• DocumentCode
    2125877
  • Title

    Adaptive time-frequency ECG analysis

  • Author

    Chouvarda, I. ; Maglaveras, N. ; Pappas, C.

  • Author_Institution
    Lab of Med. Informdtics, Aristotle Univ., Thessaloniki, Greece
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    265
  • Lastpage
    268
  • Abstract
    Non-stationary analysis of ECG using the Choi-Williams (CW) distribution (H. Choi & W.J. Williams, 1989) is presented. An analysis was carried out on subjects with acute myocardial infarction (AMI) who had undergone thrombolysis, in V1 Holder recordings. Two groups of patients were looked at: successfully and unsuccessfully thrombolysed patients. The time-frequency map generated by the CW transform (a modification of the Wigner-Ville transform) was divided into nine areas relevant to ECG features. Characteristic parameters were extracted from each area, and linear discriminant analysis was applied to these parameters, leading to a prediction index. Applying the method to ECGs six hours after lysis, the successfully thrombolysed patients were shown to be distinct from the unsuccessfully thrombolysed ones
  • Keywords
    Wigner distribution; adaptive signal processing; electrocardiography; medical signal processing; time-frequency analysis; transforms; Choi-Williams distribution; Choi-Williams transform; ECG features; V1 Holder recordings; Wigner-Ville transform; acute myocardial infarction; adaptive time-frequency ECG analysis; characteristic parameter extraction; linear discriminant analysis; nonstationary analysis; prediction index; thrombolysis; time-frequency map; Ambient intelligence; Angioplasty; Biomedical informatics; Cardiology; Electrocardiography; Linear discriminant analysis; Linear regression; Robustness; Testing; Time frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology 2001
  • Conference_Location
    Rotterdam
  • ISSN
    0276-6547
  • Print_ISBN
    0-7803-7266-2
  • Type

    conf

  • DOI
    10.1109/CIC.2001.977643
  • Filename
    977643