Design of Portable Stroke Detection Device Driven by User Demands

Portable stroke diagnostic devices for pre-hospital detection are crucial for improving stroke treatment rates, but most existing devices are too large and difficult to move, delaying diagnosis and treatment. This study uses a method to analyze and transform user needs into the design of a portable stroke detection device for quick pre-hospital diagnosis and timely treatment. Firstly, user needs from doctors, nurses, patients and patients' families were collected through surveys and online searches and organized using the KJ method. The AHP method, FAST model and QFD theories were used to prioritize these needs, translate them into design elements and establish the importance of each element. Finally, the primary and secondary design elements of the device were identified through qualitative and quantitative analyses, considering ergonomics, user behavior, technology and structure. The study shows that the AHP/FAST/QFD integrated method can effectively guide the design of portable stroke detection devices, providing valuable insights for related product designs.