In the product design and development process centered on user needs, it is crucial to deeply understand and meet users’ multidimensional emotional and image needs for product form. This study proposes a method that combines Kansei engineering (KE), grey relational analysis (GRA), and quantitative theory type I (QTT I) to more accurately capture and implement users’ Kansei needs for product form. Firstly, data is collected through the semantic difference method to quantify the semantic features of users’ perception of product form to reveal their explicit and implicit needs and provide essential data for subsequent analysis. Then, GRA is used to identify the correlation between design elements and users’ emotional needs and to determine the priority ranking of these elements to identify the design elements that are most critical in meeting user needs. Moreover, using the QTT I method to construct a mapping correlation model between product form design elements and Kansei imagery, determine the weight values of Kansei needs for each design element, to evaluate the importance of each design category. Finally, the entropy weight method and TOPSIS method are used to evaluate and prioritize the solutions, selecting the optimized design solution that best meets the multidimensional emotional needs of users. This study takes wheelchair design as an example to evaluate the feasibility and effectiveness of the proposed method.