Kansei analysis shown in a single map: multiple correspondence analysis of design elements and Kansei evaluation

In this study, we regarded the idea that supplementary variables and Multiple Correspondence Analysis are promising for analysis and visualize complicated relations in Kansei analysis. It could merge several different information tables and then project them into a map. Applying this advantage would make the overall view of Kansei. Design elements, samples, and associated Kansei words were shown in an MCA map. Leather patterns of children’s lower leg orthotics are the objective of this Kansei evaluation. The leather surface was simulated with 3D CG with physically based rendering methods

Finite Element Estimation of Pressure Distribution inside the Trunk on a Mattress

We developed a bedsore-prevention mattress and wheel chair cushion. Throughout development, we made numerous body pressure measurements on different mattresses and cushions. Such measurements required much time and effort. Simulation of body pressure has the potential to estimate the pressure distribution caused by physical parameters of different mattresses. In this study, we show attempts to model the body and estimate the pressure on its transverse plane. The computation was based on a non-linear finite element method with hyperelastic materials, such as muscle, skin and fat. Because the model simulates different tissues, we can estimate the pressure not only on the surface, but also that inside the trunk. The simulated results agreed well with actual pressure measurement results. Differences in physical properties of the mattresses were also modeled

PLS-based approach for Kansei analysis

A residential garden contributes to mental health in modern life. Gardening is a common recreational activity. From the view of the Kansei engineering, designing the garden is a quite difficult subject. Since garden components such as stones and trees are widely diversified, then number of possible design elements becomes quite large. Meanwhile, evaluation samples that can be used for Kansei Evaluation are limited. Relations between Kansei word evaluation and design elements had been analyzed with Quantification Theory type I, which is a variation of a multiple regression model. Since QT1 is based on the least square method, number of evaluation samples should be larger than the number of design elements. Thus, QT1 is not applicable in this case. Recently, PLS (Partial Least Squares) is becoming popular in the field of Chemometrics, which deal with extremely large number and interacted predictor variables. In this study, we utilized PLS for analyzing Kansei evaluation on residential gardens and their 89 design elements. Analyzing results of PLS and QT1 are compared. QT1 analyses were done on 5-fold design elements. Even when incorporating 89 variables, PLS's multiple correlation coefficient was much higher than QT1. Analyzing result was made into hand-made virtual reality Kansei engineering system. The system contains two projectors and a PC. 3D models of parts such as trees and stones are dynamically chosen and allocated in the scene. The system was based on originally developed 3D computation and rendering library on Java

Effect of averageness and sexual dimorphism on the judgment of facial attractiveness

AbstractEffect of sexual dimorphism and averageness on the judgment of facial attractiveness was investigated. Participants (n=114) rated attractiveness of 96 facial photographs with neutral expressions. Principal component analyses were conducted on 80 facial feature points standardized via the generalized Procrustes method. Local regression analysis was used to obtain the distribution of attractiveness evaluations for the first two principal components. The distribution of facial attractiveness of each sex was approximately line-symmetrical, and each axis of the symmetry passed through average male and female faces. These results suggest that sexual dimorphism and averageness independently influence facial attractiveness

Kansei Analysis of the Japanese Residential Garden and Development of a Low-Cost Virtual Reality Kansei Engineering System for Gardens

Residential garden design using Kansei engineering is a challenging problem. Landscaping components, such as rocks, trees, and ponds, are widely diversified and have a large number of possible arrangements. This large number of design alternatives makes conventional analyses, such as linear regression and its variations like Quantification Theory Type I (QT1), inapplicable for analyzing the relationships between design elements and the Kansei evaluation. We applied a partial least squares (PLS) model that effectively deals with a large number of predictor variables. The multiple correlation coefficient of the PLS analysis was much higher than that of the QT1 analysis. The results of the analyses were used to create a low-cost virtual reality Kansei engineering system that permits visualization of garden designs corresponding to selected Kansei words. To render complex garden scenes, we developed an original 3D computation and rendering library built on Java. The garden is shown in public-view style with stereo 3D graphic projection. The rendering is scalable from low to high resolution and enables drop object shadowing, which is indispensable for considering the effect of daytime changes in insolation. Visualizing the garden design based on Kansei analysis could facilitate collaboration between the designer and customer in the design process