搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

多尺度多变量模糊熵分析

李鹏 刘澄玉 李丽萍 纪丽珍 于守元 刘常春

引用本文:
Citation:

多尺度多变量模糊熵分析

李鹏, 刘澄玉, 李丽萍, 纪丽珍, 于守元, 刘常春

Multiscale multivariate fuzzy entropy analysis

Li Peng, Liu Cheng-Yu, Li Li-Ping, Ji Li-Zhen, Yu Shou-Yuan, Liu Chang-Chun
PDF
导出引用
  • 多尺度多变量样本熵评价同步多通道数据的多变量复杂度, 是非线性动态相互关系的一种反映, 但其统计稳定性差, 且不适用于非线性非平稳信号. 研究利用模糊隶属度函数代替模式相似判断的硬阈值准则, 并分析模糊隶属度函数形式的影响; 研究利用多变量经验模态分解算法进行多尺度化, 并对比其处理效果. 仿真试验表明, 模糊隶属度函数的引入可以有效提高算法的统计稳定性, 所构造的物理模糊隶属度函数的性能最为显著; 基于多变量经验模态分解算法的多尺度化过程可更有效地捕获信号的不同尺度成分, 从而更敏感地区分具有不同复杂度的信号. 对临床试验数据的分析支持以上结论, 且结果提示随着年龄增加或心脏疾病的发生, 心率变异性和心脏舒张间期变异性的多变量复杂度以不同的方式降低: 年龄增加会使低尺度熵值降低, 表示近程相关性的丢失; 而心脏疾病会同时影响各个尺度的熵值, 即同时丢失了近程和长时相关性. 该结论可用于指导心血管疾病的无创预警研究.
    Multiscale multivariate sample entropy can test the multivariate complexity, which is accepted as a kind of reflection of nonlinear dynamical interactions in multichannel data. It is however relatively unstable due to the rigid ranking scheme used in comparison among different patterns. It is not applicable to the nonlinear and non-stationary data because the multiscale framework used is in fact handled by moving average succeeded by down-sampling, which actually has a premise of stationary data. We substitute a fuzzy membership function for the original rigid one and compare the performances of different kinds of fuzzy membership functions. In addition, we employ the multivariate empirical mode decomposition (MEMD) to capture different scales. Results show that the substitution of fuzzy membership function brings in significant stability. It is much more obvious by using the introduced physical fuzzy membership function (PFMF). Also MEMD could capture scales more robustly. In conclusion, the introduced PFMF- and MEMD-based MMFE perform best. Final analysis on the interactions between heart rate variability (HRV) and heart diastolic time interval variability (DIV) validates it. In addition, the results show that the multivariate complexity between HRV and DIV decreases in aging or heart failure group but in a distinctly different decreasing manner–it deceased at low scales with aging, indicating a loss of short-range correlation but both at low and high scales with heart failure, which shows the losses of both short- and long-range correlations. Studies in noninvasive detection of cardiovascular diseases should benefit from the above conclusions.
    • 基金项目: 国家自然科学基金青年科学基金(批准号: 61201049)、山东大学研究生自主创新基金(批准号: yzc12082)、山东省优秀中青年科学家科研奖励基金(批准号: BS2012DX019)和中国博士后科学基金 (批准号:2013M530323)资助的课题.
    • Funds: Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 61201049), the Graduate Independent Innovation Foundation of Shandong University, China (Grant No. yzc12082), the Excellent Young Scientist Awarded Foundation of Shandong Province, China (Grant No. BS2012DX019), and the China Postdoctoral Science Foundation (Grant No. 2013M530323).
    [1]

    Ahmed M U, Mandic D P 2011 Phys. Rev. E 84 061918

    [2]

    Pincus S M 1991 Proc. Nat. Acad. Sci. U.S.A. 88 2297

    [3]

    Richman J S, Moorman J R 2000 Am. J. Physiol. Heart. Circ. Physiol. 278 H2039

    [4]

    Cao L, Mees A, Judd K 1998 Physica D 121 75

    [5]

    Costa M, Goldberger A L, Peng C K 2002 Phys. Rev. Lett. 89 068102

    [6]

    Ahmed M U, Li L, Cao J, Mandic D P 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Boston, Massachusetts, USA, Aug. 30-Sep. 3, 2011 p810

