Identification of COPD Patients' Health Status Using an Intelligent System in the CHRONIOUS Wearable Platform
Overview
Medical Informatics
Affiliations
The CHRONIOUS system offers an integrated platform aiming at the effective management and real-time assessment of the health status of the patient suffering from chronic obstructive pulmonary disease (COPD). An intelligent system is developed for the analysis and the real-time evaluation of patient's condition. A hybrid classifier has been implemented on a personal digital assistant, combining a support vector machine, a random forest, and a rule-based system to provide a more advanced categorization scheme for the early and in real-time characterization of a COPD episode. This is followed by a severity estimation algorithm which classifies the identified pathological situation in different levels and triggers an alerting mechanism to provide an informative and instructive message/advice to the patient and the clinical supervisor. The system has been validated using data collected from 30 patients that have been annotated by experts indicating 1) the severity level of the current patient's health status, and 2) the COPD disease level of the recruited patients according to the GOLD guidelines. The achieved characterization accuracy has been found 94%.
Edge Computing System for Automatic Detection of Chronic Respiratory Diseases Using Audio Analysis.
Rivas-Navarrete J, Perez-Espinosa H, Padilla-Ortiz A, Rodriguez-Gonzalez A, Garcia-Cambero D J Med Syst. 2025; 49(1):33.
PMID: 40035926 DOI: 10.1007/s10916-025-02154-7.
A systematic review on artificial intelligence approaches for smart health devices.
Aversano L, Iammarino M, Mancino I, Montano D PeerJ Comput Sci. 2024; 10:e2232.
PMID: 39650514 PMC: 11623213. DOI: 10.7717/peerj-cs.2232.
Jiang Z, Bakker O, Bartolo P Sensors (Basel). 2024; 24(17).
PMID: 39275645 PMC: 11398138. DOI: 10.3390/s24175734.
Glyde H, Morgan C, Wilkinson T, Nabney I, Dodd J J Med Internet Res. 2024; 26:e52143.
PMID: 39250789 PMC: 11420610. DOI: 10.2196/52143.
Chen X, Zhang H, Li Z, Liu S, Zhou Y JMIR Mhealth Uhealth. 2024; 12:e56226.
PMID: 39024559 PMC: 11294786. DOI: 10.2196/56226.