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. Current sports interface designs lack attention mechanisms for dynamic exercise. Through EEG, eye-tracking, and user evaluations (16 participants ×3 running state ×4 interfaces), we found: (1) Exercise intensity significantly alters users’ visual attention allocation patterns; (2) Operational performance declines under fast running, despite stable subjective evaluations; (3) Well-structured visual flow can alleviate cognitive load and support effective interaction in dynamic state.