All of the information retrieval (IR) systems try to retrieve the information that users really want. For this purpose, users have to exactly express and submit their requirements to the systems. However, how to reflect user's subjectivities is a hard problem. When a user wants to search for something, for instance a passenger car or a costume, he/she normally has a kind of feeling such as "graceful and looks intelligent, but not so expensive." Many researchers call this feeling as "Kansei" in many researches, which means the user's psychological feeling as well as the physiological issues. Let's see another example. Image retrieval systems having an ability to handle subjective expressions are useful especially when the users, who have no knowledge about contents of the image database, try to use some Kansei words (e.g., " beautiful", "calm", etc.) to retrieve unknown images. Unfortunately, traditional information retrieval systems cannot efficiently deal with the user-given search requests with Kansei words. Thus, in many application systems, how to deal with Kansei words from different users has become an important issue that the system designers have to confront. In this background, "Kansei engineering" has become one of the hot topics in IR field. In addition, many Kansei retrieval systems have been implemented. However, all of the existing Kansei retrieval systems aim at specific applications. Thus, they are very different from each other. In this paper, based on the many investigations and analysis on the existing systems, we propose a general method for designing efficient Kansei retrieval systems, which has not been done in this field. Our proposal mainly includes a general flow for designing Kansei retrieval systems and a discussion on how to speed up the Kansei retrieval processes using multidimensional indexes. We hope that this paper will be able to help the designers who are planning to design Kansei retrieval systems.