随着经济的发展和消费者审美趋势的多样化，满足用户的情感需求已逐渐成为提升市场竞争力的关键因素，消费者对于产品意象造型的需求日益提高。传统的医疗器械产品往往更加注重功能，而忽略产品的使用体验及外观的不尽完美，给患者带来额外的不适感和心理负担。常规的中小企业和科研机构往往没有足够的设计资源进行产品外观的开发和迭代，从而造成产品及企业在竞争中处于劣势。如何用最简易的方式及少量的资源获得用户的情感意象并设计出高质量的满足用户需求的产品外观是本次研究的重点。本研究以经颅磁刺激设备为例，提出一种融合生成式人工智能（AIGC）及感性工学的产品造型设计方法，旨在获得用户对于经颅磁刺激设备外观设计的感性意象，并设计出满足用户情感需求的产品外观。

本研究分为四个阶段进行：图像数据构建、感性要素提取、构建映射关系、方案设计与验证。首先，在图像数据构建阶段，收集并整理市场上现有的经颅磁刺激设备图片，以此为基础利用AIGC技术生成一系列概念草图，并筛选出20张具有显著差异的图像。接着，在感性要素提取阶段，通过因子分析法，从选定的感性词汇中提取出影响产品外观的主要因素：信任性因素、先进性因素和风格性因素。利用层次分析法（AHP）确定这些因素在产品外观中的相对重要性。在映射关系构建阶段，通过问卷调查获取用户对产品外观的感性因素评分，结合外观分析，将产品分解为结构、支撑方式、显示器、按钮、操作台位置和底座六个部分，并同感性因素结合建立感性评价矩阵。使用支持向量机回归模型（SVR）来构建预测模型，评估和预测各设计方案的感性评价值。最后，在方案设计与验证阶段，根据模型预测结果，通过整合和应用最高分外观的关键元素，利用AIGC协助生成多个设计方案，对方案进行整合后完成最终的设计，最后进行用户测试验证设计的有效性。

本研究探索性验证了一种结合AIGC及感性工学的混合设计方法，根据研究结果设计出了一款满足用户需求的经颅磁刺激产品外观。该种方法能够帮助企业在产品外观设计阶段以少量的设计资源投入，快速获得符合用户情感意象的产品外观，同时也验证了AIGC在感性工学领域的发展前景。在实践意义上，采用结合了AIGC及感性工学的设计方法，可以为企业节省大量的时间和人力资源，并提高产品设计的效率和质量。这种创新的方法为其他产品的外观设计提供了新的思路和工具，有望在未来的设计实践中发挥重要作用。

With the development of the economy and the diversification of consumer aesthetic trends, meeting the emotional needs of users has gradually become a key factor in enhancing market competitiveness, and consumers' demand for product imagery modeling has been increasing. Traditional medical device products tend to focus more on functionality, neglecting the user experience and the imperfect appearance of the product, which brings additional discomfort and psychological burden to patients. Conventional small and medium-sized enterprises and research institutions often lack sufficient design resources for the development and iteration of product appearance, thus putting products and enterprises at a disadvantage in competition. How to obtain the user's emotional imagery in the simplest way and with minimal resources and design high-quality products that meet user needs is the focus of this study. This study takes the transcranial magnetic stimulation device as an example and proposes a product modeling design method that integrates generative artificial intelligence (AIGC) and Kansei engineering, aiming to obtain the emotional imagery of the transcranial magnetic stimulation device's appearance design and to design a product appearance that meets the emotional needs of users.

This study is divided into four stages: image data construction, Kansei element extraction, mapping relationship construction, and scheme design and verification. First, in the image data construction stage, collect and organize existing transcranial magnetic stimulation device images on the market, use this as a basis to generate a series of conceptual sketches using AIGC technology, and select 20 images with significant differences. Next, in the Kansei element extraction stage, use factor analysis to extract the main factors affecting the product appearance from the selected Kansei vocabulary: trust factors, advancement factors, and style factors. Use the Analytic Hierarchy Process (AHP) to determine the relative importance of these factors in the product appearance. In the mapping relationship construction stage, obtain user ratings of the product's appearance Kansei factors through questionnaire surveys, combine appearance analysis, decompose the product into six parts: structure, support method, display, buttons, operation platform position, and base, and establish a Kansei evaluation matrix in conjunction with Kansei factors. Use the Support Vector Machine Regression model (SVR) to build a predictive model to assess and predict the Kansei evaluation value of each design scheme. Finally, in the scheme design and verification stage, according to the model's predicted results, integrate and apply the key elements of the highest-scoring appearance, use AIGC to assist in generating multiple design schemes, integrate the schemes to complete the final design, and finally conduct user testing to verify the effectiveness of the design.

This study exploratorily verified a hybrid design method that combines AIGC and Kansei engineering. Based on the research results, a transcranial magnetic stimulation product appearance that meets user needs was designed. This method can help enterprises quickly obtain product appearances that conform to user emotional imagery with minimal design resource input during the product appearance design stage, and also verified the development prospects of AIGC in the field of Kansei engineering. In practical terms, adopting a design method that combines AIGC and Kansei engineering can save a lot of time and human resources for enterprises, and improve the efficiency and quality of product design. This innovative method provides new ideas and tools for the appearance design of other products and is expected to play an important role in future design practices.