Title page for etd-0716104-123628


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URN etd-0716104-123628
Author Chin-yuan Guo
Author's Email Address No Public.
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Department Applied Mathematics
Year 2003
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Studies in the electrocardiogram monitoring indices.
Date of Defense 2004-07-09
Page Count 47
Keyword
  • RR-interval
  • I(d)-Process EWRMS control chart
  • I(d)-Process EWMA control chart
  • GARCH model
  • Hurst parameter
  • Abstract An recent finding shows that heart rate data possess self-similar property, which is characterized by a parameter H, as well as a long range dependent parameter d. We estimate H by the EBP(Embedded Branching Process) method to derive the fractional parameter d in the first part. The heart rate and R-R interval data are found to have high differencing parameter(d=0.8 ~0.9) and against the
    normality assumption. Thus the heart rate and R-R interval data are first fractionally differenced of order 0.5 to achieve stationarity. In the second part, we analyze the
    RR-interval data on the physionet and obtain the long range
    parameters. After fractionally differencing 0.5 order, the EBP method is adapted to estimate the long range parameter d.
     
     The EWMA and EWRMS control charts of the I(d) processes are constructed to monitor the heart rate mean level and variability, respectively for the 18 RR-interval data sets from the physionet. For the EWMA control chart the out of control percentages are chosen to the nominal probability. However, the out of control percentages are affected by the skewness and kurtosis of the process distribution for the EWRMS control carts. Generally speaking, the I(d)-EWMA and I(d)-EWRMS control charts provide a proper monitor system for heart rate mean level and variability.
    Advisory Committee
  • Mong-Na Lo Huang - chair
  • none - co-chair
  • Grace Shwu-Rong Shieh - co-chair
  • Mei-hui Guo - advisor
  • Files
  • etd-0716104-123628.pdf
  • indicate access worldwide
    Date of Submission 2004-07-16

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