Title :
Categorization of patients´ health status in COPD disease using a wearable platform and random forests methodology
Author :
Bellos, C. ; Papadopoulos, Athanasios ; Rosso, R. ; Fotiadis, Dimitrios I.
Author_Institution :
FORTH BRI Found. for Res. & Technol. - Hellas, Biomed. Res., Ioannina, Greece
Abstract :
Chronic diseases are diseases of long duration and generally slow progression. Chronic Obstructive Pulmonary Disease (COPD) as one of these requires frequent examinations and hospital visits for its long-term management. CHRONIOUS, an integrated platform for chronic disease patients, provides functional information about their health status continuously, from the patients´ environment. The main component of the system is the intelligent core of the wearable device that aims at the real-time characterization of the patients´ health level based on the fusion of multiple data that acquired by wearable sensors, through patients smart device interface or retrieved from the specific system´s database. The Decision Support System (DSS) is activated whenever new data are entered, and is functioning using by two classification methodologies composed by highly effective algorithms. These parallel classification techniques are: a rule-based expert system and a supervised Radom Forest classifier. The classification conclusion after the above analysis is twofold. The supervised technique provides with high accuracy the severity of patients´ health level and the rule-based part, extracts the critical parameters or their combination which had been triggered leading in the improvement or the worsening of the patient´s condition.
Keywords :
decision support systems; diseases; expert systems; health care; medical computing; pattern classification; sensor fusion; user interfaces; wearable computers; CHRONIOUS; COPD disease; DSS; chronic obstructive pulmonary disease; classification methodologies; data fusion; decision support system; parallel classification techniques; patient health status categorization; patients health level characterization; patients smart device interface; random forests methodology; rule-based expert system; supervised radom forest classifier; wearable device; wearable platform; wearable sensors; Accuracy; Biomedical monitoring; Classification algorithms; Humidity; Monitoring; Sensors;
Conference_Titel :
Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-2176-2
Electronic_ISBN :
978-1-4577-2175-5
DOI :
10.1109/BHI.2012.6211600