• DocumentCode
    1217743
  • Title

    An Automated System for ST Segment and Arrhythmia Analysis in Exercise Radionuclide Ventriculography

  • Author

    Hsia, Peng-Wie ; Jenkins, Janice M. ; Shimoni, Yair ; Gage, Kevin P. ; Santinga, John T. ; Pitt, Bertram

  • Author_Institution
    Department of Electrical Engineering and Computer Science, University of Michigan
  • Issue
    6
  • fYear
    1986
  • fDate
    6/1/1986 12:00:00 AM
  • Firstpage
    585
  • Lastpage
    593
  • Abstract
    A computer-based system for interpretation of the electrocardiogram (ECG) in the diagnosis of arrhythmia and ST segment abnormality in an exercise system is presented. The system was designed for inclusion in a gamma camera so that ECG diagnosis could be combined with the diagnostic capability of radionuclide ventriculography. Digitized data are analyzed in a beat-by-beat mode and a contextual diagnosis of underlying rhythm is provided. Each beat is assigned a beat code based on a combination of waveform analysis and RR interval measurement. The waveform analysis employs a new correlation coefficient formula which corrects for baseline wander. Selective signal averaging, in which only normal beats are included, is done for an improved signal-to-noise ratio prior to ST segment analysis. Template generation, R wave detection, QRS window size, baseline correction, and continuous updating of heart rate have all been automated. ST level and slope measurements are computed on signal-averaged data. Arrhythmia analysis of 13 passages of abnormal rhythm by computer was found to be correct in 98.4 percent of all beats. 25 passages of exercise data, 1-5 min in length, were evaluated by the cardiologist and found to be in agreement in 95.8 percent in measurements of ST level and 91.7 percent in measurements of ST slope.
  • Keywords
    Cameras; Cardiology; Data analysis; Electrocardiography; Heart rate; Heart rate detection; Length measurement; Rhythm; Signal analysis; Signal to noise ratio; Arrhythmias, Cardiac; Biomedical Engineering; Biometry; Electroencephalography; Exercise Test; Humans; Software;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.1986.325840
  • Filename
    4122347