PNEUMON: A DDDAS Framework to Detect Fatigue and Dyspnea in COPD

摘要

Chronic Obstructive Pulmonary Disease (COPD) is one of the major pulmonary diseases and a leading cause of morbidity and mortality worldwide. Although there is no cure for COPD, it can be managed by medication and rehabilitation. Therefore, it is important to monitor the progression of the disease. In this paper, we propose a framework to detect and study the symptoms of COPD using multiple physiological sensors. We focus on two main symptoms dyspnea and fatigue. As there are two types of fatigue physical and cognitive, their detection and sensor fusion pose a challenge. To address this, we employ the Dynamic Data-Driven Application System (DDDAS) paradigm that enables us to collect and analyze data in real-time.