Evaluation of Assistive Mobility Product for the Japanese Elderly by the Kansei Sheets

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3 Citations (Scopus)


After being a subject of psychological, social and even anthropological studies for many years, the nature of emotions and their measurement has become a popular target for research in recent times, in fields such as design and advertising. The consumer world is starting to realize that the human is by nature an emotional being, and that it is important to start addressing this in many different levels in order to for example improve sales, develop better and more personal products and in general to evaluate the effect that all these products and services may have in our life. Basically, emotion is an essential key for developing a product that brings happiness to people. This study investigated the Kansei needs of the Japanese elderly for personal assistive products relating to mobility with emotional design approaches. In Japan, the proportion of people older than 80 years is growing rapidly. To guarantee the sustainability of health and social care systems while enhancing quality of life, it is important to find ways to promote the functional capacity of older people. Mobility is a key issue in maintaining independence in old age. Mobility refers to a person's ability to move independently and safely from one place to another. In the market, there are various types of personal assistive products. This study evaluated the present design of a walking stick from the older people's points of views. Two new emotional evaluation methods were used to carry out this study; Kansei sheets and read body language (RBL) sheet. The present study identified the problems of the walking stick design. Furthermore, it had proved the efficiency of the new evaluation methods to capture older people's experiences and emotions.

Original languageEnglish
Pages (from-to)2205-2212
Number of pages8
JournalProcedia Manufacturing
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


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