Exploration of a method for insight into accessibility design flaws based on touch dynamics

Junyi Lu (), Yuan Liu, Song Shen and Hui Ren
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Junyi Lu: Jiangnan University
Yuan Liu: Jiangnan University
Song Shen: Jiangnan University
Hui Ren: Jiangnan University

Palgrave Communications, 2024, vol. 11, issue 1, 1-13

Abstract: Abstract The widespread use of smartphones implies that intelligent systems must address the negative emotions experienced by a diverse user group when encountering usability difficulties. Therefore, exploring the relationship between users’ emotions and operational behaviors is crucial for further enhancing the accessibility of intelligent systems. Touch dynamics, as a method of dynamic touch data monitoring, has already provided many models for emotion recognition, which are beneficial in gaining insight into users’ accessibility needs for smartphones and exploring intelligent solutions to design issues. This paper validates this aspect through interviews and experimental studies. The study first conducted an open-ended interview, and then used a touch behavior experiment with emotional labels and a questionnaire to validate the association between accessibility design flaws in intelligent systems and user emotions. The interview results show that middle-aged and older smartphone users have difficulty activating accessibility tools independently. Consequently, this paper establishes a dataset for emotion classification based on touch gesture data, which is used to gain insight into implicit difficulties in the interaction process through negative emotions. From a touch experiment and questionnaire survey of 57 sample users, there is approximately a 78.57% match between the accessibility needs of intelligent systems and users’ negative emotions, with interaction fluency and interface cognition being the main reasons for this phenomenon. Therefore, touch dynamics, as a non-invasive method of emotion recognition, can use negative emotional feedback to gain insights into user needs that are difficult to detect by other methods. This has application value for enhancing users’ emotional experience and promoting a transformation in interaction design thinking.

Date: 2024
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DOI: 10.1057/s41599-024-03234-8

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