An Automated Management System to Detect COPD Exacerbation Using Bayesian Network

• Activity Number: 384
• Type: Topic Contributed
• Date/Time: Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): R. Guo*+ and J. Palmer
• Companies: University of Colorado and University of Colorado

Abstract

Acute exacerbations of chronic obstructive pulmonary disease (COPD) are increasingly being recognized as a major and increasing burden to both patients and society, so it is of great interest to predict and detect COPD exacerbation to reduce admissions. We develop an automated management system using a smartphone device and wearable sensing devices to monitor COPD patients, to collect and automatically send data to central server for statistical assessment, and to alert patients if there are signs of oncoming exacerbation. A Bayesian network model is developed to study the probability of an exacerbation.