Research on the Design of Elderly Care Robot Based on KANO-AHP
- DOI
- 10.2991/978-94-6463-562-1_34How to use a DOI?
- Keywords
- KANO model; analytic hierarchy process; home care; escort robot; product design
- Abstract
In order to cope with the increasingly serious aging problem in China, the application of KANO-AHP method in the design of elderly care robot is studied and explored, so as to deeply explore the needs of elderly users and promote product innovation. Firstly, the KANO model is used to identify and classify the core needs of elderly users and clarify the design direction. Then, the AHP method is introduced to construct the hierarchical model. The weight and ranking of each demand are calculated by the judgment matrix, and the demand priority is analyzed to provide scientific decision-making guidance for the design. The results show that vital signs detection has the highest weight in essential attributes, followed by fall alarm and emergency call. The remote call ranked top in the charm attribute; the expectation attribute is the highest priority for middle-aged and elderly community services. The sorting effectively guides the design practice of the elderly care robot. Through the integrated application of KANO model and AHP method, we can accurately grasp the needs of elderly users, so as to provide a solution to the problem of aging.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yun Ma AU - Shengzan Yan AU - Zhiao Qiu PY - 2024 DA - 2024/11/13 TI - Research on the Design of Elderly Care Robot Based on KANO-AHP BT - Proceedings of the 2024 5th International Conference on Big Data and Social Sciences (ICBDSS 2024) PB - Atlantis Press SP - 366 EP - 382 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-562-1_34 DO - 10.2991/978-94-6463-562-1_34 ID - Ma2024 ER -