• DocumentCode
    3549354
  • Title

    Approximations to magic: finding unusual medical time series

  • Author

    Lin, Jessica ; Keogh, Eamonn ; Fu, Ada ; Van Herle, Helga

  • Author_Institution
    California Univ., Riverside, CA, USA
  • fYear
    2005
  • fDate
    23-24 June 2005
  • Firstpage
    329
  • Lastpage
    334
  • Abstract
    In this work we introduce the new problem of finding time series discords. Time series discords are subsequences of longer time series that are maximally different to all the rest of the time series subsequences. They thus capture the sense of the most unusual subsequence within a time series. While the brute force algorithm to discover time series discords is quadratic in the length of the time series, we show a simple algorithm that is 3 to 4 orders of magnitude faster than brute force, while guaranteed to produce identical results.
  • Keywords
    approximation theory; electrocardiography; time series; ECG; approximation; force algorithm; medical time series; time sequence; Biomedical equipment; Data mining; Detectors; Electrocardiography; Euclidean distance; Heart rate variability; Humans; Medical services; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems, 2005. Proceedings. 18th IEEE Symposium on
  • ISSN
    1063-7125
  • Print_ISBN
    0-7695-2355-2
  • Type

    conf

  • DOI
    10.1109/CBMS.2005.34
  • Filename
    1467711