Challenges of Integrating Assistive Technologies and Robots with Embodied Intelligence in the Homes of Older People Living with Frailty
Source abstract
Abstract
The rapid increase in the global population of older adults presents a significant challenge, but also a unique opportunity to leverage technological advancements for promoting independent living and well-being. This study introduces the CIREI framework, which is a comprehensive model designed to enhance the integration of smart home and assistive technologies specifically for pre-frail older adults. Developed through a systematic literature review and innovative and comprehensive co-design activities, the CIREI framework captures the nuanced needs, preferences, and challenges faced by older adults, caregivers, and experts. Key findings from the co-design workshop highlight critical factors such as usability, privacy, and personalised learning preferences, which directly influence technology adoption. These insights informed the creation of an intelligent middleware prototype named WISE-WARE, which seamlessly integrates commercial off-the-shelf (COTS) devices to support health management and improve the quality of life for older adults. The CIREI framework’s adaptability ensures it can be extended and refined to meet the ever-changing needs of the ageing population, providing a robust foundation for future research and development in user-centred technology design. All workshop materials, including tools and methodologies, are made available to encourage the further exploration and adaptation of the CIREI framework, ensuring its relevance and effectiveness in the dynamic landscape of ageing and technology. This research contributes significantly to the discourse on ageing in place, digital inclusion, and the role of technology in empowering older adults to maintain independence.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Technology Use by Older Adults · Context-Aware Activity Recognition Systems · IoT and Edge/Fog Computing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Computing and Digital Technologies, Sheffield Hallam University, Sheffield S1 1WB, UK
Computer Engineering Department, Yarmouk University, Irbid 21163, Jordan
School of Information, Journalism and Communication, The University of Sheffield, Sheffield S10 2TN, UK
Computing Education Research Centre, King’s College London, London WC2R 2LS, UK
School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK
Funding
UK Engineering and Physical Sciences Research Council (EPSRC) under the EMERGENCE (Project EP/W000741/1) Network+ Grant
References (89)
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