Analysis on the cognitive mechanism of semantic relevance of icons in industrial systems

Yang Dong; Ying Zhang; Chengye Ming

doi:10.1117/12.2671586

1 June 2023 Analysis on the cognitive mechanism of semantic relevance of icons in industrial systems

Yang Dong, Ying Zhang, Chengye Ming

Proceedings Volume 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022); 1262508 (2023) https://doi.org/10.1117/12.2671586
Event: International Conference on Mathematics, Modeling and Computer Science (MMCS2022),, 2022, Wuhan, China

Abstract

This study aims to use N400 components to verify the matching degree of icon design scheme and corresponding semantic vocabulary. The results of behavioral experiments show that the response speed of related semantic words is significantly faster than that of irrelevant semantic words, the subjects are more sensitive to the semantic processing of icon-related semantic words, and the recognition accuracy of irrelevant semantic words is significantly lower than that of related semantic intention words. The analysis results of N400 components show that the activation of the frontal lobe of irrelevant semantic words is significantly higher than that of related semantic words, the N400 amplitude of irrelevant semantic words is larger, and the average voltage is higher, indicating that when the user's subjective judgment of icons and the semantic meaning of the words are presented The higher the degree of deviation, the greater the degree of N400 activation. The study confirmed that N400 can be used as a physiological detection method to verify the correlation between semantic words and icon design.

Citation Download Citation

Yang Dong, Ying Zhang, and Chengye Ming "Analysis on the cognitive mechanism of semantic relevance of icons in industrial systems", Proc. SPIE 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022), 1262508 (1 June 2023); https://doi.org/10.1117/12.2671586

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