Introduction: Introduced in 2002 as a means of evaluating neuromuscular disease, Electrical Impedance Myography (EIM) has since been widely utilized across clinical conditions, including disuse atrophy and amyotrophic lateral sclerosis (ALS), as an approach based on electrical impedance measurements. Electrical Impedance Myography (EIM) operates as a tetra-electrode impedance measurement method based on the fundamental principle of Ohm’s law. In this technique, a low-intensity, high-frequency alternating current is applied to the muscle or muscle group under examination through the outer pair of electrodes and the voltage difference between the inner pair of electrodes captures the potential difference, enabling the measurement of basic alternating current parameters like resistance, reactance, and phase. However, EIM measurements exhibit notable fluctuations due to the anisotropic nature of muscle. Further, electrical impedance measurements rely significantly on factors such as electrode dimensions, electrode spacing, muscle size, and the thickness of both the skin and subcutaneous fat layers. Currently, the majority of research in this field has employed straightforward linear electrode arrangements where all four electrodes are placed along the muscle fiber orientation. In this research we applied a novel approach of placing all four electrodes transverse to the muscle fiber orientation in the developed finite element model (FEM) of human upper arm. Electrode placement plays an important role in EIM measurement. This study aims at finding an optimized placement of the electrodes with respect to the muscle fiber orientation for the better diagnosis of disease state.
Materials and
Methods: The FEM model of human upper arm used in this study incorporates the governing equations of EIM measurement. The model was developed and analysed using the AC/DC Module, Electric Currents Physics, in Comsol Multiphysics software (Comsol, Inc, Burlington, MA). Based on the cross-sectional view of human upper arm, the model was designed to have four different body tissue layers i.e. bone marrow, muscle, subcutaneous fat, and skin layer. The traditional approach of placing electrodes in longitudinal pattern and the current distributions are shown in Fig. 1 where the electrodes run along the muscle fibers. The proposed electrode configurations used in this study where the electrodes run transverse to the muscle fibers, is illustrated in Fig. 2. For EIM simulation, a value of 1 mA is set to the excitation current electrode. Throughout the model, the skin-subcutaneous fat, cortical bone, and bone marrow are all considered to isotropic while muscle properties are considered as an anisotropic. The value of conductivity and relative permittivity for muscle layers at each different frequency are obtained from the published sources. . The simulations reveal the relative relationship between normal and diseased tissue, as well as the effects of the new electrode placements in determining muscle health.
Results, Conclusions, and Discussions: The simulations have been run for 50kHz and 100kHz for both normal and diseased muscle and EIM parameters such as resistance, reactance and phase is measured for both conditions for both electrode configurations. According to the previous studies, reactance at 50kHz is considered the ideal measurement of muscle condition. However, the outcome of this study shows that the phase angle(Φ) changes the most (over 12%) among all the EIM parameters at 100kHz from normal to diseased muscle for the electrode configuration where the electrodes were at transverse to the muscle fibers.
Our research aims to evaluate the effect of electrode position with the goal of providing insights for further optimizing electrode configurations in EIM. The outcome can be further compared with the experimental results of a group of normal and neuromuscular diseased subjects.
We continue to anticipate that with additional research and advancement, EIM will progressively play a valuable role in diagnosing and managing various neuromuscular disorders in the near future.
