Research on the Influence of User and Graphic–Text Combined Icon Construal Level Fitting on Visual Cognition

Zhu, Yonghua; Liu, Ying; Lin, Yun; Chen, Mo; Guo, Qi; Zhang, Zhisheng

doi:10.3390/app121910111

Cited by 3 publications

(1 citation statement)

References 56 publications

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“…The results showed that the best search performance was achieved with a vertically symmetrically arranged layout, which provided a reference for the GIS interface layout. Zhu et al (2022) explored the differences in users' visual perception characteristics of the two visual parameters, graphics and text, and pointed out that the design of combination icons should choose a concrete match between graphics and text to reduce the cognitive load.…”

Section: Visual Parameters As Predictors Of Interface Designmentioning

confidence: 99%

Operator visual attention allocation prediction in a robotic arm teleoperation interface

An,

Zhang,

Jiang

et al. 2023

Hum Ftrs & Erg Mfg Svc

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In digital interactive interfaces with high visual workloads, it is important for operators to allocate their limited attentional resources appropriately to ensure efficient information collection. The salience, effort, expectancy, value (SEEV) model, which combines top‐down and bottom‐up attention mechanisms for predicting attention allocation, has been validated in research areas such as piloting, driving, and surgical operations. However, the validity of the SEEV model in the field of robotic arm teleoperation has not yet been thoroughly studied. The primary purpose of this study was to confirm the feasibility of the SEEV model for operator visual attention allocation prediction in a robotic arm teleoperation scenario. The improved ITTI algorithm, distance‐measuring tool, Delphi method, and lowest ordinal algorithm were adopted to qualify the four factors of the SEEV model, which also contributed to salience and expectancy quantification methods. Accordingly, an attention allocation prediction model in a robotic arm teleoperation scene was constructed. To verify the validity of the prediction model, 20 participants were recruited to control the robotic arm using V‐REP simulation software, and their fixation durations were recorded using an eye tracker as an attention allocation indicator. Participants controlled the robotic arm according to the experimental requirements and operational tasks, such as grasping and placing the target. The results demonstrated that the theoretical data based on the SEEV prediction model are significantly related to the proportion of fixation durations. The experiment verifies the suitability of the SEEV prediction model, and it is anticipated to be utilized in the optimization of interactive interfaces for robotic arm teleoperation.

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Section: Visual Parameters As Predictors Of Interface Designmentioning

confidence: 99%

Operator visual attention allocation prediction in a robotic arm teleoperation interface

An,

Zhang,

Jiang

et al. 2023

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

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A study on the impact of icon structural features in human–computer interface on visual search efficiency

Li,

Lin,

Yang

et al. 2024

Ergonomics

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Evaluation Method for Virtual Museum Interface Integrating Layout Aesthetics and Visual Cognitive Characteristics Based on Improved Gray H-Convex Correlation Model

Wang,

Wen,

Chen

et al. 2024

Applied Sciences

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A scientific method for evaluating the design of interfaces is proposed to address the unique characteristics and user needs of infrequent-contact public service interfaces. This method is significant for enhancing service efficiency and promoting the sustainable development of public services. Current interface evaluation methods are limited in scope and often fail to meet actual user needs. To address this, this study focuses on virtual museums, examining users’ aesthetic psychology and cognitive behavior in terms of layout aesthetics and visual cognitive characteristics, aiming to explore the relationship between the two. Interface layout aesthetic values and user visual cognitive measurements were obtained by using computational aesthetics methods and eye-tracking experiments. These served as input data for a new model. An improved gray H-convex correlation model utilizing the ICRITIC method is proposed to examine the mapping relationship between interface layout aesthetics and visual cognitive features. The results demonstrate that our new model achieves over 90% accuracy, outperforming existing models. For virtual museum interfaces, symmetry and dominance significantly influence user visual cognition, with the most notable correlations found between density and gaze shift frequency, simplicity and mean pupil diameter, and order and gaze shift frequency. Additionally, fixation duration, fixation count, and mean pupil diameter were inversely correlated with interface layout aesthetics, whereas gaze shift frequency and gaze time percentage were positively correlated.

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Research on the Influence of User and Graphic–Text Combined Icon Construal Level Fitting on Visual Cognition

Cited by 3 publications

References 56 publications

Operator visual attention allocation prediction in a robotic arm teleoperation interface

Operator visual attention allocation prediction in a robotic arm teleoperation interface

A study on the impact of icon structural features in human–computer interface on visual search efficiency

Evaluation Method for Virtual Museum Interface Integrating Layout Aesthetics and Visual Cognitive Characteristics Based on Improved Gray H-Convex Correlation Model

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