) are high-performance display devices for modern aircraft. We propose a novel method combining event-related potentials (ERPs) and BubbleView to measure cognitive load under different HMD interfaces. The distribution of the subjects' attention resources is reflected by analyzing the BubbleView, and the input of the subjects' attention resources on the interface is reflected by analyzing the ERP's P3b and P2 components. The results showed that the HMD interface with more symmetry and a simple layout had less cognitive load, and subjects paid more attention to the upper portion of the interface. Combining the experimental data of ERP and BubbleView, we can obtain a more comprehensive, objective, and reliable HMD interface evaluation result. This approach has significant implications for the design of digital interfaces and can be utilized for the iterative evaluation of HMD interfaces.

Indexed as

Cognitive loadEvent-related potentialEye trackingGraphical user interfaceHelmet mounted display systems

Identifiers

PMID36867298
PMCPMC9984593

What OpenQuestion holds

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Registered trials

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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.