Application of EEG and Interactive Evolutionary Design Method in Cultural and Creative Product Design

Using subjective emotion, facial expression, and gaze direction to evaluate user affective experience and predict preference when playing single-player games

The affective experience generated when users play computer games can influence their attitude and preference towards the game. Existing evaluation means mainly depend on subjective scales and physiological signals. However, some limitations should not be ignored (e.g. subjective scales are not objective, and physiological signals are complicated). In this paper, we 1) propose a novel method to assess user affective experience when playing single-player games based on pleasure-arousal-dominance (PAD) emotions, facial expressions, and gaze directions, and 2) build an artificial intelligence model to identify user preference. Fifty-four subjects participated in a basketball experiment with three difficulty levels. Their expressions, gaze directions, and subjective PAD emotions were collected and analysed. Experimental results showed that the expression intensities of angry, sad, and neutral, yaw angle degrees of gaze direction, and PAD emotions varied significantly under different difficulties. Besides, the proposed model achieved better performance than other machine-learning algorithms on the collected dataset.

The consumers' response to product design: a narrative review

This paper reviews the research ideas around consumer response to product design. From the product side, we discuss the most significant design features preferred by average consumers, such as aesthetics and utility. And from the consumer side, we investigate the human factors influencing consumer perceptions. We present the main approaches used to measure the consumer response to product design and summarize the multiple biases that occur during the evaluation. Finally, we present in detail the most commonly used methods to analyze consumer response data and their roles in the design evaluation context. Practitioner Summary: To answer the question: What causes differences in design response? We summarise the research findings related to product design features and human factors. We highlight the biases that can emerge from the measurement approach. And discuss the most common analysis methods used for product design response information.

Cognitive physiological data analysis based on the XGBoost algorithm to realize positive perceptual sample classification

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.

Integrating kansei engineering and interactive genetic algorithm in jiangxi red cultural and creative product design

To show the unique charm of Jiangxi’s traditional culture, it is of great importance to apply Jiangxi’s unique red culture to products’ creative designs. This paper aims to apply Kansei Engineering (KE) and interactive genetic algorithm (IGA) to extract the apparent symbol elements of Jiangxi red culture and then transform them into the creative watch design with modern culture. First of all, KE is used to extract customers’ emotional resonance to red culture, and 16 pairs of Kansei image vocabulary pairs are preliminarily collected. The theory of semiotics is used to extract symbols such as shapes, colors, and patterns from the perspective of Jiangxi’s red architecture. Secondly, through the designers’ subjective aesthetic thinking, these cultural symbols are broken up and reconstructed, thus forming the morphological deconstruction table combined with the case of the watch. Finally, IGA is implemented to code and decode the cultural symbols, thus building a product form’s evolutionary design system. Through biological genetic manipulation, cultural symbols of refinement, particularity, and regionality are retained. Then these superior cultural genes are integrated into the innovation of the watch to get creative products with the characteristics of Jiangxi red culture. The model proposed in this paper optimizes the decision-making process of cultural creative product design, and also explores a sustainable development path of culture.

An Interactive Evolutionary Design Method for Mobile Product Customization and Validation of Its Application

Product customization is a means that effectively caters to personal needs, and as such, has increasingly caught the attention of both consumers and manufacturers. With technological advancements, the customization of products is now being made available through mobile applications. However, mobile apps need to be easy to use and operate, which presents some challenges for mobile app designers. In response, this study proposes an interactive evolutionary design method for mobile apps, based on an interactive genetic algorithm, to help consumers generate high-quality designs and enhance their retail experience by optimizing synthetic fitness and reducing the user’s fatigue from evaluation. Firstly, a human–computer interaction model for mobile interactive evolutionary design was launched to solve the screen space problem and simplify the evaluation process. Secondly, to accelerate the convergence of the algorithm, this paper combines hesitation patterns to obtain accurate individual fitness. Thirdly, an ongoing prediction and replacement mechanism were presented to improve user experience. After addressing these items, the proposed method is applied to a customization system that involves traditional brocade patterns of the Zhuang ethnic group in southwestern China and validated using a conventional interactive evolutionary design system with an interactive genetic algorithm. The experimental results show that the proposed method increases the designs’ efficiency, and can help consumers effectively customize their product purchases on mobile devices.

Data-driven affective product design using complete three-dimensional surface data

As the main part of design display and evaluation, product three-dimensional (3D) form is the core object in affective product design. However, previous research has not yet addressed the development of technical models and method involving complete 3D surface data, and thus cannot guarantee the quality of affective product design. By using the techniques of triangular mesh model, spherical harmonic and conditional variational auto-encoder, this paper proposes a data-driven affective product design method composed of several technical models using complete 3D surface data. These models include: mathematical model for quantifying 3D form, recognition model for recognizing customer’s affective responses, and generative model for generating new 3D forms. For affective product design, the mathematical model achieves the acquisition and processing of complete 3D surface data, the recognition model improves the objectivity and accuracy of recognition by integrating the 3D form data into the calculation process of emotion recognition, and the generative model realizes the automatic generation of new 3D forms in response to emotional data based on the recognition results. Each model provides technical support for realizing the acquisition, processing and generation of complete 3D surface data of product form, and ensures the systematic and completeness of the proposed method for the affective product design involving 3D form innovation. The feasibility of the method is verified by an example of car design, and the results show that it is an effective affective product design method involving 3D form innovation.

Evaluation and Balance of Cognitive Friction: Evaluation of Product Target Image Form Combining Entropy and Game Theory

With the great progress of product development technology, product forms have been greatly enriched by cognitive differences; users and designers have formed a “cognitive friction” phenomenon in the product evaluation process, which results in designers being unable to grasp user emotions accurately and risks of product development failure. This paper aims to balance the cognitive differences between cognitive subjects (users and designers) and evaluates the product image form. First, image entropy is used to evaluate and extract the weight of the product target image. Second, fuzzy Theil entropy is used to evaluate the cognitive friction between cognitive subjects, and its existence and size are visually presented. Then, a cognitive friction balance model is built by combining game theory, the comprehensive evaluation weight between cognitive subjects is obtained, and the product image form is ranked and optimized. Finally, all the research steps are described in the form of a household hair dryer. The results show that fuzzy Theil entropy and game theory have significant advantages in the evaluation and balance of cognitive friction in product design. Thus, the cognitive friction evaluation and balance model constructed from the fuzzy Theil entropy and game theory do not only enable different cognitive subjects to achieve cognitive symmetry, but also screen out product forms that meet the cognitive needs of users. This finding provides the theoretical basis and practical significance for the establishment of a closed-loop model in cognitive friction balance and the reduction of cognitive differences between cognitive subjects in the entire process of product design. It also introduces new ways of thinking and methods for cognitive science research.