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<p>From a biological viewpoint, the muscle tissue produces efficient gait behavior that can be adjusted by neural signals. From the physical viewpoint, the limb movement can be simulated by applying a neural circuit to control the artificial electromechanical arm (EA). In this paper, a functional neural circuit is used to excite a single EA, the load circuit attached to the moving beam is driven by a neural circuit, and the Ampere force is activated by the load circuit to control the artificial EA. The dynamic equations of the neural circuit are derived using Kirchhoff’s theorem, while the energy and motion equations of the beam are computed through the application of mechanics and related theoretical principles. Furthermore, the dynamic characteristics of the functional neural circuit forced EA are analyzed. The results indicate that the beam movement can be controlled by the electrical activity of this functional neural circuit. This work will provide theoretical guidance to build the electromechanical device for complex gait behaviors.</p>

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Characteristics analysis of a single electromechanical arm driven by a functional neural circuit

  • 期刊论文

  • 发表日期：

    2025年4月22日

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  • Xinlin Song,
  • Ya Wang,
  • Zhenhua Yu,
  • Feifei Yang

摘要

From a biological viewpoint, the muscle tissue produces efficient gait behavior that can be adjusted by neural signals. From the physical viewpoint, the limb movement can be simulated by applying a neural circuit to control the artificial electromechanical arm (EA). In this paper, a functional neural circuit is used to excite a single EA, the load circuit attached to the moving beam is driven by a neural circuit, and the Ampere force is activated by the load circuit to control the artificial EA. The dynamic equations of the neural circuit are derived using Kirchhoff’s theorem, while the energy and motion equations of the beam are computed through the application of mechanics and related theoretical principles. Furthermore, the dynamic characteristics of the functional neural circuit forced EA are analyzed. The results indicate that the beam movement can be controlled by the electrical activity of this functional neural circuit. This work will provide theoretical guidance to build the electromechanical device for complex gait behaviors.