Research on the functional relation between Kansei evaluation and smart watch

In product model design, it is of great significance to get to know consumer's perceptual feelings, i.e. Kansei, about the product so as to improve design and work out the desired product. In this paper, smart watch samples are firstly selected by referring to various kinds of sources. By decomposing watch model structure using morphological analysis method, the key features that appeal to consumers are identified. Kansei is described by and exist in the form of Kansei word, by performing a Factor Analysis on the reduced Kansei Words, the most representative Kansei Words are selected. Then, subjects are invited to make a Kansei evaluation for the watch samples. At last, based on the Quantification Theory Type ?, the prediction model for smart watch design is established in the form of multivariate linear regression model. With the functional relation between Kanseis and watch features being worked out, the design of smart watch can be well directed.