3-D modeling of thin wire and thin plate using finite element method and electrical circuit equation

Ali, Abakar; Coulomb, Jean‐Louis; Meunier, G.; Zgainski, F.-X.; Guérin, Christophe

doi:10.1109/20.952585

Cited by 15 publications

(2 citation statements)

References 4 publications

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“…The wiring of the coils was extracted from X-ray images and modeled with each individual turn [ 49 ], [ 50 ]. A simplification of the coils to single-turn representations as common in the literature was avoided here (see Fig.…”

Section: Modelmentioning

confidence: 99%

Prediction of Force Recruitment of Neuromuscular Magnetic Stimulation From 3D Field Model of the Thigh

Goetz

Kammermann

Helling

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

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Neuromuscular magnetic stimulation is a promising tool in neurorehabilitation due to its deeper penetration, notably lower distress, and respectable force levels compared to surface electrical stimulation. However, this method faces great challenges from a technological perspective. The systematic design of better equipment and the incorporation into modern training setups requires better understanding of the mechanisms and predictive quantitative models of the recruited forces. This article proposes a model for simulating the force recruitment in isometric muscle stimulation of the thigh extensors based on previous theoretical and experimental findings. The model couples a 3D field model for the physics with a parametric recruitment model. This parametric recruitment model is identified with a mixed-effects design to learn the most likely model based on available experimental data with a wide range of field conditions. This approach intentionally keeps the model as mathematically simple and statistically parsimonious as possible in order to avoid over-fitting. The work demonstrates that the force recruitment particularly depends on the effective, i.e., fiber-related cross section of the muscles, and that the local median electric field threshold amounts to about 65 V/m, which agrees well with values for magnetic stimulation in the brain. The coupled model is able to accurately predict key phenomena observed so far, such as a threshold shift for different distances between coil and body, the different recruiting performance of various coils with available measurement data in the literature, and the saturation behavior with its onset amplitude. The presented recruitment model could also be readily incorporated into dynamic models for biomechanics as soon as sufficient experimental data are available for calibration.

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Section: Modelmentioning

confidence: 99%

Prediction of Force Recruitment of Neuromuscular Magnetic Stimulation From 3D Field Model of the Thigh

Goetz

Kammermann

Helling

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

View full text Add to dashboard Cite

show abstract

“…The experimental performance of the figure-of-eight coil for magnetic stimulation of the intramuscular nerve structures is not represented in the literature, but was added to predict its force potential using the model calibration to the other coils. The wiring of the coils was extracted from X-ray images and modeled with each individual turn (49, 50). A simplification of the coils to single-turn representations as common in the literature was avoided here (see Fig.…”

Section: Modelmentioning

confidence: 99%

Force Recruitment of Neuromuscular Magnetic Stimulation Predicted Through High-Resolution Anatomical 3D Models

Goetz

Kammermann

Helling

et al. 2021

Preprint

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Neuromuscular magnetic stimulation is a promising tool in neurorehabilitation due to its deeper penetration, notably lower distress, and respectable force levels compared to electrical stimulation. However, this method faces great challenges from a technological perspective. The systematic design of better equipment and the incorporation into modern training setups requires better understanding of the mechanisms and predictive quantitative models of the recruited forces. This article proposes a model for simulating the force recruitment in isometric muscle stimulation of the thigh extensors based on previous theoretical and experimental findings. The model couples a 3D field model for the physics with a parametric recruitment model, which is identified with a mixed-effects design to learn the most likely model based on available experimental data with a wide range of field conditions. This approach intentionally keeps the model as mathematically simple and statistically parsimonious as possible in order to avoid over-fitting. The coupled model is able to accurately predict key phenomena observed so far, such as a threshold shift for different distances between coil and body, the different recruiting performance of various coils with available measurement data in the literature, and the saturation behaviour with its onset amplitude. The presented recruitment model could also be readily incorporated into dynamic models for biomechanics as soon as sufficient experimental data are available for calibration.

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Numerical Solution of Multi-scale Electromagnetic Boundary Value Problems by Utilizing Transformation-Based Metamaterials

Özgün

Kuzuoğlu

2011

Computational Science and Its Applications - ICCSA 2011

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3-D modeling of thin wire and thin plate using finite element method and electrical circuit equation

Cited by 15 publications

References 4 publications

Prediction of Force Recruitment of Neuromuscular Magnetic Stimulation From 3D Field Model of the Thigh

Prediction of Force Recruitment of Neuromuscular Magnetic Stimulation From 3D Field Model of the Thigh

Force Recruitment of Neuromuscular Magnetic Stimulation Predicted Through High-Resolution Anatomical 3D Models

Numerical Solution of Multi-scale Electromagnetic Boundary Value Problems by Utilizing Transformation-Based Metamaterials

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