Abstract
Chronic obstructive pulmonary disease (COPD) is one of the most severe public health problems worldwide. Pervasive computing technology creates a new opportunity to redesign the traditional pattern of medical system. While many pervasive healthcare systems are currently found in the literature, there is little published research on the effectiveness of these paradigms in the medical context. This paper designs and validates a rule-based ontology framework for COPD patients. Unlike conventional systems, this work presents a new vision of telemedicine and remote care solutions that will promote individual self-management and autonomy for COPD patients through an advanced decision-making technique. Rules accuracy estimates were 89% for monitoring vital signs, and environmental factors, and 87% for nutrition facts, and physical activities.
Highlights
Chronic obstructive pulmonary disease (COPD) has a significant impact on individuals and society
Activity would be classified into four categories: the first is sedentary, which requires the least amount of effort, or in other words, the minimal rate of oxygen consumption, the second category is called light-intensity activities; the third category is defined as moderate physical activity; and the fourth category is the vigorous intensity level
We evaluated the performance of the proposed system for the identification of abnormal situations or patterns that may pose serious health risks for COPD patients
Summary
COPD has a significant impact on individuals and society. COPD represents an economic burden on the healthcare system. Brian Carlin, a pulmonary specialist and former chairman of the COPD Alliance, confirms that recognizing the main triggers in each patient is the best health protection plan to prevent flare-ups and thereby slow the progression of the disease; this is through maintaining an active lifestyle in a controlled environment without being exposed to such triggers Specialists in this field suggested that “it may be more valuable to build the telemonitoring and telecommunication. We will present the validation of that proposition, and demonstrating its efficiency through simulated examples of real-life scenarios and empirical data about the environment, activities, symptoms, and physiological parameters For this purpose, we explain in detail the methods for extracting the medical rules of different contextual events.
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