Design of intensive self-suction multi-purpose household ironing table: based on kansei engineering

Chen, Xin; Wang, Wei Zhen

doi:10.1504/ijart.2019.097340

Cited by 3 publications

(2 citation statements)

References 18 publications

(22 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After the measurement test, the description of the perceptual meaning of the product by potential users is obtained, and then the design elements affecting the perceptual intention of consumers are identified by further investigation, statistics, analysis or experiments. Computer-aided analysis modeling methods, such as rough set analysis, linear regression, fuzzy mathematics, neural networks, etc., are used to build research and application models of man-machine systems and Kansei engineering [19][20].…”

Section: Kansei Engineeringmentioning

confidence: 99%

Machine Vision Prediction Model for Product Color Design by Kansei Engineering

Han

2024

Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development,

View full text Add to dashboard Cite

Color is a visual element of people, it can bring people different levels, different feelings, and can make people have associations and emotional resonance. Under the background of Kansei engineering, product color design is an important research field. This paper aims to discuss the predictive model of Kansei engineering in product color design, in order to improve the quality of products and meet the needs of consumers. Through empirical research and user survey, this paper verifies the accuracy and effectiveness of product color perceptual image generated by machine vision prediction model for the elderly products. The survey and experimental results show that support vector machines perform best, with an accuracy of 91% and a recall rate 4% higher than BP neural networks.

show abstract

Section: Kansei Engineeringmentioning

confidence: 99%

Machine Vision Prediction Model for Product Color Design by Kansei Engineering

Han

2024

Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development,

View full text Add to dashboard Cite

show abstract

“…Kansei engineering is a method proposed by Nagamachi to translate users' subjective feelings into quantifiable design elements. Kansei engineering was first introduced in Japan in the automotive industry (Nagamachi, 1995) and has since been applied to many fields such as electronics (Oztekin et al, 2013), household products (Chen and Wang, 2019) and product packaging (Nasution et al, 2021). Zhou et al (2021) established a user experience evaluation model for nursing beds by combining physiological data with the help of KE, and Shirafuji et al (Shirafuji et al, 2018) proposed a design strategy for medical transfer-aid equipment with the help of KE.…”

Section: Kansei Evaluationmentioning

confidence: 99%

A user-centered development model for innovation design in automated nursing beds

YANG,

YUAN,

2023

JAMDSM

View full text Add to dashboard Cite

With the improvement of technology and living standard, nursing beds have become more automatic and intelligent, while gradually moving from the ward into the home. In addition to functional technology, the emotional experience has become the dominant factor influencing user purchases. Therefore, it is particularly important to consider user emotional requirements and performance metrics such as usability, ease of use in a coordinated way while maintaining high design efficiency. This paper presents a user-centered development model (UCDM) for products that covers the entire design process. The UCDM successfully complements the generic user-centered design (UCD) approach to effectively and efficiently complete product design. It is validated with the example of an automated nursing bed, which ensures the company's profitability while satisfying users' emotional requirements. Firstly, the Kano model is integrated with Quality of Functional Deployment (QFD) to help designers better understand user needs and locate key design areas and key technical issues for new product innovation. Then, Theory of Creative Problem Solving (TRIZ) is applied to efficiently propose available alternatives to technical issues. And later with the help of Kansei evaluation (KE) methods, the alternatives are scientifically evaluated and decided while providing a reference basis for subsequent optimization. Finally, all the new nursing bed alternatives designed according to the proposed method have been highly evaluated and satisfied by users. The results demonstrate that the proposed design method can help designers to accurately complete user-centered product innovation, scientifically guide the whole design process, and verify the scientific and effective performance of the UCDM.

show abstract

Applying Latent Dirichlet Allocation and Support Vector Regression to the Aesthetic Design of Medical Nursing Beds

Yuan

et al. 2023

Journal of Computing and Information Science in Engineering

View full text Add to dashboard Cite

With the development of social productivity and the improvement in material living standards, emotional value has become the core driver of the enhancement of product market competitiveness. A medical nursing bed, one of the most typical types of medical devices, is designed with little attention to the emotional experience of the users. Therefore, this paper proposes an innovative perceptual design approach under the Kansei engineering (KE) framework for resource-limited and information-poor companies. It guides the aesthetic design of medical nursing beds by constructing a mapping relationship between users' perceptual needs and the design characteristics of medical nursing beds to maximize users' emotions. First, latent Dirichlet allocation (LDA) is used to extract usable Kansei semantics from big data, compensating for the subjectivity of traditional KE data input. Then, the design characteristics obtained after deconstructing a medical nursing bed are simplified with rough set theory (RST). Finally, a mapping model between users' perceptual needs and the core design characteristics of nursing beds is established through support vector regression (SVR), and the optimal design solution is obtained by weighting calculation. The optimal combination of design characteristics for medical nursing beds is finally obtained. The results suggest that the design method proposed in this paper can help designers accurately grasp users' emotional perceptions in terms of aesthetic design and scientifically guide and complete the design of new medical nursing beds, verifying the feasibility and scientificity of the proposed method in terms of aesthetic design.

show abstract

Design of intensive self-suction multi-purpose household ironing table: based on kansei engineering

Cited by 3 publications

References 18 publications

Machine Vision Prediction Model for Product Color Design by Kansei Engineering

Machine Vision Prediction Model for Product Color Design by Kansei Engineering

A user-centered development model for innovation design in automated nursing beds

Applying Latent Dirichlet Allocation and Support Vector Regression to the Aesthetic Design of Medical Nursing Beds

Contact Info

Product

Resources

About