Context-aware Approach for Cardiac Rehabilitation Monitoring

Ogbuabor, Godwin, Augusto, Juan Carlos ORCID: https://orcid.org/0000-0002-0321-9150, Moseley, Ralph ORCID: https://orcid.org/0000-0001-5504-0665 and van Wyk, Aléchia ORCID: https://orcid.org/0000-0001-6823-088X (2020) Context-aware Approach for Cardiac Rehabilitation Monitoring. Iglesias, Carlos A., Novella, Jose Ignacio Moreno, Ricci, Alessandro, Pinto, Diego Rivera and Roman, Dumitru, eds. Intelligent Environments 2020: Workshop Proceedings of the 16th International Conference on Intelligent Environments. In: 4th International Workshop on Citizen-Centric Smart Cities Services (CCSCS 2020), 22-23 Jun 2020, Madrid, Spain. ISBN 9781643680903, e-ISBN 9781643680910. ISSN 1875-4163 [Conference or Workshop Item] (doi:10.3233/AISE200039)

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Abstract

As technology advances, the usage and applications of context-aware systems continue to spread across different areas in patient monitoring and disease management. It provides a platform for healthcare professionals to assess the health status of patients in their care using multiple relevant parameters. Existing technologies for cardiac patient monitoring are generally based on the physiological information, mostly the heart rate or Electrocardiogram(ECG) Signals. Other important factors such as physical activities and time of the day are usually ignored. We propose a context-aware solution for cardiac rehabilitation monitoring using multiple vital signs from the physiological and activity data of the patient. This research considers the activity of the patient alongside the time of the activity to facilitate physicians decision-making process. We provide a personalised physical activity recognition processing by generating a personalised model for each user. A prototype is presented to illustrate our proposed approach.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Series:Ambient Intelligence and Smart Environments, Volume: 28
Research Areas: A. > School of Science and Technology > Computer Science > Intelligent Environments group
Item ID: 30288
Notes on copyright: Intelligent Environments 2020, C.A. Iglesias et al. (Eds.)
© 2020 The authors and IOS Press.
This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/AISE200039
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Depositing User: Juan Augusto
Date Deposited: 04 Jun 2020 08:59
Last Modified: 06 Aug 2020 10:12
URI: https://eprints.mdx.ac.uk/id/eprint/30288

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