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Coupling analysis of multivariate bioelectricity signal based symbolic partial mutual information

Zhang Mei Cui Chao Ma Qian-Li Gan Zong-Liang Wang Jun

Coupling analysis of multivariate bioelectricity signal based symbolic partial mutual information

Zhang Mei, Cui Chao, Ma Qian-Li, Gan Zong-Liang, Wang Jun
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  • Symbolic partial mutual information is proposed in this paper, which is based on partial mutual information. This algorithm can be used to analyse the coupling between multivariate time series. We use this method to treat and analyse the sleeping multivariate bioelectricity signal (MBS) and wake one, it turns out that the coupling of wake MBS is obviously bigger than that of sleeping MBS. Finally hypothesis testing is done to prove that this method works and the average energy dissipation can be used as a parameter to detect nonequilibrium.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 61271082, 61201029, 61102094), and the Natural Science Foundation of Jiangsu Province, China (Grant Nos. BK2011759, BK2011565).
    [1]

    Fang X L, Jiang Z L 2007 Acta Phys. Sin. 56 7330 (in Chinese) [方小玲, 姜宗来 2007 物理学报 56 7330]

    [2]

    Meng Q F, Zhou W D, Chen Y H, Peng Y H 2010 Acta Phys. Sin. 59 123 (in Chinese) [孟庆芳, 周卫东, 陈月辉, 彭玉华 2010物理学报 59 123]

    [3]

    Ma Q L, Bian C H, Wang J 2010 Acta Phys. Sin. 59 4480 (in Chinese) [马千里, 卞春华, 王俊 2010物理学报 59 4480]

    [4]

    Bian H R, Wang J, Han C X, Deng B, Wei X L, Che Y Q 2011 Acta Phys. Sin. 60 118701 (in Chinese) [边洪瑞, 王江, 韩春晓, 邓斌, 魏熙乐, 车艳秋 2011 物理学报 60 118701]

    [5]

    Wang J, Ma Q L 2008 Chin. Phys. B 17 4424

    [6]

    Hsu W Y 2012 Int. J. Neural Syst. 22 51

    [7]

    Nevado-Holgado A J, Marten F, Richardson M P, Terry J R 2012 Neuro Image 59 2374

    [8]

    Petrantonakis P C, Hadjileontiadis L J 2012 IEEE Trans. Signal Proces. 60 2604

    [9]

    Thatcher R W 2012 Dev. Neuropsychol. 37 476

    [10]

    Wang J, Yu Z F 2012 Chin. Phys. B 21 018702

    [11]

    Wang J, Zhao D Q 2012 Chin. Phys. B 21 028703

    [12]

    Musselman M, Djurdjanovic D 2012 Exp. Syst. Appl. 39 11413

    [13]

    Shao S Y, Shen K Q, Yu K, Wilder-Smith E P V, Li X P 2012 Clin. Neurophysiol. 123 2042

    [14]

    Tarokh L, van Reen E, Acebo C, Le Bourgeois M, Seifer R, Fallone G, Carskadon M A 2012 Alcohol.-Clin. Exp. Res. 36 1530

    [15]

    Wang R F, Zhang J H, Zhang Y, Wang X Y 2012 Biomed. Signal Proc. Control 7 490

    [16]

    Orhan U, Hekim M, Ozer M 2012 J. Med. Syst. 36 2219

    [17]

    Acharya U R, Sree S V, Alvin A P C, Suri J S 2012 Exp. Syst. Appl. 39 9072

    [18]

    Siuly S, Li Y 2012 IEEE Trans. Neur. Syst. Reh. Eng. 20 526

    [19]

    Acharya U R, Molinari F, Sree S V, Chattopadhyay S, Ng K H, Suri J S 2012 Biomed. Signal Proc. Control. 7 401

    [20]

    Frenzel S, Pompe B 2007 Phys. Rev. Lett. 99 204101

    [21]

    Staniek M, Lehnertz K 2008 Phys. Rev. Lett. 100 158101

    [22]

    Li J, Ning X B 2006 Phys. Rev. E 73 052902

    [23]

    Wessel N, Ziehmann C, Kurths J, Meyerfeldt U, Schirdewan A, Voss A 2000 Phys. Rev. E 61 733

    [24]

    Shen W, Wang J 2011 Acta Phys. Sin. 60 118702 (in Chinese) [沈韡, 王俊 2011 物理学报 60 118702]

  • [1]

