Optimizing the Myokinetic Interface: A Finite Element Model to Predict Displacement in Amputated Muscles.

Abstract

In recent years, a novel human-machine interface for prosthetic control has been developed: the myokinetic interface, which decodes the user intent by monitoring the displacement of implanted magnets in the muscles. Simulations and the first in-human demonstration of this interface indicate that the placement of the magnets is crucial for the range and stability of the control signals. Therefore, a preoperative estimation of individual muscle displacement is necessary to identify optimal implantation regions and generate synthetic datasets of magnet displacement. In this study, we developed a finite element model of pennate muscles, calibrated and validated using the geometries of healthy muscles and in vivo measurements from healthy subjects. The performance of the model was further assessed on three amputated muscles by comparing simulations with in vivo data from a limb-impaired individual. Overall, the simulation results aligned well with experimental data, with average errors below 0.7 mm for the healthy muscles and 1.7 mm for the amputated ones. These results suggest that this model could serve as a valuable tool for optimizing surgical procedures and control strategies prior to clinical implementation. This framework could be expanded to investigate muscle behavior in different amputee populations or individuals with neuromuscular diseases, to enhance understanding of muscle biomechanics and advance the design of personalized rehabilitation devices.