informatics Article A Self-Adaptive and Efficient Context-Aware Healthcare Model for COPD Diseases Hamid Mcheick 1, * and John Sayegh 2   Citation: Mcheick, H.; Sayegh, J. A Self-Adaptive and Efficient Context-Aware Healthcare Model for COPD Diseases. Informatics 2021, 8, 41. https://doi.org/10.3390/ informatics8030041 Academic Editors: Kamran Sedig and Antony Bryant Received: 8 May 2021 Accepted: 15 June 2021 Published: 22 June 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1 Department of Computer Science and Mathematics, University of Quebec at Chicoutimi, Chicoutimi, QC G7H 2B, Canada 2 Department of Computer Science, Faculty of Science Branch I, Lebanese University, Hadath, Beirut 6574, Lebanon; John.sayegh@st.ul.edu.lb * Correspondence: Hamid_mcheick@uqac.ca; Tel.: +141-8545-5011-5676 Abstract: The emergence of pervasive computing technology has revolutionized all aspects of life and facilitated many everyday tasks. As the world fights the coronavirus pandemic, it is necessary to find new ways to use technology to fight diseases and reduce their economic burden. Distributed systems have demonstrated efficiency in the healthcare domain, not only by organizing and managing patient data but also by helping doctors and other medical experts to diagnose diseases and take measures to prevent the development of serious conditions. In the case of chronic diseases, telemonitoring systems provide a way to monitor patients’ states and biomarkers in the course of their everyday routines. We developed a Chronical Obstructive Pulmonary Disease (COPD) healthcare system to protect patients against risk factors. However, each change in the patient context initiated the execution of the system’s entire rule base, which diminished performance. In this article, we use separation of concerns to reduce the impact of contextual changes by dividing the context, rules and services into software modules (units). We combine healthcare telemonitoring with context awareness and self-adaptation to create an adaptive architecture model for COPD patients. The model’s performance is validated using COPD data, demonstrating the efficiency of the separation of concerns and adaptation techniques in context-aware systems. Keywords: software architecture; self-adaptation; context-aware system; COPD; separation of con- cerns; healthcare systems 1. Introduction Chronic obstructive pulmonary disease (COPD) has attracted research interest as a major public health problem. According to the World Health Organization [1], COPD is currently considered the fourth—and is positioned to become the third—most frequent cause of death worldwide [2]. It is also a disabling disease and is thus associated with high treatment and patient management costs. As the disease progresses, patients become more susceptible to respiratory exacerbations, which cause frequent hospital admissions and significantly impact patients’ quality of life and healthcare costs [3,4]. Monitoring patients’ health conditions from home or hospital and transmitting related data to a healthcare centre could be an excellent solution that facilitates the management of the growing number of COPD patients and reduces the burden on health services. This approach, called remote telemonitoring, can be used for timely assessment of an acute exacerbation or as a mechanism to generate alarms for patients and/or healthcare professionals when clinical changes occur that may constitute a risk to the patient [5]. There are many systematic reviews and studies on the topic of telemonitoring in respiratory patients, specifically COPD patients [6–9]. All of these studies have focused on proving the effectiveness of remote telemonitoring for COPD patients by studying the provided services and their impacts on the patient’s quality of life, as well as the obtained organizational and clinical benefits. However, no one has yet proposed a comprehensive Informatics 2021, 8, 41. https://doi.org/10.3390/informatics8030041 https://www.mdpi.com/journal/informatics