Magneto-mechanical resonators (MMRs) are a recently proposed type of passive sensor that can estimate their position and orientation, as well as detect other parameters in their surroundings. These sensors are excited by oscillating magnetic fields, and their responses are measured using inductive receiver coils. To determine sensor parameters from the measured signals in real time, a nonlinear inverse problem must be solved using the signals and a suitable forward model.
This work introduces a reference model and simplified models for describing MMR dynamics and inductive readout. The authors also develop robust parameter-estimation methods designed to provide accurate results while meeting real-time computational requirements.
The effectiveness of the proposed methods is evaluated in terms of their real-time potential, precision, and accuracy. All presented methods demonstrate the ability to estimate the measured signals. The simplified methods reduce parameter-estimation time by up to two orders of magnitude, with less than 4% deviation from the reference method for large maximum deflection angles.
The study is a collaboration between the Institute for Biomedical Imaging at Hamburg University of Technology (TUHH), the Section for Biomedical Imaging at University Medical Center Hamburg-Eppendorf, and the Fraunhofer Research Institution for Individualized Medical Technology and Engineering (IMTE). .
Sarah Reiss, Tobias Knopp, Justin Ackers, Jonas Faltinath, Fabian Mohn, Marija Boberg, Nora Timm and Martin Möddel (2026). Parameter Estimation for Model-Based Sensing of Magneto-Mechanical Resonators. Communications Physics 9, Article number 312 (2026).
https://doi.org/10.1038/s42005-026-02884-1
