ASIA unversity:Item 310904400/9559
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    题名: Fuzzy C-Means Clustering for Myocardial Ischemia Estimation with Pulse Waveform Analysis.Biomedical Engineering
    作者: Shing-Hong Liu;Kang-Ming Chang;Chu-Chang Tyan
    关键词: Fuzzy C-means;Form Factor;Harmonic;Myocardial Ischemia;Pulse Waveform Analysis.
    日期: 2009
    上传时间: 2010-05-12 01:12:17 (UTC+0)
    出版者: Asia University
    摘要: The purpose of this study is to build an automatic disease classification system
    using pulse waveform analysis, based on a Fuzzy C-means clustering algorithm. A
    self designed three-axis mechanism was used to detect the optimal site to accurately
    measure the pressure pulse waveform (PPW). Considering the artery as a cylinder,
    the sensor should detect the PPW with the lowest possible distortion and hence an
    analysis of the vascular geometry and an arterial model were used to design a standard
    positioning procedure based on the arterial diameter changed waveform for the X- and
    Z-axes. A fuzzy C-means algorithm was used to estimate the myocardial ischemia
    symptoms in 35 elderly subjects with the PPW of the radial artery. Two type
    parameters are used to make the features, one is a harmonic value of Fourier transfer,
    and the other is a form factor value. A receiver operating characteristics curve is
    used to determine the optimal decision function. The harmonic feature vector (H2,
    H3, H4) performed at the level of 69% for sensitivity and 100% for specificity while
    the form factor feature vector (LFF, RFF) performed at the level of 100% for
    sensitivity and 53% for specificity. The modified clustering algorithm based on
    FCM and ROC curve is an efficient way for estimating the risk of myocardial
    ischemia based on the exercise ECG.
    關聯: Applications, Basis and Communications 21(2):139-147
    显示于类别:[光電與通訊學系] 期刊論文

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