    [7]

    Ahmed M U, Mandic D P 2012 IEEE Signal Process Lett. 19 91

    [8]

    Looney D, Ahmed M U, Mandic D P 2012 Natural Intelligence: the INNS Magazine 1 40

    [9]

    Li P, Liu C Y, Wang X P, Li L P, Yang L, Chen Y C, Liu C C 2013 Med. Biol. Eng. Comput. 58 581

    [10]

    Chen W T, Zhuang J, Yu W X, Wang Z Z 2009 Med. Eng. Phys. 31 61

    [11]

    Xiong G L, Zhang L, Liu H S, Zou H J, Guo W Z 2010 J. Zhejiang University-Science A 11 270

    [12]

    Chen X J, Li Z, Bai B M, Pan W, Chen Q H 2011 J. Electron. Inform. Tech. 33 1198 (in Chinese) [陈小军, 李赞, 白宝明, 潘玮, 陈清华 2011 电子与信息学报 33 1198]

    [13]

    Sun K H, He S B, Yin L Z, A D L·Duo L K 2012 Acta Phys. Sin. 61 130507 (in Chinese) [孙克辉, 贺少波, 尹林子, 阿地力·多力坤 2012 物理学报 61 130507]

    [14]

    Liu C Y, Li K, Zhao L N, Liu F, Zheng D C, Liu C C, Liu S T 2013 Comput. Biol. Med. 43 100

    [15]

    Nikulin V V, Brismar T 2004 Phys. Rev. Lett. 92 089803

    [16]

    Valencia J F, Porta A, Vallverdu M, Claria F, Baranowski R, Orlowska-Baranowska E, Caminal P 2009 IEEE Trans. Biomed. Eng. 56 2202

    [17]

    Huang N E, Shen Z, Long S R, Wu M C, Shih H H, Zheng Q, Yen N C, Tung C C, Liu H H 1998 Proc. R. Soc. London A 454 903

    [18]

    Amoud H, Snoussi H, Hewson D, Doussot M, Duchene J 2007 IEEE Signal Process Lett. 14 297

    [19]

    Rehman N, Mandic D P 2010 Proc. R. Soc. London, Ser. A 466 1291

    [20]

    Hu M, Liang H 2012 IEEE Trans. Biomed. Eng. 59 12

    [21]

    Ahmed M U, Rehman N, Looney D, Rutkowski T M, Mandic D P 2012 Bull. Pol. Ac.: Tech. 60 433

    [22]

    Lu S, Chen X, Kanters J K, Solomon I C, Chon K H 2008 IEEE Trans. Biomed. Eng. 55 1966

    [23]

    Liu C Y, Liu C C, Shao P, Li L P, Sun X, Wang X P, Liu F 2011 Physiol. Meas. 32 167

    [24]

    Kaplan D T, Furman M I, Pincus S M, Ryan S M, Lipsitz L A, Goldberger A L 1991 Biophys. J. 59 945

    [25]

    Iyengar N, Peng C K, Morin R, Goldberger A L, Lipsitz L A 1996 Am. J. Physiol. Regulatory Integrative Comp. Physiol. 271 R1078

    [26]

    Liu C Y, Liu C C, Li L P, Zhang Q G, Li B 2009 3rd International Conference on Bioinformatics and Biomedical Engineering Beijing, China, June 11-13, 2009 p2609

    [27]

    Li P, Liu C C, Zhang M, Che W B, Li J 2011 Acta Biophys. Sin. 27 222 (in Chinese) [李鹏, 刘常春, 张明, 车文彪, 李键 2011 生物物理学报 27 222]

  • [1]

    Ahmed M U, Mandic D P 2011 Phys. Rev. E 84 061918

    [2]

    Pincus S M 1991 Proc. Nat. Acad. Sci. U.S.A. 88 2297

    [3]

    Richman J S, Moorman J R 2000 Am. J. Physiol. Heart. Circ. Physiol. 278 H2039

    [4]

    Cao L, Mees A, Judd K 1998 Physica D 121 75

    [5]

    Costa M, Goldberger A L, Peng C K 2002 Phys. Rev. Lett. 89 068102

    [6]

