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    基于非線性理論的ECG 信號多重分形特性譜研究
    來源: | 作者: | 發布時間:2014-4-15 17:52:56

    基于非線性理論的ECG 信號多重分形特性譜研究
    (中國礦業大學計算機科學與技術學院,江蘇 徐州 221116)
    摘要:生理信號屬非平穩時變信號。因此,采用非線性動力學方法能更好的揭示其特性和機理。本文以多重分形方法,詳細研究了大量樣本同步十二導聯心電圖(ECG)信號的奇異譜面積和質量指數譜曲率,發現各種人群該特征值有較大差異,代表了不同含義。研究發現,健康年輕人ECG 的奇異譜面積十二導均值最大、心梗患者最小,其他人群處于中等大小水平。表明健康人生理系統處于最佳狀態,其ECG 信號非線性動力學復雜程度也最高。隨著年齡增長,人體自主神經的自律控制功能逐漸減弱,由多重分形趨向單重分形,人的ECG信號奇異譜面積十二導均值在一定程度上反映了人體自主神經控制的強弱。另外,健康人ECG 信號的質量指數譜曲率(絕對值)最小,CHF 和VF 患者依次增大。本文研究和結論期望為早期診斷和臨床應用提供有價值的信息。
    Research of ECG multifractal characteristic spectrum based on nonlinear dynamic theorey
    YANG Xiaodong
    (School of Computer Science and Technology, China University of Mining and Technology,JiangSu XuZhou 221116)
    Abstract: Physiological signal belongs to nonstationary and time-variant signal. Thus, Nonlinear dynamic theories can be better to disclose its characteristic and mechanism. In this paper, multifractal approach is used to research the singularity spectrum area and mass exponent spectrum curvature of synchronous 12-lead ECG signals from a largr test set. We find this
    eigenvalue is not all the same to the kinds of crowd, and it represents different implications. Among this, the mean value of 12-lead singularity spectrum area from healthy young man is the largest and this value becomes the minimum when it comes to the Myocardial Infarction (MI) sufferer. As to the other crowds, this value is wholly at the middle level. It indicates that the physiological system of healthy young man is at the best status. We also find the self-discipline control of human autonomic nervous system weakens gradually when people get older. It tends to turn to monofractality from multifractality. Thus, the 12-lead mean value of singularity spectrum area of human ECG signal can reflect the self-discipline control status of human autonomic nervous to some degree. In addition, the mass exponent spectrum curvature from healthy man is the least and the value from CHF anf VF sufferer increase accordingly. We expect our research and conclusion can provide some information to early diagnosis and clinical application.
    Keywords: ECG; Nonlinear; Multifractality; Singularity spectrum; Mass exponent spectrum