Emotional Design Research Articles

An Emotion Recognition Method for Humanoid Robot Body Movements Based on a PSO-BP-RMSProp Neural Network

This paper mainly explores the computational model that connects a robot’s emotional body movements with human emotion to propose an emotion recognition method for humanoid robot body movements. There is sparse research directly carried out from this perspective to recognize robot bodily expression. A robot’s body movements are designed by imitating human emotional body movements. Subjective questionnaires and statistical methods are used to analyze the characteristics of a user’s perceptions and select appropriate designs. An emotional body movement recognition model using a BP neural network (EBMR-BP model) is proposed, in which the selected robot’s body movements and corresponding emotions are used as inputs and outputs. The corresponding topological architecture, encoding rules, and training process are illustrated in detail. Then, the PSO method and the RMSProp algorithm are introduced to optimize the EBMR-BP method, and the PSO-BP-RMSProp model is developed. Through experiments and comparisons for emotion recognition of a robot’s body movements, the feasibility and effectiveness of the EBMR-BP model, with a recognition rate of 66.67%, and the PSO-BP-RMSProp model, with a recognition rate of 88.89%, are verified. This indicates that the proposed method can be used for emotion recognition of a robot’s body movements, and optimization can improve emotion recognition. The contributions are beneficial for emotional interaction design in HRI.

The Impact of User Aesthetics on UI Design: Exploring Design Preferences in China's Sinking Markets vs. Tier 1 and Tier 2 Cities

The purpose of this paper is to explore the impact of the aesthetics of users in China's sinking - market and those in first - and second - tier cities on UI design. This research will conduct a case analysis through a series of typical e - commerce platforms in China. By distinguishing among user experience, cognitive burden, and emotional design, it summarizes what the aesthetic differences are among different market groups, what factors cause these differences, and the impact of these differences on UI design.

Human Perception of the Emotional Expressions of Humanoid Robot Body Movements: Evidence from Survey and Eye-Tracking Measurements

The emotional expression of body movement, which is an aspect of emotional communication between humans, has not been considered enough in the field of human–robot interactions (HRIs). This paper explores human perceptions of the emotional expressions of humanoid robot body movements to study the emotional design of the bodily expressions of robots and the characteristics of the human perception of these emotional body movements. Six categories of emotional behaviors, including happiness, anger, sadness, surprise, fear, and disgust, were designed by imitating human emotional body movements, and they were implemented on a Yanshee robot. A total of 135 participants were recruited for questionnaires and eye-tracking measurements. Statistical methods, including K-means clustering, repeated analysis of variance (ANOVA), Friedman’s ANOVA, and Spearman’s correlation test, were used to analyze the data. According to the statistical results of emotional categories, intensities, and arousals perceived by humans, a guide to grading the designed robot’s bodily expressions of emotion is created. By combining this guide with certain objective analyses, such as fixation and trajectory of eye movements, the characteristics of human perception, including the perceived differences between happiness and negative emotions and the trends of eye movements for different emotional categories, are described. This study not only illustrates subjective and objective evidence that humans can perceive robot bodily expressions of emotions through only vision but also provides helpful guidance for designing appropriate emotional bodily expressions in HRIs.

A new era for stress research: supporting user performance and experience in the digital age

Stress is both a driver of objective performance impairments and a source of negative user experience of technology. This review addresses future directions for research on stress and ergonomics in the digital age. The review is structured around three levels of analysis. At the individual user level, stress is elicited by novel technologies and tasks including interaction with AI and robots, working in Virtual Reality, and operating autonomous vehicles. At the organisational level, novel, potentially stressful challenges include maintaining cybersecurity, surveillance and monitoring of employees supported by technology, and addressing bias and discrimination in the workplace. At the sociocultural level, technology, values and norms are evolving symbiotically, raising novel demands illustrated with respect to interactions with social media and new ethical challenges. We also briefly review the promise of neuroergonomics and emotional design to support stress mitigation. We conclude with seven high-level principles that may guide future work.