    Ahmed M U, Li L, Cao J, Mandic D P 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Boston, Massachusetts, USA, Aug. 30-Sep. 3, 2011 p810

    [7]

    Ahmed M U, Mandic D P 2012 IEEE Signal Process Lett. 19 91

    [8]

    Looney D, Ahmed M U, Mandic D P 2012 Natural Intelligence: the INNS Magazine 1 40

    [9]

    Li P, Liu C Y, Wang X P, Li L P, Yang L, Chen Y C, Liu C C 2013 Med. Biol. Eng. Comput. 58 581

    [10]

    Chen W T, Zhuang J, Yu W X, Wang Z Z 2009 Med. Eng. Phys. 31 61

    [11]

    Xiong G L, Zhang L, Liu H S, Zou H J, Guo W Z 2010 J. Zhejiang University-Science A 11 270

    [12]

    Chen X J, Li Z, Bai B M, Pan W, Chen Q H 2011 J. Electron. Inform. Tech. 33 1198 (in Chinese) [陈小军, 李赞, 白宝明, 潘玮, 陈清华 2011 电子与信息学报 33 1198]

    [13]

    Sun K H, He S B, Yin L Z, A D L·Duo L K 2012 Acta Phys. Sin. 61 130507 (in Chinese) [孙克辉, 贺少波, 尹林子, 阿地力·多力坤 2012 物理学报 61 130507]

    [14]

    Liu C Y, Li K, Zhao L N, Liu F, Zheng D C, Liu C C, Liu S T 2013 Comput. Biol. Med. 43 100

    [15]

    Nikulin V V, Brismar T 2004 Phys. Rev. Lett. 92 089803

    [16]

    Valencia J F, Porta A, Vallverdu M, Claria F, Baranowski R, Orlowska-Baranowska E, Caminal P 2009 IEEE Trans. Biomed. Eng. 56 2202

    [17]

    Huang N E, Shen Z, Long S R, Wu M C, Shih H H, Zheng Q, Yen N C, Tung C C, Liu H H 1998 Proc. R. Soc. London A 454 903

    [18]

    Amoud H, Snoussi H, Hewson D, Doussot M, Duchene J 2007 IEEE Signal Process Lett. 14 297

    [19]

    Rehman N, Mandic D P 2010 Proc. R. Soc. London, Ser. A 466 1291

    [20]

    Hu M, Liang H 2012 IEEE Trans. Biomed. Eng. 59 12

    [21]

    Ahmed M U, Rehman N, Looney D, Rutkowski T M, Mandic D P 2012 Bull. Pol. Ac.: Tech. 60 433

    [22]

    Lu S, Chen X, Kanters J K, Solomon I C, Chon K H 2008 IEEE Trans. Biomed. Eng. 55 1966

    [23]

    Liu C Y, Liu C C, Shao P, Li L P, Sun X, Wang X P, Liu F 2011 Physiol. Meas. 32 167

    [24]

    Kaplan D T, Furman M I, Pincus S M, Ryan S M, Lipsitz L A, Goldberger A L 1991 Biophys. J. 59 945

    [25]

    Iyengar N, Peng C K, Morin R, Goldberger A L, Lipsitz L A 1996 Am. J. Physiol. Regulatory Integrative Comp. Physiol. 271 R1078

    [26]

    Liu C Y, Liu C C, Li L P, Zhang Q G, Li B 2009 3rd International Conference on Bioinformatics and Biomedical Engineering Beijing, China, June 11-13, 2009 p2609

    [27]

    Li P, Liu C C, Zhang M, Che W B, Li J 2011 Acta Biophys. Sin. 27 222 (in Chinese) [李鹏, 刘常春, 张明, 车文彪, 李键 2011 生物物理学报 27 222]

