• DocumentCode
    625078
  • Title

    Multi-data source fusion agent based method for ECG classification

  • Author

    Ben Boussada, Elhoucine ; Ben Ayed, Mounir ; Alimi, Adel M.

  • Author_Institution
    Nat. Sch. of Eng. of Sfax, Sfax, Tunisia
  • fYear
    2013
  • fDate
    20-22 Jan. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, we purpose to develop a system to aid in the diagnosis of anomalies cardiac signals (ECG). This system is based on data fusion and architected by using the multi-agents system for ECG classification. Therefore, the proposed system helps doctors to quickly and precisely diagnose a heart disease by examining only the class of the ECG beats. This system is tested on a MIT-BIH arrhythmia database.
  • Keywords
    diseases; electrocardiography; medical signal processing; multi-agent systems; sensor fusion; signal classification; ECG beats; ECG classification; MIT-BIH arrhythmia database; anomaly cardiac signal diagnosis; heart disease diagnosis; multiagent system; multidata source fusion agent-based method; Data integration; Databases; Electrocardiography; Feature extraction; Multi-agent systems; Neural networks; Training; ECG; MIT-BIH database; PSO; artificial intelligence; dam fusion; multi agent system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Applications Technology (ICCAT), 2013 International Conference on
  • Conference_Location
    Sousse
  • Print_ISBN
    978-1-4673-5284-0
  • Type

    conf

  • DOI
    10.1109/ICCAT.2013.6569167
  • Filename
    6569167
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=625078