1. Simulating Current Distribution In Tissue During Electrical Stimulation Using Finite Element Model
Rajdeep Ojha1, Vimal Chander1, Devakumar2
1. Department of Physical Medicine and Rehabilitation, Christian Medical College, Vellore, Tamilnadu, India
2. Department of Nuclear Medicine, Christian Medical College, Vellore, Tamilnadu, India
INTRODUCTION: Electrical stimulation of nerve/muscle is achieved by passing current between stimulating and the return electrode. The spread of current depends on several factors such as tissue properties, shape and size of electrodes and stimulation parameters. For a desired stimulus response, it is important to understand the current distribution by varying aforementioned factors before trying on the patient.
OBJECTIVES:
To demonstrate the spread of current in tissue during surface and needle electrical stimulation.
To demonstrate targeted delivery of current in needle electrical stimulation as compared to surface electrical stimulation.
To elicit the above objectives in hypothetical and real geometry using COMSOL and SIMPLEWARE.
Finite element model on real tissue model was also studied using combination of COMSOL Multiphysics 5.3a and SIMPLEWARE N ver.1. 3-D. The region of thigh was extracted from MRI images using SIMPLEWARE and was exported to COMSOL compatible format after preprocessing. Using COMSOL AC/DC module both needle and surface electrode model were studied for current ranging from 1 mA to 50 mA. [fig 3 and 4]. Material property and physics similar to hypothetical model was assigned.
RESULTS: Potential distribution in hypothetical cylindrical model is shown in Fig. 5 and 7 for surface electrode model and Fig. 6 and 8 for needle electrode model (both real and hypothetical model with current of 10 mA). The inset picture view of Fig. 5 and 6 shows the large attenuation of current at stratum corneum layer in surface electrode model while very small attenuation of current in needle electrode model.
COMPUTATIONAL METHODS: A hypothetical concentric cylindrical finite element model (FEM) which represents human thigh was created and the spread of current was studied in COMSOL Multiphysics 5.3a. Cylindrical geometry representing skin, soft tissue, muscle and bone were constructed using model builder. The anode, cathode and corresponding gel layer for surface electrode model were built using circular conductive disc [electrode (top) and gel (bottom)] stacked together. The anode and cathode were placed 120 mm apart over the skin as shown in fig 1, while the needle electrode model was built using two concentric cylinders [insulation (outer) and electrode layer (inner)] placed between the skin and muscle as shown in fig2. The constructed geometry was assigned user-defined material property[1,2]. Static as well as pulsatile current ranging from 1mA - 50mA were assigned using AC/DC module of COMSOL. The electrical potential V in a medium of conductivity σ (under quasi-static approximation) is the solution of the homogeneous Poisson equation:
Fig: 5 Potential distribution in hypothetical cylindrical model showing large attenuation of current at skin layer
Fig: 6 Potential distribution in hypothetical needle electrical stimulation model
Fig: 7 Potential distribution in low impedance thigh surface electrical stimulation model
Fig: 8 Potential distribution in thigh needle electrical stimulation model
CONCLUSIONS: Simulated results shows that the localization of current in needle stimulation model while wide spread of current across the tissue in surface stimulation model, most of which, got attenuated at the skin layer. The model is useful in understanding the factors that affect the current distribution during electrical stimulation. The model not only finds its usefulness in pre-determining the parameters of stimulation but also gives pictorial view of spread of current inside the tissue. .
Fig: 1 Hypothetical surface electrode
model
Fig: 2 Hypothetical needle electrode
model
REFERENCES:
1. K. Zhu, L. Li, X. Wei, and X. Sui, “A 3D computational model of transcutaneous electrical nerve stimulation for estimating Aß tactile nerve fiber excitability,” Frontiers in Neuroscience, vol. 11, no. MAY, 2017. 2.
ACKNOWLEDGEMENTS:
Department of Biotechnology, Government of India, New Delhi
Department of Physical Medicine and Rehabilitation, CMC Vellore, Tamilnadu, India
Fig: 3 Snapshot of MRI Image of a Thigh
Fig: 4 FEM thigh surface electrode model
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