| Peer-Reviewed

Nerve Electrical Signal Analysis Based on Matlab

Received: 23 February 2017     Accepted: 1 April 2017     Published: 18 April 2017
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Abstract

Action potential is one of the main ways to transmit information in the nervous system. In fact, a single electrode tends to record the activities of more than one neuron, therefore, the recorded signals need to be analyzed to get the single neuron discharge sequences. This paper separates and analyzes the nerve signals of rat dorsal root ganglion by the program written in Matlab and commercial data analysis system LabChart respectively. The results showed that both of them can achieve to separate the different amplitudes signal and conduct statistical analysis, but Matlab program is simple and can directly isolate different neural signals which is easy to understand and accept, it can also process the data according to their specific characteristics and get more consistent results to the reality, while LabChart can only get the results close to the reality. In addition, LabChart can be modified to get more practical analysis through the analysis of Matlab. In a conclusion, Matlab program can satisfy the need to deal with the data independently, and it can also work as helper to improve the results of a commercial software processing.

Published in International Journal of Neurologic Physical Therapy (Volume 3, Issue 2)
DOI 10.11648/j.ijnpt.20170302.12
Page(s) 11-16
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Nerve Electrical Signal, Action Potential, Interspike Interval, Data Statistics, Matlab Program

References
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[2] Christian L, Thomas W, Guenther Z, Unsupervised neural spike sorting for high-density microelectrode arrays with convolutive independent component analysis, Journal of neuroscience methods, 2016, 271: 1-13.
[3] Barnett AH, Magland JF, Greengard LF, Validation of neural spike sorting algorithms without ground-truth information, Journal of Neuroscience Methods, 2016, 264: 65–77.
[4] Michael S Lewicki. A review of methods for spike sorting: the detection and classification of neural action potentials, Network: Computation in Neural Systems, 1998, 9(4): 53-78.
[5] Han CX. Wang J. Che YQ. Liu YY. Nonlinear characteristics extraction from electrical signals of dorsal spinal nerveroot evoked by acupunctureat Zusanli point. Acta Phys. Sinica., 2010, 59: 5881-5888.
[6] Ren JF. The Virtual Instrument for Neural Signals Recording & Spike Sorting Based on Lab VIEW. Master Dissertation. Nanjing University of Aeronautics & Astronautics. 2008 (in Chinese)
[7] Su CK, Chiang CH, Lee CM, Fan YP, Ho CM, Shyu LY, Computational solution of spike overlapping using data-based subtraction algorithms to resolve synchronous sympathetic nerve discharge, Frontiers in computational neuroscience, 2013, 7(149): 1-19, doi: 10.3389/fncom.2013.00149
[8] Takahashi S. Sakurai Y. Tsukada M. Anzai Y. Classification of neuronal activities form tetrode recordings using independent component analysis. Neurocomputing. 2002, 49: 289-298.
[9] Letelier JC. Weber PP. Spike sorting based on discrete wavelet transform coefficients. Journal of neuroscience methods. 2000, 101(2): 93-106.
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[11] Jia XF. Zhang J. Chen TY. et al. Experimental study on harvesting the electrical signal of peripheral nerve at rabbits by intrafascicular microelectrodes. Chin J Hand Surg. 2002, 18 (4): 245-247 (in Chinese).
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  • APA Style

    Yao Wei, Wang Yiqiao. (2017). Nerve Electrical Signal Analysis Based on Matlab. International Journal of Neurologic Physical Therapy, 3(2), 11-16. https://doi.org/10.11648/j.ijnpt.20170302.12

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    ACS Style

    Yao Wei; Wang Yiqiao. Nerve Electrical Signal Analysis Based on Matlab. Int. J. Neurol. Phys. Ther. 2017, 3(2), 11-16. doi: 10.11648/j.ijnpt.20170302.12

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    AMA Style

    Yao Wei, Wang Yiqiao. Nerve Electrical Signal Analysis Based on Matlab. Int J Neurol Phys Ther. 2017;3(2):11-16. doi: 10.11648/j.ijnpt.20170302.12

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  • @article{10.11648/j.ijnpt.20170302.12,
      author = {Yao Wei and Wang Yiqiao},
      title = {Nerve Electrical Signal Analysis Based on Matlab},
      journal = {International Journal of Neurologic Physical Therapy},
      volume = {3},
      number = {2},
      pages = {11-16},
      doi = {10.11648/j.ijnpt.20170302.12},
      url = {https://doi.org/10.11648/j.ijnpt.20170302.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijnpt.20170302.12},
      abstract = {Action potential is one of the main ways to transmit information in the nervous system. In fact, a single electrode tends to record the activities of more than one neuron, therefore, the recorded signals need to be analyzed to get the single neuron discharge sequences. This paper separates and analyzes the nerve signals of rat dorsal root ganglion by the program written in Matlab and commercial data analysis system LabChart respectively. The results showed that both of them can achieve to separate the different amplitudes signal and conduct statistical analysis, but Matlab program is simple and can directly isolate different neural signals which is easy to understand and accept, it can also process the data according to their specific characteristics and get more consistent results to the reality, while LabChart can only get the results close to the reality. In addition, LabChart can be modified to get more practical analysis through the analysis of Matlab. In a conclusion, Matlab program can satisfy the need to deal with the data independently, and it can also work as helper to improve the results of a commercial software processing.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Nerve Electrical Signal Analysis Based on Matlab
    AU  - Yao Wei
    AU  - Wang Yiqiao
    Y1  - 2017/04/18
    PY  - 2017
    N1  - https://doi.org/10.11648/j.ijnpt.20170302.12
    DO  - 10.11648/j.ijnpt.20170302.12
    T2  - International Journal of Neurologic Physical Therapy
    JF  - International Journal of Neurologic Physical Therapy
    JO  - International Journal of Neurologic Physical Therapy
    SP  - 11
    EP  - 16
    PB  - Science Publishing Group
    SN  - 2575-1778
    UR  - https://doi.org/10.11648/j.ijnpt.20170302.12
    AB  - Action potential is one of the main ways to transmit information in the nervous system. In fact, a single electrode tends to record the activities of more than one neuron, therefore, the recorded signals need to be analyzed to get the single neuron discharge sequences. This paper separates and analyzes the nerve signals of rat dorsal root ganglion by the program written in Matlab and commercial data analysis system LabChart respectively. The results showed that both of them can achieve to separate the different amplitudes signal and conduct statistical analysis, but Matlab program is simple and can directly isolate different neural signals which is easy to understand and accept, it can also process the data according to their specific characteristics and get more consistent results to the reality, while LabChart can only get the results close to the reality. In addition, LabChart can be modified to get more practical analysis through the analysis of Matlab. In a conclusion, Matlab program can satisfy the need to deal with the data independently, and it can also work as helper to improve the results of a commercial software processing.
    VL  - 3
    IS  - 2
    ER  - 

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Author Information
  • Department of Aeronautics and Astronautics, Shanghai Key Laboratory of Acupuncture Mechanism and Acupoint Function, Fudan University, Shanghai, P. R. China

  • The Second Middle School Attached to Fudan University, Shanghai, P. R. China

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