Master's Thesis Elcin Cavusoglu

Abstract

Chronic Obstructive Pulmonary Disease (COPD) is a major respiratory disease that causes difficulty in breathing and reduces health-related quality of life. Throughout their respiratory physiotherapy (pulmonary rehabilitation) treatment, COPD patients need to perform breathing exercises at home by themselves. Without the supervision of healthcare professionals, patients have difficulties in performing their exercises alone, and healthcare professionals have no control over patients' health status outside the clinical setup. This thesis aims to develop a system that assists COPD patients with their self-breathing exercises and provides their physiotherapists a data-driven overview of patients' health status and exercise performance at home. To achieve this, a case study including a survey and interviews are conducted with physiotherapists. After understanding the current challenges of the treatment and requirements of the system, the practical approach that consists of detecting the proper breathing pattern, and a web-based assistive system is developed. To evaluate the accuracy of the developed algorithm that detects the proper breathing pattern as well as the usability and efficiency of this approach in the treatment of COPD, this system is integrated into the treatment process of physiotherapists and their COPD patients for two weeks. The results indicate the acceptable accuracy of the algorithm and usability of the system. They also show the interest of both physiotherapists and patients in using this system on their further treatment processes.