Title of article :
Modeling the Electromyogram Signal of Stimulated Biceps Brachii Muscle
Author/Authors :
khodadadi, Vahid Department of Biomedical Engineering - Islamic Azad University Science and Research Branch, Tehran, Iran , Nowshiravan Rahatabad, Fereidoun Department of Biomedical Engineering - Islamic Azad University Science and Research Branch, Tehran, Iran , Sheikhani, Ali Department of Biomedical Engineering - Islamic Azad University Science and Research Branch, Tehran, Iran , Jafarnia Dabanloo, Nader Engineering Research Center in Medicine and Biology - Islamic Azad University Science and Research Branch, Tehran, Iran
Pages :
6
From page :
140
To page :
145
Abstract :
Introduction: The usage of modeling methods has been proposed to achieve a better understanding of biological systems, so that some ambiguities about their function could be resolved. Accordingly, the present review was performed to model the electromyogram signal of stimulated biceps brachii muscle. Methods: In this review study, a search was performed in databases of Emerald, Cochrane Library, MEEDLINE, EMBASE, Wiley, Scopus, and Magiran on papers published over the past 20 years. Papers that fulfilled all inclusion criteria were critically appraised in order to assess their quality. Out of the 66 papers extracted, eight original papers were included. The findings obtained from the papers were noted, and then underwent content analysis and categorization. Results: Findings indicated that most of the performed studies had been modeled using cybernetic, robotic, regression, and neural network modeling methods. These physiological mathematical models model the physiological structure of the muscle based on a direct description of biomechanical, biological, and physiological characteristics of the system individually, which is difficult for obtaining many parameters. Conclusion: Most of the models presented so far do not match reality and have errors. Thus, studies are required to design a model similar to a biological system with the properties of biological systems in order to reduce the modeling error.
Keywords :
Modeling , Signal , Electromyogram , Biceps Brachii Muscle
Journal title :
International Journal of Medical Reviews
Serial Year :
2021
Record number :
2715427
Link To Document :
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