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A Framework for Evaluating the Reliability of Health Monitoring Technologies Based on Ambient Intelligence

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Publicado en:Information vol. 16, no. 10 (2025), p. 833-849
Autor principal: Shakes, Scott Mfundo
Otros Autores: Nobert, Jere, Sibanda Khulumani, Domor, Mienye Ibomoiye
Publicado:
MDPI AG
Materias:
Monte Carlo simulation
Patient safety
Failure
Markov chains
System reliability
Artificial intelligence
Health care
Heart rate
Glucose monitoring
Telemedicine
Adaptive technology
Sensors
Elder care
Wearable computers
Connectivity
Block diagrams
Ambient intelligence
Monitoring systems
Explainable artificial intelligence
Robustness
Markov analysis
Case studies
Acceso en línea:Citation/Abstract
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Resumen:The reliability of health monitoring technologies has become increasingly critical as Ambient Intelligence (AmI) becomes integrated into healthcare. However, a significant gap remains in systematically evaluating reliability, particularly in resource-constrained environments. This study addresses this gap by introducing a comprehensive framework specifically designed to evaluate the reliability of AmI-based health monitoring systems. The proposed framework combines robust simulation-based techniques, including reliability block diagrams (RBDs) and Monte Carlo Markov Chain (MCMC), to evaluate system robustness, data integrity, and adaptability. Validation was performed using real-world continuous glucose monitoring (CGM) and heart rate monitoring (HRM) systems in elderly care. The results demonstrate that the framework successfully identifies critical vulnerabilities, such as rapid initial system degradation and notable connectivity disruptions, and effectively guides targeted interventions that significantly enhance overall system reliability and user trust. The findings contribute actionable insights for practitioners, developers, and policymakers, laying a robust foundation for further advancements in explainable AI, proactive reliability management, and broader applications of AmI technologies in healthcare.
ISSN:2078-2489
DOI:10.3390/info16100833
Fuente:Advanced Technologies & Aerospace Database