Electrocardiogram (ECG) Signal Enhancement Using Genetic Soliton Neural Networks (GSNN)
A soliton is a solitary wave whose amplitude, shape, and velocity are conserved after a collision with another soliton. Solitons, in general, manifest themselves in a large variety of wave/particle systems in nature: practically in any system that possesses both dispersion (in time or space) and non...
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| Format: | Article |
| Language: | English |
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Unviversity of Technology- Iraq
2014-06-01
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| Series: | Engineering and Technology Journal |
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| Online Access: | https://etj.uotechnology.edu.iq/article_99869_a88e46cedc3325394b174d01e5e043fe.pdf |
| _version_ | 1827358600679391232 |
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| author | Ahmed Chyad Kadhim Mehdi Munshid Shellal Sinan Majid Abdul Satar |
| author_facet | Ahmed Chyad Kadhim Mehdi Munshid Shellal Sinan Majid Abdul Satar |
| author_sort | Ahmed Chyad Kadhim |
| collection | DOAJ |
| description | A soliton is a solitary wave whose amplitude, shape, and velocity are conserved after a collision with another soliton. Solitons, in general, manifest themselves in a large variety of wave/particle systems in nature: practically in any system that possesses both dispersion (in time or space) and nonlinearity. Solitons have been identified in optics, plasmas, fluids, condensed matter, particle physics, and astrophysics. Yet over the past decade, the forefront of soliton research has shifted to neuroscience. The Soliton model in neuroscience is a recently developed model that attempts to explain how signals are conducted within neurons. It proposes that the signals travel along the cell's membrane in the form of certain kinds of sound (or density) pulses known as solitons. The electrocardiogram (ECG) signal is generated by the rhythmic contractions of the heart. It represents the electrical activity of the heart muscles, and is usually measured by the electrodes placed on body surface. Electrocardiogram (ECG) signal has been widely used in cardiac pathology to detect heart disease. In this paper, Soliton Feed forward Neural Network (SFNN) is proposed for ECG signal enhancement. Computer simulation results demonstratedthat the proposed approach can successfully be used to model the ECG signal and remove high-frequency noise. |
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| id | doaj.art-3f75f0cad3d64fff8f0f9c587d95fab7 |
| institution | Directory Open Access Journal |
| issn | 1681-6900 2412-0758 |
| language | English |
| last_indexed | 2024-03-08T06:13:15Z |
| publishDate | 2014-06-01 |
| publisher | Unviversity of Technology- Iraq |
| record_format | Article |
| series | Engineering and Technology Journal |
| spelling | doaj.art-3f75f0cad3d64fff8f0f9c587d95fab72024-02-04T17:30:49ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582014-06-013251251126510.30684/etj.32.5A.1499869Electrocardiogram (ECG) Signal Enhancement Using Genetic Soliton Neural Networks (GSNN)Ahmed Chyad KadhimMehdi Munshid ShellalSinan Majid Abdul SatarA soliton is a solitary wave whose amplitude, shape, and velocity are conserved after a collision with another soliton. Solitons, in general, manifest themselves in a large variety of wave/particle systems in nature: practically in any system that possesses both dispersion (in time or space) and nonlinearity. Solitons have been identified in optics, plasmas, fluids, condensed matter, particle physics, and astrophysics. Yet over the past decade, the forefront of soliton research has shifted to neuroscience. The Soliton model in neuroscience is a recently developed model that attempts to explain how signals are conducted within neurons. It proposes that the signals travel along the cell's membrane in the form of certain kinds of sound (or density) pulses known as solitons. The electrocardiogram (ECG) signal is generated by the rhythmic contractions of the heart. It represents the electrical activity of the heart muscles, and is usually measured by the electrodes placed on body surface. Electrocardiogram (ECG) signal has been widely used in cardiac pathology to detect heart disease. In this paper, Soliton Feed forward Neural Network (SFNN) is proposed for ECG signal enhancement. Computer simulation results demonstratedthat the proposed approach can successfully be used to model the ECG signal and remove high-frequency noise.https://etj.uotechnology.edu.iq/article_99869_a88e46cedc3325394b174d01e5e043fe.pdfsoliton systemsfeed forward neural networkselectrocardiogram |
| spellingShingle | Ahmed Chyad Kadhim Mehdi Munshid Shellal Sinan Majid Abdul Satar Electrocardiogram (ECG) Signal Enhancement Using Genetic Soliton Neural Networks (GSNN) Engineering and Technology Journal soliton systems feed forward neural networks electrocardiogram |
| title | Electrocardiogram (ECG) Signal Enhancement Using Genetic Soliton Neural Networks (GSNN) |
| title_full | Electrocardiogram (ECG) Signal Enhancement Using Genetic Soliton Neural Networks (GSNN) |
| title_fullStr | Electrocardiogram (ECG) Signal Enhancement Using Genetic Soliton Neural Networks (GSNN) |
| title_full_unstemmed | Electrocardiogram (ECG) Signal Enhancement Using Genetic Soliton Neural Networks (GSNN) |
| title_short | Electrocardiogram (ECG) Signal Enhancement Using Genetic Soliton Neural Networks (GSNN) |
| title_sort | electrocardiogram ecg signal enhancement using genetic soliton neural networks gsnn |
| topic | soliton systems feed forward neural networks electrocardiogram |
| url | https://etj.uotechnology.edu.iq/article_99869_a88e46cedc3325394b174d01e5e043fe.pdf |
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