Date
2019
Abstract
The population of older adults is increasing across the globe; this growth is predicted to continue into the future. Most older adults prefer to live in their own home, but many live alone without immediate support. Living longer is often coupled with health and social problems and difficulty managing daily activities. Therefore, some level of care is required, but this is costly. Technological solutions may help to mitigate these problems by recognising subtle changes early and intervening before problems become unmanageable. Understanding a personâ s usual behaviour when carrying out Activities of Daily Living (ADL) makes it possible to detect and respond to anomalies. However, current commercial and research monitoring systems do not offer an analysis of ADL and are unable to detect subtle changes. To address this gap, we propose the STRETCH (Socio-Technical Resilience for Enhancing Targeted Community Healthcare) sensor platform that is comprised of non-invasive sensors and machine learning techniques to recognise changes and allow early interventions. The paper discusses design principles, modalities, system architecture, and sensor network architecture.
Supervisor
Description
peer-reviewed
Publisher
Springer
Citation
Innovation in Medicine and Healthcare Systems, and Multimedia. Smart Innovation, Systems and Technologies, Chen YW., Zimmermann A., Howlett R., Jain L. (eds);145
Collections
Lero - The Science Foundation Ireland Research Centre for Software
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Nuseibeh_2019_Sensor.pdf
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Keywords
Ambient assisted living, eHealth, Older people care, Sensor platform, Smart house
ULRR Identifiers
https://researchrepository.ul.ie/handle/10344/9075
 https://doi.org/10.34961/644
Funding code
Funding Information
EPSRC, European Research Council (ERC)
Sustainable Development Goals
External Link
Type
Meetings and Proceedings
Rights
https://creativecommons.org/licenses/by-nc-sa/1.0/
License