• DocumentCode
    2093247
  • Title

    Automatic QRS complex detection algorithm designed for a novel wearable, wireless electrocardiogram recording device

  • Author

    Nielsen, Dorthe B. ; Egstrup, Kenneth ; Branebjerg, Jens ; Andersen, G.B. ; Sorensen, Helge Bjarup Dissing

  • Author_Institution
    DTU Electr. Eng., Lyngby, Denmark
  • fYear
    2012
  • fDate
    Aug. 28 2012-Sept. 1 2012
  • Firstpage
    2913
  • Lastpage
    2916
  • Abstract
    We have designed and optimized an automatic QRS complex detection algorithm for electrocardiogram (ECG) signals recorded with the DELTA ePatch platform. The algorithm is able to automatically switch between single-channel and multi-channel analysis mode. This preliminary study includes data from 11 patients measured with the DELTA ePatch platform and the algorithm achieves an average QRS sensitivity and positive predictivity of 99.57% and 99.57%, respectively. The algorithm was also evaluated on all 48 records from the MIT-BIH Arrhythmia Database (MITDB) with an average sensitivity and positive predictivity of 99.63% and 99.63%, respectively.
  • Keywords
    body sensor networks; electrocardiography; medical signal detection; medical signal processing; DELTA ePatch platform; MIT-BIH Arrhythmia Database; MITDB; QRS sensitivity; automatic QRS complex detection algorithm; electrocardiogram; multichannel analysis mode; positive predictivity; single channel analysis mode; wearable wireless ECG recording device; Algorithm design and analysis; Databases; Detection algorithms; Electrocardiography; Feature extraction; Noise; Sensitivity; Algorithms; Electrocardiography; Humans; Wireless Technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4119-8
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2012.6346573
  • Filename
    6346573