Modeling the excitation of nerve axons under transcutaneous stimulation

Narrendar RaviChandran; James Hope; Kean Aw; Andrew McDaid

doi:10.1016/j.compbiomed.2023.107463

Modeling the excitation of nerve axons under transcutaneous stimulation

Comput Biol Med. 2023 Oct:165:107463. doi: 10.1016/j.compbiomed.2023.107463. Epub 2023 Sep 6.

Authors

Narrendar RaviChandran¹, James Hope², Kean Aw³, Andrew McDaid⁴

Affiliations

¹ Medical Devices and Technologies Group, Department of Mechanical and Mechatronics Engineering, The University of Auckland, Auckland 1010, New Zealand; Singapore Eye Research Institute, Singapore 169856, Singapore. Electronic address: nrav195@aucklanduni.ac.nz.
² Medical Devices and Technologies Group, Department of Mechanical and Mechatronics Engineering, The University of Auckland, Auckland 1010, New Zealand; Department of Mechanical Engineering, The University of Minnesota, Minneapolis, MN 55455, United States.
³ Smart Materials and Microtechnologies Group, Department of Mechanical and Mechatronics Engineering, The University of Auckland, Auckland 1010, New Zealand.
⁴ Medical Devices and Technologies Group, Department of Mechanical and Mechatronics Engineering, The University of Auckland, Auckland 1010, New Zealand.

PMID: 37699322
DOI: 10.1016/j.compbiomed.2023.107463

Abstract

Computational models enable a safe and convenient way to study the excitation of nerve fibers under external stimulation. Contemporary models calculate the electric field distribution from transcutaneous stimulation and the resulting neuronal response separately. This study uses finite element methods to develop a multi-scale model that couples electric fields within macroscopic tissue layers and microscopic nerve fibers in a single-stage computational framework. The model included a triaxial myelinated nerve fiber bundle embedded within a volume conductor of tissue layers to represent the median nerve innervating the forearm muscles. The model captured the excitability of nerve fibers under transcutaneous stimulation and their nerve-tissue interactions to a transient external stimulus. The determinants of the strength-duration curve, rheobase, and chronaxie for the proposed model had close correlations with in-vivo experimentation on human participants. Additionally, the excitability indices for the triaxial myelinated nerve fiber implemented using the finite element method agreed well with experimental data from the literature. The validity of the proposed model encourages its use for applications involving transcutaneous stimulation. Capable of capturing field distribution across realistic morphologies, the model can serve as a testbed to improve stimulation protocols and electrode designs with subject-level specificity.

Keywords: Bundled fibres; Ephaptic coupling; Finite element modeling; Myelinated axon; tNMES.

MeSH terms

Axons*
Electrodes
Forearm
Humans
Nerve Fibers, Myelinated
Pain Management*