Serious Games for Improving Mental Health: Status and Prospects

With the rapid development of time and technology, the significance of digital game development cannot be underestimated. In today's era, games have permeated thousands of households, encompassing a wide range of genres. They are no longer solely entertainment products but also can be applied in education, medical care, learning, scientific research, and other fields. Research indicates that serious games (games designed to teach knowledge and skills or provide professional training and simulation) can effectively improve mental health. This review discusses the current status and future prospects of serious games in promoting mental health. It presents a comprehensive classification of serious games by integrating several literature resources, synthesizing information and data analysis to investigate their effectiveness in improving mental health outcomes. The findings show that serious games play a certain role in the treatment of mental illness. However, the current body of research is not without limitations, as there exists a dearth of controlled experiments comparing the efficacy of serious games to other types of games and investigating the effectiveness of gamification techniques. To address these gaps, researchers and designers should further prioritize approaches such as emotional design and participatory design. Additionally, leveraging emerging technologies like virtual reality can facilitate the development of adaptable game designs and methodologies that align with evolving societal needs.

The application of emotional design in lighting for Chinese healthcare spaces

AbstractWith the development of time, people have more emotional needs for interior spaces. Interior lighting design is an extremely important part of interior design, especially in children's healthcare. In order to meet the needs of child patients and healthcare professionals for ward lighting, it is necessary to comply with various standards while also designing emotionally, emphasizing the positive effects of light on the psychology and health of the user. A literature research approach was used to combine the current status of interior lighting in healthcare spaces, culminating in the integration of the concept of emotional design into the lighting design of children's wards.

The current research status of Kansei engineering in the field of emotional clothing design

PurposeThis study provides a comprehensive overview of the research landscape of Kansei engineering (KE) within the domain of emotional clothing design. It explores the pivotal technologies, challenges and potential future directions of KE, offering application methodologies and theoretical underpinnings to support emotional clothing design.Design/methodology/approachThis study briefly introduces KE, outlining its overarching research methodologies and processes. This framework lays the groundwork for advancing research in clothing Kansei. Subsequently, by reviewing literature from both domestic and international sources, this research initially explores the application of KE in the design and evaluation of clothing products as well as the development of intelligent clothing design systems from the vantage point of designers. Second, it investigates the role of KE in the customization of online clothing recommendation systems and the optimization of retail environments, as perceived by consumers. Finally, with the research methodologies of KE as a focal point, this paper discusses the principal challenges and opportunities currently confronting the field of clothing Kansei research.FindingsAt present, studies in the domain of clothing KE have achieved partial progress, but there are still some challenges to be solved in the concept, technical methods and area of application. In the future, multimodal and multisensory user Kansei acquisition, multidimensional product deconstruction, artificial intelligence (AI) enabling KE research and clothing sales environment Kansei design will become new development trends.Originality/valueThis study provides significant directions and concepts in the technology, methods and application types of KE, which is helpful to better apply KE to emotional clothing design.

Multidimensional Perspectives on the Teaching and Practice of Typography Design

With the continuous deepening of teaching reforms in higher education, it is imperative to reform the teaching of art and design courses. Research has found that the current teaching of typography design in art and design courses has rigid teaching methods, students' operational abilities are relatively singular, and the teaching content is predominantly "Westernized," leading to poor student adaptability. This paper, from a multidimensional perspective, guides typography design course teaching and practice with the "Three E's" (Effect, Efficiency and Efficacy). It positions the teaching content of typography design as multidimensional and emotional, employing multidimensional and emotional design thinking to strengthen the visual information of Chinese culture and tap into students' creative potential, aiming to enhance their innovation and creativity abilities.

