Loading…
Developing a virtual reality healthcare product based on data-driven concepts: A case study
The rapid development of artificial intelligence (AI) and big data technologies has profoundly changed the way of human life and work, and in the healthcare field, the related product design is moving towards the trend of digitalization, intelligence, and personalization. The growing demands for per...
Saved in:
Published in: | Advanced engineering informatics 2023-08, Vol.57, p.102118, Article 102118 |
---|---|
Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | The rapid development of artificial intelligence (AI) and big data technologies has profoundly changed the way of human life and work, and in the healthcare field, the related product design is moving towards the trend of digitalization, intelligence, and personalization. The growing demands for personalised healthcare have contributed to a boom in product design theories in related fields. However, it is difficult to measure product users' preferences in precise numerical terms to make strategic decisions in product design. To fill this gap, this study proposes a framework for virtual reality (VR) healthcare product design based on a data-driven concept and develops a VR virtual roaming system for system users guided by this theory. The data-driven concept incorporates AI and big data technologies into product design, helping to shift the design of medical products towards a data-centred approach. Ultimately, an ergonomic experiment was conducted and a case study was carried out to assess the user's experience using brain function data to enable data-driven VR value-added services. This study provides a new perspective on rehabilitation product design, opening the way for better personalised healthcare delivery. |
---|---|
ISSN: | 1474-0346 1873-5320 |
DOI: | 10.1016/j.aei.2023.102118 |