Internet of Things Meets Complex Networks for Early Prediction and Management of Chronic Obstructive Pulmonary Disease.

Project number: PN-III-P2-2.1-PED-2016-1145

Contract number: 31PED / 2017

Period: February 2017 – August 2018

Short summary: Chronic Obstructive Pulmonary Disease (COPD) is the third major cause of death and a serious impediment for the quality of living; it is defined as a clinical condition that consists of airways obstruction which reduces pulmonary capacity. The causes which trigger COPD are not clarified, but scientists converge on indicating smoking and exposure to pollution as main factors. COPD is not reversible, however early detection leads to a better disease evolution. Although COPD diagnosis is a complex process, it is mostly based on spirometry which is performed in a controlled medical environment. The spirometer is a device that measures the air capacity of lungs, rendered as parameters FEV1 and FVC; these parameters are used to classify patients is one of the COPD stages: I-Mild, II-Moderate, III-Severe, and IV-Very Severe. The unanimously accepted classification methodology is the COPD Gold Standard. Unfortunately, early COPD detection and diagnosis at population-level is difficult because clinical signs are hard to detect in early phases. As such, patients are subjected to spirometry and diagnosed when they are already at stages II-IV, thus smoothing the disease trajectory by therapy becomes difficult.

In order to address the problem of COPD management in a big population of individuals, we propose a personalized (precision) medicine approach that relies on big data gathering and modeling, according to the complex network paradigm. Our scope is to demonstrate a solution that consists of a mobile and cloud computing integrated system for COPD early detection, monitoring, and management. Therefore, our system aims at detecting COPD cases in phases I and II. Nonetheless, such a result is not a conventional diagnosis, therefore the prediction will have to be checked and confirmed by a physician. We also intend to provide a disease monitoring and management solution for individuals that are already diagnosed with COPD, in order to assess the effectiveness of their therapy and provide feedback to medical doctors and clinical trial companies.