Emotional parameter estimation from emo-soundscapes dataset using Deep Convolutional Autoencoders

AbstractPredicting the emotional responses of humans to acoustic features in the surrounding environment has a highly potential of applications in different fields, ranging from videogames, therapeutic use of virtual reality to the emotional design of spaces according to their expected use. In this paper we model the estimation process of the classical emotion characterization parameters (arousal and valence) from sounds. By means of convolutional neural networks and convolutional autoencoders, the model is adjusted for the prediction of these parameters from a standard dataset [1], improving the results obtained in previous literature. The relevance of the work, apart from improving the results due to the use of autoencoders, is that it eliminates the need to compute handcrafted features, thus demonstrating the ability of convolutional neural networks to treat raw information. Other main contributions of the paper is a new way to visualize the errors in the joint estimation of arousal and valence that facilitates the evaluation of the results obtained by the models. Finally, the use of bootstrap to estimate the confidence intervals of the MSE and r2 of Deep Learning models shows that in comparison to non-overlapping samples, overlapping samples introduces performance bias.

Automobile exterior emotional design method based on deep learning and multiple views imagery integrating calculation

In the context of the increasingly dynamic experience economy, users’ emotional experience with automobile has become a leading factor in consumption, making automobile exterior crucial carriers of emotional needs and design expression. However, users’ emotion expression is from three-dimensional automobile entities, with a single perspective potentially causing deviations. Thus, this paper presents a novel automobile exterior emotion design method based on deep learning and multiple views imagery integrating calculation. This approach enables a seamless transition from users’ emotional needs to automobile exterior design. First, we explore users’ emotional evaluation of automobile exterior using the semantic differential method. The improved model of ResNet101-Attention mechanism was used to predict users’ emotion. Additionally, based on above emotional evaluation values, this study proposed a calculation method of multiple views automobile imagery integrating using the Analytic Hierarchy Process and Entropy Weight, calculate the automobile imagery weights of different views, and obtain the final automobile exterior emotional imagery. Finally, the Captum toolkit and the LoRA fine-tuning training technique are used to construct an automobile exterior design optimization generation model, producing a design that meets users’ emotion needs. By comparing the results obtained using both manual and automatic evaluations, and comparing to classical deep learning models. we verify the model’s validity and the advantages of the proposed method. This intelligent method assists designers in quickly identifying users’ responses for automobile design and provides automobile design that meet their emotional needs

어린이 놀이 학습 공간의 감성적 특성을 활용한 학원 공간 설계

The 4th Industrial Revolution and the pandemic are bringing about major changes in the educational environment. Amid the limitations of existing education methods, the rapid development of digital technology and the spread of non-face-to-face education require new methods to draw learners' participation and immersion. Play can be an alternative to the modern educational environment that provides opportunities to develop creativity, cooperation, social skills, and problem-solving skills. This study is a thesis that examines the meaning of play spaces in modern society and examines the design implementation process of learning spaces using emotional design components. To this end, it was conducted based on Maslow's theory of desire, Aaron Walter's theory of emotional design, and domestic prior studies on the components of emotional space. The proposed design is meaningful in creating an environment that naturally increases the motivation and outcome of learning and the restoration of bonds based on the pleasuable of children.

A Study on the Design of Generative AI Cosmetics Containers with Emotional Design

A Study on the Design of Generative AI Cosmetics Containers with Emotional Design

Emotional design for pro-environmental life: Visual appeal and user interactivity influence sustainable consumption intention with moderating effect of positive emotion

As the public pursues sustainable consumption patterns, pro-environmental mobile applications are being developed to promote green lifestyles. Ant Forest has attracted a large number of users to participate due to its gamified interactive design. The objectives of this study are to understand the process by which visual appeal and user interactivity in pro-environmental mobile applications influence the user's sustainable consumption intention and to analyse the moderating effect of the user's positive emotion on this process. The researchers constructed a theoretical framework based on the Stimulus-Organism-Response (S-O-R) theory in this study and used the Partial Least Squares Structural Equation Modelling (PLS-SEM) for quantitative analysis with an online questionnaire survey of 586 Ant Forest users. Findings for this study include: 1) Visual appeal shows a large positive effect on the perceived usefulness of Ant Forest; 2) Ant Forest's perceived usefulness shows a significant positive effect on the user's sustainable consumption intention; 3) Ant Forest's perceived usefulness fully mediates the relationship between visual appeal and the user's sustainable consumption intention; 4) Positive emotion moderates the relationship between perceived usefulness and sustainable consumption intention. This study improves the application of the S-O-R theory in emotional design research, while emphasising the importance of optimising the visual appeal of design elements and guiding users' positive emotions in the development of pro-environmental mobile applications. The findings of this study highlight the importance of incorporating positive emotions into visual design for designers and developers of pro-environmental applications, further clarifying the focus of emotional design.

