Investigating the mechanisms of user attention allocation and interface interaction evaluation across different running states

Current research in sports interaction design emphasises interface optimisation, yet understanding user attention allocation mechanisms across exercise states remains limited. This study explores user attention and interface evaluation under three treadmill-based motion states: stationary, jogging, and fast running. Sixteen participants completed visual tasks across four interface layouts, with multimodal data collected via EEG, eye-tracking, and subjective ratings. Results show that running state alters attention allocation patterns, with increased exercise intensity leading to a pronounced shift towards centrally located interface regions and core exercise metrics. While motion state adversely affects operational performance-most notably during fast running-it does not directly influence users' subjective evaluations of the interface. Importantly, well-structured visual flow can effectively mitigate the impact of motion-induced cognitive constraints. The proposed model of dynamic cognitive resource allocation offers empirical and practical guidance for developing motion-adaptive interfaces that support usability in high-intensity physical environments.

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Publication Details

Journal
Ergonomics
Published
2025-08-03
DOI
https://doi.org/10.1080/00140139.2025.2538706
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Investigating the mechanisms of user attention allocation and interface interaction evaluation across different running states

Yanlin Yin, Yonghong Liu, Pingping Fang, Qingxia Chen
Ergonomics
Human-Automation Interaction and Safety
article

Investigating the mechanisms of user attention allocation and interface interaction evaluation across different running states

Yanlin Yin, Yonghong Liu, Pingping Fang, Qingxia Chen
article en

Abstract

Current research in sports interaction design emphasises interface optimisation, yet understanding user attention allocation mechanisms across exercise states remains limited. This study explores user attention and interface evaluation under three treadmill-based motion states: stationary, jogging, and fast running. Sixteen participants completed visual tasks across four interface layouts, with multimodal data collected via EEG, eye-tracking, and subjective ratings. Results show that running state alters attention allocation patterns, with increased exercise intensity leading to a pronounced shift towards centrally located interface regions and core exercise metrics. While motion state adversely affects operational performance-most notably during fast running-it does not directly influence users' subjective evaluations of the interface. Importantly, well-structured visual flow can effectively mitigate the impact of motion-induced cognitive constraints. The proposed model of dynamic cognitive resource allocation offers empirical and practical guidance for developing motion-adaptive interfaces that support usability in high-intensity physical environments.

Ergonomics
Hunan University (CN), Hunan University of Science and Engineering (CN), Machine Intelligence Research Institute (US)
Openalex Percentile: Top 78%
Human-Automation Interaction and Safety
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Investigating the mechanisms of user attention allocation and interface interaction evaluation across different running states — Yanlin Yin, Yonghong Liu, et al. · Ergonomics (2025) | TGRS Research Map | TGRS