    Fang X L, Jiang Z L 2007 Acta Phys. Sin. 56 7330 (in Chinese) [方小玲, 姜宗来 2007 物理学报 56 7330]

    [2]

    Meng Q F, Zhou W D, Chen Y H, Peng Y H 2010 Acta Phys. Sin. 59 123 (in Chinese) [孟庆芳, 周卫东, 陈月辉, 彭玉华 2010物理学报 59 123]

    [3]

    Ma Q L, Bian C H, Wang J 2010 Acta Phys. Sin. 59 4480 (in Chinese) [马千里, 卞春华, 王俊 2010物理学报 59 4480]

    [4]

    Bian H R, Wang J, Han C X, Deng B, Wei X L, Che Y Q 2011 Acta Phys. Sin. 60 118701 (in Chinese) [边洪瑞, 王江, 韩春晓, 邓斌, 魏熙乐, 车艳秋 2011 物理学报 60 118701]

    [5]

    Wang J, Ma Q L 2008 Chin. Phys. B 17 4424

    [6]

    Hsu W Y 2012 Int. J. Neural Syst. 22 51

    [7]

    Nevado-Holgado A J, Marten F, Richardson M P, Terry J R 2012 Neuro Image 59 2374

    [8]

    Petrantonakis P C, Hadjileontiadis L J 2012 IEEE Trans. Signal Proces. 60 2604

    [9]

    Thatcher R W 2012 Dev. Neuropsychol. 37 476

    [10]

    Wang J, Yu Z F 2012 Chin. Phys. B 21 018702

    [11]

    Wang J, Zhao D Q 2012 Chin. Phys. B 21 028703

    [12]

    Musselman M, Djurdjanovic D 2012 Exp. Syst. Appl. 39 11413

    [13]

    Shao S Y, Shen K Q, Yu K, Wilder-Smith E P V, Li X P 2012 Clin. Neurophysiol. 123 2042

    [14]

    Tarokh L, van Reen E, Acebo C, Le Bourgeois M, Seifer R, Fallone G, Carskadon M A 2012 Alcohol.-Clin. Exp. Res. 36 1530

    [15]

    Wang R F, Zhang J H, Zhang Y, Wang X Y 2012 Biomed. Signal Proc. Control 7 490

    [16]

    Orhan U, Hekim M, Ozer M 2012 J. Med. Syst. 36 2219

    [17]

    Acharya U R, Sree S V, Alvin A P C, Suri J S 2012 Exp. Syst. Appl. 39 9072

    [18]

    Siuly S, Li Y 2012 IEEE Trans. Neur. Syst. Reh. Eng. 20 526

    [19]

    Acharya U R, Molinari F, Sree S V, Chattopadhyay S, Ng K H, Suri J S 2012 Biomed. Signal Proc. Control. 7 401

    [20]

    Frenzel S, Pompe B 2007 Phys. Rev. Lett. 99 204101

    [21]

    Staniek M, Lehnertz K 2008 Phys. Rev. Lett. 100 158101

    [22]

    Li J, Ning X B 2006 Phys. Rev. E 73 052902

    [23]

    Wessel N, Ziehmann C, Kurths J, Meyerfeldt U, Schirdewan A, Voss A 2000 Phys. Rev. E 61 733

    [24]

    Shen W, Wang J 2011 Acta Phys. Sin. 60 118702 (in Chinese) [沈韡, 王俊 2011 物理学报 60 118702]

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  • Received Date:  12 October 2012
  • Accepted Date:  03 November 2012
  • Published Online:  20 March 2013

Coupling analysis of multivariate bioelectricity signal based symbolic partial mutual information

  • 1. Image Processing and Image Communications Key Laboratory, Nanjing University of Posts and Telecommunication, Nanjing 210003, China;
  • 2. Mechanical Engineering College, Zhengzhou University, Zhengzhou 450001, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant Nos. 61271082, 61201029, 61102094), and the Natural Science Foundation of Jiangsu Province, China (Grant Nos. BK2011759, BK2011565).

Abstract: Symbolic partial mutual information is proposed in this paper, which is based on partial mutual information. This algorithm can be used to analyse the coupling between multivariate time series. We use this method to treat and analyse the sleeping multivariate bioelectricity signal (MBS) and wake one, it turns out that the coupling of wake MBS is obviously bigger than that of sleeping MBS. Finally hypothesis testing is done to prove that this method works and the average energy dissipation can be used as a parameter to detect nonequilibrium.

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