• DocumentCode
    2716322
  • Title

    Optimized R peak detection algorithm for ultra low power ECG systems

  • Author

    Shrestha, Sachin ; Torfs, Tom ; Kim, Hyejung ; Yazicioglu, Refet Firat ; Romero, Inaki ; Buxi, Dilpreet ; Berset, Torfinn ; Altini, Marco

  • Author_Institution
    Heterogeneous Integrated Microsyst. Dept., imec, Leuven, Belgium
  • fYear
    2011
  • fDate
    10-12 Nov. 2011
  • Firstpage
    225
  • Lastpage
    228
  • Abstract
    In this paper, an optimized R peak detection algorithm with a high level of accuracy that can be implemented using very low power consumption is proposed. The accuracy of the algorithm is evaluated against the MIT-BIH arrhythmia database, giving an average sensitivity of 99.22% and positive predictivity of 99.86%, as well as against imec´s database with ambulatory data, giving an average sensitivity of 99.77% and positive predictivity of 99.82%. The power consumption of the algorithm is estimated by implementation in a commercial low power microcontroller (TI MSP430) to 71.42 μW. The algorithm has been tested in a hardware system using applied signals at varying signal to noise ratio as well as on human volunteers.
  • Keywords
    electrocardiography; medical image processing; medical signal processing; microcontrollers; optimisation; power consumption; MIT-BIH arrhythmia database; ambulatory data; hardware system; imec database; microcontroller; optimized R peak detection algorithm; power 71.42 muW; power consumption; ultralow power ECG systems; Application specific integrated circuits; Continuous wavelet transforms; Databases; Detection algorithms; Electrocardiography; Power demand; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Circuits and Systems Conference (BioCAS), 2011 IEEE
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-1-4577-1469-6
  • Type

    conf

  • DOI
    10.1109/BioCAS.2011.6107768
  • Filename
    6107768