Abstract
A swarm intelligence-based procedure to detect critical conditions of a patient, affected by a specific disease, at an early stage in absence of clinician, is proposed. The procedure is to be integrated inside a remote health care system for patients at home, where some physiological parameters related to a specific disease are being monitored. A significant variation in the monitored parameters can lead the patient to a critical state, thus the proposed method is aimed at predicting a possible future bad condition of the patient on the basis of past measurements. Moreover, different physiological parameters contribute to diverse degrees in dissimilar diseases; consequently, a swarm intelligence-based method is proposed for optimizing the weight of each parameter for a more accurate diagnosis. The proposed approach has been validated experimentally under the framework of the industrial research project Patient Diagnosis and Monitoring at Domicile (PADIAMOND: co-funded by EU and the company Filia srl, Caserta, Italy).
Original language | English |
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Article number | 5782924 |
Pages (from-to) | 692-698 |
Number of pages | 7 |
Journal | IEEE Sensors Journal |
Volume | 12 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2012 |
Keywords
- Computer-aided diagnosis
- fuzzy logic
- particle swarm optimization (PSO)
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Instrumentation