Analyzing Electrical Impedance Myography Parameters to Identify the Least Affected Parameter with Alteration in Subcutaneous Fat Thickness
Location
Room 2903
Session Format
Paper Presentation
Research Area Topic:
Engineering and Material Sciences - Electrical
Co-Presenters and Faculty Mentors or Advisors
Faculty Adviser - Dr. Mohammad Ahad, Assistant Professor, Department of Electrical Engineering.
Abstract
Electrical Impedance Myography (EIM) 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 analysed 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 three above major EIM parameters. The purpose of this study is to explore the effect of SF thickness variation on different EIM parameters and propose a parameter which is least effected and also can detect muscle conditions. As Finite Element Method (FEM) has been established as an appropriate approach for analysis of non-symmetrical shape like muscle tissue for assessing alternations of muscle in disease-induced changes through ElM, in this study, we analysed the effect of SF thickness on EIM parameters using a finite element model of human upper arm which is developed based on anatomic data; material properties of the tissue obtained from rat and published sources. We analysed four different parameters in this study for various SF thicknesses. For example, resistance in normal condition and at 50 kHz varies 24.48% with per millimetre SF thickness variation while phase varies 4.01%. Reactance at 50 kHz varies 1.36% per millimetre of SF thickness for normal muscle. In conclusion, among the observed parameters, percentage change in reactance is the minimum with fat thickness variation while effectively identifying different muscle conditions. So we propose to use reactance as the principal parameter while analysing EIM in disease detection.
Keywords
EIM, EIM parameters, SF thickness, FEM
Presentation Type and Release Option
Presentation (Open Access)
Start Date
4-24-2015 1:30 PM
End Date
4-24-2015 2:30 PM
Recommended Citation
Baidya, Somen and Fazle Rabbi, Khondokar Mohammad, "Analyzing Electrical Impedance Myography Parameters to Identify the Least Affected Parameter with Alteration in Subcutaneous Fat Thickness" (2015). GS4 Georgia Southern Student Scholars Symposium. 76.
https://digitalcommons.georgiasouthern.edu/research_symposium/2015/2015/76
Analyzing Electrical Impedance Myography Parameters to Identify the Least Affected Parameter with Alteration in Subcutaneous Fat Thickness
Room 2903
Electrical Impedance Myography (EIM) 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 analysed 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 three above major EIM parameters. The purpose of this study is to explore the effect of SF thickness variation on different EIM parameters and propose a parameter which is least effected and also can detect muscle conditions. As Finite Element Method (FEM) has been established as an appropriate approach for analysis of non-symmetrical shape like muscle tissue for assessing alternations of muscle in disease-induced changes through ElM, in this study, we analysed the effect of SF thickness on EIM parameters using a finite element model of human upper arm which is developed based on anatomic data; material properties of the tissue obtained from rat and published sources. We analysed four different parameters in this study for various SF thicknesses. For example, resistance in normal condition and at 50 kHz varies 24.48% with per millimetre SF thickness variation while phase varies 4.01%. Reactance at 50 kHz varies 1.36% per millimetre of SF thickness for normal muscle. In conclusion, among the observed parameters, percentage change in reactance is the minimum with fat thickness variation while effectively identifying different muscle conditions. So we propose to use reactance as the principal parameter while analysing EIM in disease detection.