Fitness Equipment Design Based on Web User Text Mining

To propose home fitness equipment that meets modern users' needs, this study employs web user text mining, combined with the Fuzzy Analytic Hierarchy Process (FAHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to design and evaluate home fitness equipment that aligns with contemporary demands. First, we used crawler data to collect user reviews of home fitness equipment from a well-known Chinese shopping platform. The data were cleaned and processed to extract key user needs and preferences. Next, the FAHP method was used to prioritize these requirements, and TOPSIS was applied for the comprehensive evaluation of design proposals. This process allowed us to identify the solution that best meets user needs, completing the development of the product design. The results indicate that the second design, with its features targeting lumbar health, efficient space utilization, rich interactive experience, integration of smart technology, and minimalist appearance, has significant market potential and social value. Finally, the SUS (System Usability Scale) was used to validate the design, showing excellent user satisfaction and usability for the second scheme. This study establishes a design process incorporating web scraping, FAHP, and TOPSIS, demonstrating the effectiveness of this theoretical integration in the field of home fitness equipment design.