Non-invasive phrenic nerve stimulation is a promising alternative to mechanical ventilation because it keeps the diaphragm active and prevents muscle atrophy. Digital twins are increasingly being used to optimize the stimulation parameter selection. However, the accuracy of their predictions depends on biological input parameters, such as electrical tissue conductivity. These parameters can vary considerably due to measurement uncertainties, individual differences, and physiological and pathological conditions.
The current study investigated how this uncertainty influences the nerve activation threshold. The nerve activation threshold is the stimulation current required to activate the phrenic nerve. To this end, a surrogate model was developed from an existing, detailed, multi-scale model that calculates the nerve activation threshold directly and efficiently from the tissue conductivity. The surrogate model was then used to perform a comprehensive Monte-Carlo analysis that considered thousands of possible combinations of tissue conductivities.
The results showed that the activation threshold varies by approximately ± 15 %, depending on conductivity variations. A sensitivity analysis revealed that muscle tissue conductivity has the strongest influence on the nerve activation threshold. For future electromagnetic simulations, this means that muscle tissue should be characterized and modeled as accurately as possible.
Thus, the study provides an explanation for the differences observed in individual activation thresholds in experiments and contributes to more realistic, patient-specific simulations of phrenic nerve stimulation.
Publication in Biocybernetics and Biomedical Engineering, The influence of tissue conductivity uncertainty on the nerve activation thresholds in non-invasive electrical phrenic nerve stimulation (https://www.sciencedirect.com/science/article/pii/S0208521625000841)
From Laureen Wegert, Luca Di Rienzo, Lorenzo Codecasa, Sicheng An, Marek Ziolkowski, Alexander Hunold, Irene Lange, Tim Kalla, Jens Haueisen
DOI: doi.org/10.1016/j.bbe.2025.11.003
