Mitigating the Effect of Muscle Thickness on Electrical Impedance Myography Measurements Using a Finite Element Model

Electrical impedance myography (EIM) is a non-invasive neurophysiological technique that evaluates the electrical properties of body tissues by applying a high-frequency, low-intensity current through surface electrodes. While EIM is effective in detecting neuromuscular disorders by identifying changes in these properties, its measurements can also be affected by factors beyond muscle abnormalities. Variations in muscle thickness, subcutaneous fat (SF), and electrode spacing may influence results, potentially causing deviations from expected patterns. This study examines how muscle thickness affects EIM measurements and proposes adjusting electrode size to minimize its impact. Using a finite element model (FEM), results show that while muscle thickness alters EIM parameters, resizing the electrodes reduces these variations. This approach improves the detection of neuromuscular disorders, suggesting that variable-size electrodes could enhance EIM accuracy compared to conventional fixed-size ones.