Development of a digital twin of the leg for monitoring lymphedema by means of bioimpedance spectroscopy

The electrical bioimpedance spectroscopy consists of measuring electrical impedance of living tissues in function of frequency [1]. It is a non-invasive technique, widely used in the biomedical domain for diagnostic and monitoring purposes, for wound healing or lymphedema evolution [2]. Measurements are performed using different electrode topologies (two, three or four), and the excitation current must cross the electrode-skin interface. Even when specific electrode configurations can reduce the influence of this interface impedance, its amplitude remains largely higher than the impedance of the underlying tissues, thus constituting one of the most complex challenges in the field of bioimpedance instrumentation. Furthermore, the measured impedance depends on the electrical properties of the tissue and is the result of a complex combination due to the variation of relative conductivities and permittivities in presence.

The development of a physical model, on which these measurements can be carried out [3], is an interesting solution, because it offers stable and reproducible parameters, but it remains time-consuming and limited to a given geometry. In vivo tests, on the other hand, are necessarily more restrictive and poorly suited to this stage of investigation.

To overcome these challenges, this thesis project proposes to contribute to optimizing the performance of bioimpedance spectroscopy by developing a digital twin of the leg. This virtual model will allow an in-depth study of the bioimpedance technique, thus effectively guiding experimental decisions.

The objective of this thesis is to develop a digital tool to assist in the design of bioimpedance measurement devices dedicated to the assessment of the water content of living tissues.

More specifically, it is proposed to develop a digital twin of the human leg using finite element-based solvers, reproducing electrical parameters of tissues. The starting point will be the reproduction of electrical parameters extracted from experimental measurements, carried out on standardized measuring cells [4].

The project involves the implementation of different bioimpedance measurement scenarios to obtain a physiological signature of each tissue, thus allowing non-invasive monitoring of the evolution of a healthy or pathological leg. Topology, size, material and shape of the electrodes will be optimized in order to create the best combinations for accurate and robust measurements.

The use of this computational model will allow testing of different research protocols and electrode configurations, before proceeding with experimental tests, thus improving operational efficiency while reducing the associated time and costs.

References

[1] Grimnes S., Martinsen O. G., Bioimpedance & Bioelectricity Basics. Elsevier, New York, 2008.

[2] Cavezzi A., Urso S. U., Paccasassi S., Mosti G., Campana F., Colucci, R. Bioimpedance spectroscopy and volumetry in the immediate/short-term monitoring of intensive complex decongestive treatment of lymphedema. Phlebology, 35(9), 715–723, 2020.

[3] A. Bublex, A. Montalibet, B. Massot and C. Gehin. Eco-Friendly Bioimpedance Muscle Phantom: PVA-Agar Hydrogel Mimicking Living Tissue at Low Frequencies, 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2024, pp. 1-4.

[4] M.R. Longhitano, A. Bublex, A. Montalibet, B. Massot and C. Gehin. Finite Element Modelling of standardised measuring cells filled with tissue-mimicking materials for bioimpedance assessment, 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Copenhagen, 2025, pp. 1-4.

The Lyon Institute of Nanotechnologies (INL) is a Joint Research Unit (UMR 5270) supervised by the CNRS, ECL, INSA, University Lyon 1 and CPE Lyon. The INL's mission is to develop multidisciplinary technological research in the field of micro- and nanotechnologies and their applications. The areas of application cover major economic sectors: the semiconductor industry, information technology, energy and the environment, and life and health technologies.

Master's degree in Biomedical Engineering or Electrical Engineering, with good computer programming and instrumentation skills. Knowledge of Finite Element Analysis is appreciated.