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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Towards Implementing Framework to Generate Myopathic Signals

Author 1: Amira Dridi Author 2: Jassem Mtimet Author 3: Slim Yacoub
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 10, No. 3 · Published 2019

DOI: https://doi.org/10.14569/IJACSA.2019.0100350

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Abstract

In this paper, we describe a simulation system of myopathicsurface electromyography (sEMG) signals. The architecture of the proposed system consists of two cascading modules. SEMG signals of three pathological skeletal muscles (Biceps Brachii, InterosseursDorsalis, TibalisAnterior) were generated. Root Mean Square (RMS Envelope) and Power Spectral Density (PSD) were used to validate our system.

Keywords

Component Surface Electromyography (sEMG) myopathy root mean square Power Spectral Density (PSD skeletal muscles biceps brachii interosseous dorsalis tibialis anterior

How to Cite this Article

Dridi, A., Mtimet, J., & Yacoub, S. (2019). Towards Implementing Framework to Generate Myopathic Signals. International Journal of Advanced Computer Science and Applications, 10(3). https://doi.org/10.14569/IJACSA.2019.0100350

Dridi, Amira, et al.. "Towards Implementing Framework to Generate Myopathic Signals." International Journal of Advanced Computer Science and Applications, vol. 10, no. 3, 2019, https://doi.org/10.14569/IJACSA.2019.0100350.

@article{Dridi2019,
  title     = {Towards Implementing Framework to Generate Myopathic Signals},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {3},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Amira Dridi and Jassem Mtimet and Slim Yacoub},
  doi       = {10.14569/IJACSA.2019.0100350},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100350}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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