• DocumentCode
    3106764
  • Title

    Real-Time ECG Signal Feature Extraction for the Proposition of Abnormal Beat Detection - Periodical Signal Extraction

  • Author

    Szczepanski, Adam ; Saeed, Khalid

  • Author_Institution
    Fac. of Phys. & Appl. Comput. Sci., AGH Univ. of Sci. & Technol., Kraków, Poland
  • fYear
    2013
  • fDate
    5-7 July 2013
  • Firstpage
    261
  • Lastpage
    266
  • Abstract
    This paper presents a novel algorithm for ECG signal feature extraction and proposes a solution for detection of abnormal beats. The main goal is to extract signal and heartbeat parameters by using local extreme values and their dependences. This produces the averaged heartbeat which is used to analyze the signal in real time to detect anomalies. The main advantages of our approach are fast computation and portability between software development platforms. The main disadvantage is the need of clear fragments of samples for the training of the algorithm. Experimental results indicate the proposed system is efficient when compared to other models.
  • Keywords
    electrocardiography; feature extraction; medical signal detection; abnormal beat detection; anomaly detection; heartbeat parameters; local extreme values; periodical signal extraction; real-time ECG signal feature extraction; signal analysis; software development platform portability; Algorithm design and analysis; Electrocardiography; Heart beat; Medical services; Real-time systems; Software; Software algorithms; Biomedical signal processing; Electrocardiography; Signal analysis; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biometrics and Kansei Engineering (ICBAKE), 2013 International Conference on
  • Conference_Location
    Tokyo
  • Type

    conf

  • DOI
    10.1109/ICBAKE.2013.51
  • Filename
    6603513