In-time prognosis based on swarm intelligence for home-care monitoring: A case study on pulmonary disease

Pasquale Arpaia, Carlo Manna, Giuseppe Montenero, Giovanni D'Addio

Research output: Contribution to journalArticle

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 languageEnglish
Article number5782924
Pages (from-to)692-698
Number of pages7
JournalIEEE Sensors Journal
Volume12
Issue number3
DOIs
Publication statusPublished - 2012

Keywords

  • Computer-aided diagnosis
  • fuzzy logic
  • particle swarm optimization (PSO)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Instrumentation

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