Author Date


Degree Name



Electrical and Computer Engineering


Ira A. Fulton College of Engineering

Defense Date


Publication Date


First Faculty Advisor

Ben Schooley

First Faculty Reader

Steven Allen

Honors Coordinator

Karl Warnick


COPD, spirometry, remote patient monitoring, RPM, telemonitoring, exacerbations


Chronic obstructive pulmonary disease (COPD) affects an estimated 30 million Americans and is the third leading cause of death worldwide. A recent effort to curb deaths and hospitalizations involves remote patient monitoring (RPM). Of all possible monitoring parameters, spirometry presents itself as potentially helpful. Existing RPM studies using spirometry present software systems in early stages of development that have yet to be tested thoroughly in large trials. Further, the array of data elements and software features that should be combined with spirometry for effective COPD RPM and care have yet to be determined. A meta-analysis was performed to determine a generalizable framework of RPM technologies for COPD patients. Use of remote spirometry was a main inclusion factor. A literature search of PubMed, Web of Science, Scopus, and EBSCOhost resulted in 594 records. After screening, 29 records matched inclusion criteria. These RPM studies illustrates several data elements such as spirometry (i.e., FEV1, FVC, PEF), pulse oximetry, vital signs, and physical activity measured by wearable devices; and patient self-reporting of symptoms, medication use, respiratory rate, and standardized tests (e.g., COPD Assessment Test). A qualitative analysis was performed using statements made about effective monitoring parameters in 8 papers, and based on these statements, three RPM parameters are suggested as most likely to be effective: FEV1, daily questionnaires for symptoms and wellbeing, and oxygen saturation. Additional studies could evaluate RPM solutions in larger, more general COPD populations, the role of personalized selection of monitoring parameters, and the potential of monitoring c-reactive protein levels.