Model approach of electromechanical arm interacted with neural circuit, a minireview

Jun Ma and Yitong Guo

Chaos, Solitons & Fractals, 2024, vol. 183, issue C

Abstract: Artificial neurons can be designed and excited to produce similar smart responses as biological neurons driven by electromagnetic excitations. The interaction between cell membrane and ion channels accounts for the mode transition in membrane potentials and the changes of inner field energy during continuous diffusion and propagation of ions in the neuron. The external stimuli just speed up the mode selection by changing the gradient distribution of electromagnetic field of the cell. The propagated electric pulses are affected by the Calcium wave and concentration, and muscle is controlled to behave suitable body gaits. In this review, a neural circuit-coupled electromechanical device is suggested to clarify how neural signals drive the artificial arms. The pre-placed neural circuit can be regarded as a wave filter, and the encoded signals are guided to excite one electromechanical arm, and then a pair of arms connected with a spring is controlled to simulate the motion of two arms. The circuit and motion equations for the artificial arms are presented with exact definition of energy function. Scale transformation is applied to obtain an equivalent dimensionless dynamical model and the dimensionless Hamilton energy. Finally, an adaptive control law is presented to control the neural circuit and the load circuit in the electromechanical device. This work provides possible guidance for designing artificial arms or legs under electric stimuli, readers can find clues for further investigation under complete dynamical analysis.

Keywords: Neural circuit; Scale transformation; Neuron; Artificial arm; Synchronization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:183:y:2024:i:c:s0960077924004776

DOI: 10.1016/j.chaos.2024.114925

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