Chronic Obstructive Pulmonary Disease (COPD) is the fourth most frequent cause of death worldwide. There are two reasons why it is desirable to monitor COPD patients outside of hospitals. One is economical, since it has been shown that more than 70% of COPD–related healthcare costs are consequences of emergency and hospital stays for treatment of exacerbations. Early identification of exacerbation and consequently a prompt treatment, reduces hospital stay and overall costs. The other reason is that common lifethreatening events, can be automatically detected in a timely manner for an efficient treatment. Early detections improve recovery time, facilitate more efficient care, and improve quality of life.
The project focuses on physiological parameters that are crucial for detecting exacerbation and life-threatening events, but are currently not measured for COPD patients outside of hospitals. Novel signal processing and reasoning algorithms are developed for the purpose of detecting life-threatening events and generating alarms, based on the physiological parameters, in remote settings. The findings are to be implemented in a prototype system for continuous monitoring of COPD patients. The system will be consisted of the sensors, and a personal computing device on which the system logic will be implemented.
Data Flow and Collection for Remote Patients Monitoring: From Wireless Sensors through a Relational Database to a Web interface in Real Time (Jun 2017) Ivan Tomasic, Nikola Petrovic, Hossein Fotouhi, Maria Lindén, Mats Björkman Joint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) (EMBEC & NBC 2017)