Promoting Plant-Based Sustainable Diet to Support Future Development: Emotional Design Card Development

The quest for a plant-based sustainable diet has significant value for promoting future development, posing novel challenges for designers. This study involved a five-step design process, encompassing a case study, an experimental study, prototype conception, user testing, and design refinement, with the aim of developing a “Plant-based Sustainable Diet 3P Emotional Design Method” card set that enables individuals to devise personalized sustainable diet plans. The results demonstrated that the instinctive level originates from the product itself, signifying the efficacy of sensory design cues for plant-based foods. The behavioral level stems from the interactive content generated by the product, denoting the efficacy of design cues and highlighting the advantages of transitioning to healthier ingredients for the body. The reflective level arises from the reflection and contemplation of the product, signifying the efficacy of value perception and design cues pertaining to economic, environmental, and social sustainability knowledge. The study analyzed the influencing factors of diet choices through emotional design and provided insights into the underlying psychological mechanisms. The theoretical contribution of this study lies in the novel integration of emotional design and sustainable diet research, while its practical contribution is the introduction of methods and tools that facilitate the adoption of plant-based sustainable diet practices at the individual level.

Research on Sustainable Form Design of NEV Vehicle Based on Particle Swarm Algorithm Optimized Support Vector Regression

With the growing emphasis on eco-friendly and sustainable development concepts, new energy vehicles (NEVs) have emerged as a popular alternative to traditional fuel vehicles (FVs). Due to the absence of an internal combustion engine, electric vehicles (EVs) do not require a front air intake grille, allowing for a more minimalist and flexible design. Consequently, aligning EV styling with users’ visual cognition and emotional perception is a critical objective for automakers and designers. In this study, we establish the mapping relationship between users’ emotional cognition and NEV styling design based on experimental data. We introduce Particle Swarm Optimization Support Vector Regression (PSO-SVR) into the perceptual engineering (KE) research process to predict user emotions using Support Vector Regression (SVR). To optimize the three hyperparameters (penalty coefficient C, RBF kernel function parameter γ, and insensitivity loss coefficient ε) of the SVR model, we utilize the Particle Swarm Optimization (PSO) algorithm. The results indicate that the proposed PSO-SVR model outperforms traditional SVR and BPNN models in predicting NEV user emotions. This model effectively captures the nonlinear relationship between battery electric vehicle (BEV) morphological features and users’ emotional cognition, providing a novel method for enhancing NEV design. The results of this research are expected to drive design innovation and technological advancement in the new energy vehicle industry, contributing to the achievement of the ambitious goal of global eco-friendliness and sustainable development.

Facial animacy in anthropomorphised designs: Insights from leveraging self-report and facial expression analysis for multimedia learning

Anthropomorphism is the act of attributing human-like characteristics to non-human objects and has played a key role in the field of emotional design in multimedia learning. Despite its significance, the relationship between animacy and anthropomorphism, particularly facial animacy, remains underexplored albeit its potential impact on learning engagement and emotional responses. Hence, this study aims to address this gap by examining the effects of facial animacy in anthropomorphised designs using a 3 × 2 design (none vs. static vs. animated) based on self-reported measure (SRM) and facial emotion recognition (FER) and how both measures are associated. The findings revealed discrepancies between both measures, with mostly moderate to weak correlations between hypothesised associations. SRM results indicated that face animacy decreased perceived boredom, while static and dynamic anthropomorphised designs increased curiosity. The FER results revealed notable similarities between designs without anthropomorphism and the static versions, highlighting that facial animacy led participants to express more joy and less neutral expressions. Additionally, neutral expressions were associated with lower enjoyment perception, while negative emotions, especially boredom, were linked to reduced attention.

