A framework for evaluating the reliability of health monitoring technologies that are based on ambient intelligence
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Date
2024-12
Authors
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Journal ISSN
Volume Title
Publisher
University of Fort Hare
Abstract
The advancement of health monitoring technologies rooted in Ambient Intelligence (AmI) has created innovative solutions for improving healthcare delivery and supporting independent living. However, a critical challenge persists because of the absence of a standardised, integrated framework to evaluate the reliability of these systems. This gap is particularly significant in resource-constrained environments, where operational uncertainties and infrastructure limitations exacerbate reliability issues. To address this problem, this study proposes a comprehensive framework for evaluating the reliability of AmI-based health monitoring technologies. The framework encompasses key dimensions, including data accuracy, system robustness, reliability and context or environment considerations. It was developed using a combination of simulation-based modelling, reliability block diagrams, and Monte Carlo Markov Chain (MCMC) techniques to systematically quantify and analyse reliability metrics. These methods were applied to case studies such as continuous glucose monitoring and heart rate monitoring in elderly care to validate the framework's practical relevance.
Results from these applications demonstrate the framework's efficacy in identifying and addressing reliability challenges. The findings highlight its ability to facilitate systematic evaluation, enhance fault tolerance, and ensure adaptability across diverse operational contexts. The presented framework contributes significantly to various stakeholders as it offers researchers a structured methodology for reliability assessment, provides healthcare practitioners with tools to ensure dependable patient monitoring, and guides policymakers in the adoption of reliable health technologies. By bridging the gap between technological innovation and practical application, this research advances the field of AmI-based health monitoring, fostering improved healthcare outcomes and greater trust in intelligent systems. Software developers, researchers, Health Monitoring devices manufacturers, Internet of Things (IOT) experts and patients on chronic medication who require regular monitoring, and the health sector are the targeted beneficiaries of the framework. Using two case studies which are Continuous Glucose Monitoring and Heart Rate Monitoring in elderly care the main limitations was the effectiveness of reliability in addressing these issues. This lays the groundwork for further refinement and application of the framework in broader contexts. Thus, future research ought to focus on addressing operational challenges, improving explainability in AI models, and discovering innovative applications of AI in healthcare monitoring systems.
Description
PhD thesis
Keywords
Reliability, Self-help devices for people with disabilities, Ambient Intelligence, Medical care
Citation
Scott, M.S. (2024) A framework for evaluating the reliability of health monitoring technologies based on ambient intelligence. PhD thesis. Alice, South Africa: University of Fort Hare.