• DocumentCode
    2510825
  • Title

    Monitoring patient status through principal components analysis

  • Author

    Buemi, M. ; Macerata, A. ; Taddei, A. ; Varanini, M. ; Emdin, M. ; Marchesi, C.

  • Author_Institution
    Dept. of Comput. Eng., Florence Univ., Italy
  • fYear
    1991
  • fDate
    23-26 Sep 1991
  • Firstpage
    385
  • Lastpage
    388
  • Abstract
    Principal component (PC) analysis allows the definition of a transform with optimum coefficients. The PCs of several time series of the features, extracted from the electrocardiograms (ECGs) or the arterial pressure, are calculated. With the assumption that the statistical structure of intra-patient data is going to be stable, the basis functions of the transforms are captured once, during a basal interval. A function has been derived from the two first PCs, which represent an evidence function to be used both for a compact visual presentation and for the design of an algorithm for automatic episode detection. The evaluation of the visual presentation has been based on the annotated signal of the European ST-T database
  • Keywords
    electrocardiography; haemodynamics; patient monitoring; European ST-T database; algorithm design; annotated signal; arterial pressure; automatic episode detection; basal interval; electrocardiograms; intra-patient data; optimum coefficients; principal components analysis; statistical structure; transform definition; visual presentation; Algorithm design and analysis; Biomedical monitoring; Blood pressure; Computerized monitoring; Data mining; Databases; Electrocardiography; Feature extraction; Patient monitoring; Principal component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology 1991, Proceedings.
  • Conference_Location
    Venice
  • Print_ISBN
    0-8186-2485-X
  • Type

    conf

  • DOI
    10.1109/CIC.1991.169125
  • Filename
    169125