Identifying least affected parameters in analyzing Electrical Impedance Myography with alteration in subcutaneous fat thickness via finite element model

Abstract

Electrical Impedance Myography (ElM) is a neurophysiologic technique in which high-frequency, low intensity electrical current is applied via surface electrodes over a muscle or muscle group of interest and the resulting electrical parameters (resistance, reactance and phase) are analyzed to isolate diseased muscles from healthy one. Beside muscle properties, some other factors like subcutaneous fat (SF) thickness, inter-electrode distance, muscle thickness etc. also impact the major ElM parameters. The purpose of this study is to explore the effect of SF thickness variation on different ElM parameters and propose a parameter which is least affected and also can detect muscle conditions. We analyzed four different parameters in this study for various SF thicknesses and none of them possesses constant profile with alteration in SF thickness.For example, resistance in normal condition varies 24.48% with per millimeter SF thickness variation while phase varies 4.01%.Further investigation shows that among the observed parameters percentage changes in reactance is minimum with fat thickness variation while effectively identifying different muscle conditions.

Comparison of Circular and Rectangular-Shaped Electrodes for Electrical Impedance Myography Measurements on Human Upper Arms

“…These results are based on the FEM study, and it is evident from these figures that the EIM parameters for both the rectangular and circular electrode shapes change in a similar manner over the frequency spectrum, as SF thickness varies. An earlier study [ 22 ] has shown that the real part of the impedance, i.e., resistance, is highly affected by the electrical properties of the skin-fat layer, whereas reactance, which is the imaginary part of the impedance, highlights changes in the thickness or electrical properties of the muscle. The isotropic skin-fat layer acts more like an electrical barrier, which increases the overall cross-sectional area of the muscle and thus increases the resistance.…”

“…In order to minimize the error in the experimental procedure, EIM measurements were conducted on both arms and the average of the measurements was analyzed for results. For single-frequency analysis, previous studies show that reactance at a certain frequency (e.g., 50 kHz) within the lower range of the spectrum is a suitable parameter for differentiating between healthy and unhealthy muscle [ 7 , 22 ]. Since the frequency at which the peak reactance occurs varies significantly between individuals, we have chosen a generic frequency (50 kHz) at which to compare the effectiveness of the two electrode shapes at varying thicknesses of subcutaneous fat.…”

“…(a) show that reactance at a certain frequency (e.g., 50 kHz) within the lower range of the spectrum is a suitable parameter for differentiating between healthy and unhealthy muscle [7,22]. Since the frequency at which the peak reactance occurs varies significantly between individuals, we have chosen a generic frequency (50 kHz) at which to compare the effectiveness of the two electrode shapes at varying thicknesses of subcutaneous fat.…”

Assessment of Optimized Electrode Configuration for Electrical Impedance Myography Using Genetic Algorithm via Finite Element Model

“…The optimized configuration is 7 mm × 7 mm surface electrodes with 33 mm-7 mm-33 mm spacing between them. Only reactance at 50 kHz has been highlighted in this figure because it has been stated in previous studies [10] that reactance at 50 kHz is the parameter which is least affected by SF thickness alteration and the best parameter to diagnose the disease effectively. As can be depicted from the figure, this parameter is less prone to change in case of optimized configuration than the conventional configuration.…”

“…Because of its noninvasive nature, EIM measurement also includes the electrical response of other body tissues like subcutaneous fat thickness, muscle thickness variation [5–8], and also some nonanatomic factors like electrode surface area, interelectrode distance, and ambient temperature [9]. Studies prove that, out of different EIM parameters, reactance at a specific frequency is the desired parameter that is least affected by above-mentioned anatomic factors and is also the most effective parameter to detect muscle abnormal conditions successfully [10]. …”