ADAPT: Approach to Develop context-Aware solutions for Personalised asthma managemenT
Quinde, Mario, Augusto, Juan Carlos ORCID: https://orcid.org/0000-0002-0321-9150, Khan, Nawaz and van Wyk, Aléchia
ORCID: https://orcid.org/0000-0001-6823-088X
(2020)
ADAPT: Approach to Develop context-Aware solutions for Personalised asthma managemenT.
Journal of Biomedical Informatics, 111
, 103586.
pp. 1-20.
ISSN 1532-0464
[Article]
(doi:10.1016/j.jbi.2020.103586)
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Abstract
People with asthma have heterogeneous triggers and symptoms, which they need to be aware of in order to implement the strategies to manage their condition. Context-aware reasoning has the potential to provide the personalisation that is required to address the heterogeneity of asthma by helping people to define the information that is relevant considering the characteristics of their condition and delivering services based on this information. This research work proposes the Approach to Develop context-Aware solutions for Personalised asthma managemenT (ADAPT), whose aim is to facilitate the creation of solutions allowing the required customisation to address the heterogeneity of asthma.
ADAPT is the result of the constant interaction with people affected by asthma throughout the research project, which was possible to achieve thanks to the collaboration formed with the Centre for Applied Research of Asthma UK.
ADAPT context dimensions facilitate the development of preventive and reactive features that can be configured depending on the characteristics of the person with asthma. The approach also provides support to people not knowing their triggers through case-based reasoning and includes virtual assistant as a complementing technology supporting asthma management. ADAPT is validated by people with asthma, carers and experts in respiratory conditions, who evaluated a mobile application that was built based on the approach.
Item Type: | Article |
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Research Areas: | A. > School of Science and Technology > Computer Science > Intelligent Environments group |
Item ID: | 31100 |
Notes on copyright: | © 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Useful Links: | |
Depositing User: | Juan Augusto |
Date Deposited: | 01 Oct 2020 07:24 |
Last Modified: | 29 Nov 2022 18:12 |
URI: | https://eprints.mdx.ac.uk/id/eprint/31100 |
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