  • [1] 杨孝敬, 杨阳, 李淮周, 钟宁. 基于模糊近似熵的抑郁症患者静息态功能磁共振成像信号复杂度分析. 物理学报, 2016, 65(21): 218701. doi: 10.7498/aps.65.218701
    [2] 侯旺, 梅风华, 陈国军, 邓喜文. 基于背景最佳滤波尺度的红外图像复杂度评价准则. 物理学报, 2015, 64(23): 234202. doi: 10.7498/aps.64.234202
    [3] 侯公羽, 梁荣, 孙磊, 刘琳, 龚砚芬. 基于多变量混沌时间序列的煤矿斜井TBM施工动态风险预测. 物理学报, 2014, 63(9): 090505. doi: 10.7498/aps.63.090505
    [4] 薛春芳, 侯威, 赵俊虎, 王式功. 集合经验模态分解在区域降水变化多尺度分析及气候变化响应研究中的应用. 物理学报, 2013, 62(10): 109203. doi: 10.7498/aps.62.109203
    [5] 王新迎, 韩敏. 基于极端学习机的多变量混沌时间序列预测. 物理学报, 2012, 61(8): 080507. doi: 10.7498/aps.61.080507
    [6] 高光勇, 蒋国平. 采用优化极限学习机的多变量混沌时间序列预测. 物理学报, 2012, 61(4): 040506. doi: 10.7498/aps.61.040506
    [7] 孙克辉, 贺少波, 尹林子, 阿地力·多力坤. 模糊熵算法在混沌序列复杂度分析中的应用. 物理学报, 2012, 61(13): 130507. doi: 10.7498/aps.61.130507
    [8] 陈志旺, 刘文龙. Rössler超混沌系统多变量广义预测控制快速算法. 物理学报, 2011, 60(5): 050506. doi: 10.7498/aps.60.050506
    [9] 陈小军, 李赞, 白宝明, 蔡觉平. 一种确定混沌伪随机序列复杂度的模糊关系熵测度. 物理学报, 2011, 60(6): 064215. doi: 10.7498/aps.60.064215
    [10] 张春涛, 马千里, 彭宏, 姜友谊. 基于条件熵扩维的多变量混沌时间序列相空间重构. 物理学报, 2011, 60(2): 020508. doi: 10.7498/aps.60.020508
    [11] 徐艳, 董江涛, 王少华. 基于模糊隶属度的图像空间距离修正插值算法. 物理学报, 2010, 59(11): 7535-7539. doi: 10.7498/aps.59.7535
    [12] 张勇, 关伟. 基于最大Lyapunov指数的多变量混沌时间序列预测. 物理学报, 2009, 58(2): 756-763. doi: 10.7498/aps.58.756
    [13] 何 亮, 杜 磊, 庄奕琪, 李伟华, 陈建平. 金属互连电迁移噪声的多尺度熵复杂度分析. 物理学报, 2008, 57(10): 6545-6550. doi: 10.7498/aps.57.6545
    [14] 丛 蕊, 刘树林, 马 锐. 基于数据融合的多变量相空间重构方法. 物理学报, 2008, 57(12): 7487-7493. doi: 10.7498/aps.57.7487
    [15] 卢 山, 王海燕. 多变量时间序列最大李雅普诺夫指数的计算. 物理学报, 2006, 55(2): 572-576. doi: 10.7498/aps.55.572
    [16] 侯 威, 封国林, 董文杰. 基于复杂度分析logistic映射和Lorenz模型的研究. 物理学报, 2005, 54(8): 3940-3946. doi: 10.7498/aps.54.3940
    [17] 董恩增, 陈增强, 袁著祉. 混沌系统的自适应多变量广义预测控制与同步. 物理学报, 2005, 54(10): 4578-4583. doi: 10.7498/aps.54.4578
    [18] 傅 鹏, 刘正之, 罗家融, 夏海燕. HT-7铁芯超导托卡马克等离子体电流和水平位移多变量反馈控制. 物理学报, 1999, 48(4): 685-691. doi: 10.7498/aps.48.685
    [19] 胡岗, 王生贵. 具有多稳势的多变量Fokker-Planck方程非定态问题. 物理学报, 1986, 35(6): 771-778. doi: 10.7498/aps.35.771
    [20] 陈正雄, 霍裕平. 多变量Master方程及其波动解. 物理学报, 1983, 32(3): 285-293. doi: 10.7498/aps.32.285
计量
  • 文章访问数:  7231
  • PDF下载量:  1544
  • 被引次数: 0
出版历程
  • 收稿日期:  2013-02-01
  • 修回日期:  2013-02-24
  • 刊出日期:  2013-06-05

/

返回文章
返回