The interactive effects of pedagogical agent role and voice emotion design on children’s learning

The interactive effects of pedagogical agent role and voice emotion design on children’s learning

An AI-Powered Product Identity Form Design Method Based on Shape Grammar and Kansei Engineering: Integrating Midjourney and Grey-AHP-QFD

Product Identity (PI) is a strategic instrument for enterprises to forge brand strength through New Product Development (NPD). Concurrently, facing increasingly fierce market competition, the NPD for consumer emotional requirements (CRs) has become a significant objective in enterprise research and development (R&D). The design of new product forms must ensure the continuity of PI and concurrently address the emotional needs of users. It demands a high level of experience from designers and significant investment in R&D. To solve this problem, a generative and quantitative design method powered by AI, based on Shape Grammar (SG) and Kansei Engineering (KE), is proposed. The specific method is as follows: Firstly, representative products for Morphological Analysis (MA) are selected, SG is applied to establish initial shapes and transformation rules, and prompts are input into Midjourney. This process generates conceptual sketches and iteratively refines them, resulting in a set of conceptual sketches that preserve the PI. Secondly, a web crawler mines online reviews to extract Kansei words. Factor Analysis (FA) clusters them into Kansei factors, and the Grey Analytic Hierarchy Process (G-AHP) calculates their grey weights. Thirdly, after analyzing the PI conceptual sketches for feature extraction, the features are integrated with CRs into the Quality Function Deployment (QFD) matrix. Experts evaluate the relationships using interval grey numbers, calculating the optimal ranking of PI Engineering Characteristics (PIECs). Finally, professional designers refine the selected sketches into 3D models and detailed designs. Using a Chinese brand as a case study, we have designed a female electric moped (E-moped) to fit the PI and users’ emotional needs. Through a questionnaire survey on the design scheme, we argue that the proposed innovative method is efficient, applicable, and effective in balancing the product form design of PI and user emotions.

Emotional design and evaluation of children’s furniture based on AHP-TOPSIS

Children’s physical and mental health development is highly related to furniture and integrating the emotional design concept into children’s furniture design helps cultivate children’s personalities and promote healthy growth. The model framework of children’s furniture emotional design was constructed from the instinctive level, behavioral level, and reflective level. The comprehensive weight of the design factors was calculated using the Analytic Hierarchy Process (AHP), and three schemes were designed according to the priority of the design factors. The evaluation matrix was constructed by combining the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the distances of each scheme from the positive and negative ideal solutions were calculated, and the optimal scheme was selected according to the relative proximity ranking of the three schemes. The experimental results verified the importance of the reflective level in the three levels of the emotional design theory and emphasized the key role of emotional design in children’s furniture. Therefore, the evaluation system based on AHP and TOPSIS is feasible, which can effectively reduce the influence of subjective factors, make the design decision more scientific, and provide a new reference approach for furniture design.

Website Design and Network Marketing in the Printing Service Industry

Websites become a necessity in helping users to first see the information and content of a product/service offered. Therefore, the development of a website to help small businesses/industries becomes a necessity to help customers get information related to the products/services offered. Marketing product websites has become a necessity today, given that technological advancements have led users to focus more on online purchases. Website design plays a crucial role in enhancing user experience and product marketability more effectively. The aim of this study is to find the optimal combination of design elements for website design according to different user perceptions, so that a reasonable optimization reference based on user perceptions can be provided. Through Kansei Engineering methods and neural network modeling, this study measures and predicts users' perceptions of various website design forms for product marketing. Overall, this study provides conceptual and methodological support for research on the emotional design of human-computer interaction interfaces, as well as supplements existing theories of website design for product marketing. The findings of this study can serve as feedback to website developers for product marketing and related design practitioners to help them improve website design.