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Guo Z, Lin L. Cognitive physiological data analysis based on the XGBoost algorithm to realize positive perceptual sample classification. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023. [DOI: 10.3233/jifs-222656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Designers refer to existing product cases and innovate products to develop new products. However, when designers screen product cases, there is no user participation, which leads to the lack of user-side knowledge and emotional drive that is very important for design. Therefore, it is necessary to play the role of user emotional knowledge in promoting the whole design process. This paper proposes the concept of the positive perceptual sample, which applies the knowledge emotion integration of designers and users to the screening sample case stage at the beginning of the design process. This study is based on the lack of user-side knowledge and emotional drive of reference cases and integrates user emotion into the reference case screening process. Then, in the emotion measurement process, users’ cognitive data in the screening process are obtained through the eye-brain fusion cognitive experiment. Finally, the XGBoost algorithm is used to process feature index data to realize the classification and recognition of cognitive data and applied to the positive perceptual classification of products. The results show that the classification accuracy of physiological cognitive data with user emotional representation by the XGBoost algorithm is 90.87% . The results of cognitive data classification are applied to the screening of positive perceptual samples, and the satisfaction rate is 98.35% . The results show that the method proposed in this paper provides a new source of ideas for obtaining positive perceptual samples and can be applied to new product development.
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Affiliation(s)
- Zhuen Guo
- School of Mechanical Engineering, Guizhou University, Guiyang, Guizhou, China
| | - Li Lin
- School of Mechanical Engineering, Guizhou University, Guiyang, Guizhou, China
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Emotionally Sustainable Design Toolbox: A Card-Based Design Tool for Designing Products with an Extended Life Based on the User’s Emotional Needs. SUSTAINABILITY 2021. [DOI: 10.3390/su131810152] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Emotionally sustainable design helps users to develop an emotional attachment to a product and motivates them to continue using it, thus extending the product lifecycle, minimizing the need for new products and achieving product sustainability. However, the existing relevant design principles are still very scattered, and they could not effectively guide the emotionally sustainable design practice in a systematic way. We proposed an emotionally sustainable design (ESD) toolbox for product design based on the literature review and expert argumentation. The toolbox consists of seven themes and 20 principles under the three levels of emotional design. The usability of the ESD toolbox was then validated through design practice for the teapot product. The result shows that the ESD toolbox improved the efficiency of the sustainable design process and was helpful to the product’s sustainability.
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