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. 2022 Aug 24;22(17):6359.
doi: 10.3390/s22176359.

Computational Analysis of a Multi-Layered Skin and Cardiac Pacemaker Model Based on Neural Network Approach

Zuzana Psenakova  1 , Maros Smondrk  1 , Jan Barabas  1 , Mariana Benova  1 , Rafał Brociek  2 , Agata Wajda  3 , Paweł Kowol  4 , Salvatore Coco  5 , Grazia Lo Sciuto  4   5
Affiliations

Computational Analysis of a Multi-Layered Skin and Cardiac Pacemaker Model Based on Neural Network Approach

Zuzana Psenakova et al. Sensors (Basel). .

Abstract

The presented study discusses the possible disturbing effects of the electromagnetic field of antennas used in mobile phones or WiFi technologies on the pacemaker in the patient's body. This study aims to obtain information on how the thickness of skin layers (such as the thickness of the hypodermis) can affect the activity of a pacemaker exposed to a high-frequency electromagnetic field. This study describes the computational mathematical analysis and modeling of the heart pacemaker inserted under the skin exposed to various electromagnetic field sources, such as a PIFA antenna and a tuned dipole antenna. The finite integration technique (FIT) for a pacemaker model was implemented within the commercially available CST Microwave simulation software studio. Likewise, the equations that describe the mathematical relationship between the subcutaneous layer thickness and electric field according to different exposures of a tuned dipole and a PIFA antenna are used and applied for training a neural network. The main output of this study is the creation of a mathematical model and a multilayer feedforward neural network, which can show the dependence of the thickness of the hypodermis on the size of the electromagnetic field, from the simulated data from CST Studio.

Keywords: feedforward neural network; hypodermis layer thickness; pacemaker.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Cardiac Pacemaker [1].
Figure 2
Figure 2
The geometrical layout of a designed PIFA antenna model. The radiating element is highlighted by the red color, the ground plane by the green color, the shorting plate by the yellow color, the feeding pin by the blue color, and the air gap by the gray color. All dimensions are shown in millimeters.
Figure 3
Figure 3
Simulated reflection coefficients of designed dipole antenna. The reflection coefficients are plotted along the vertical axis with the blue line, the threshold value of −10 dB is represented by the red dashed line, and the green rectangle represents the 2.45 GHz frequency band of IEEE 802.11b standard (a). Simulated reflection coefficients of designed PIFA antenna. The reflection coefficients are plotted along the vertical axis with the blue line, the threshold value of −10 dB is represented by the red dashed line, and the green rectangle represents the 2.45 GHz frequency band of IEEE 802.11b standard (b).
Figure 4
Figure 4
Inverted-F antenna above and architecture PIFA structure below [35,37].
Figure 5
Figure 5
The geometrical layout of a used multilayered model with a dipole antenna (A) and PIFA antenna (B) model. The perspective view with vertical cutting plane crossing the longitudinal axis of the antenna was used to emphasize the mutual distance between the antenna and dermis. It was set up to 10 mm. Pink colored block is an epidermis layer, yellow block is a dermis layer, green block is a hypodermis layer, and blue block is a pacemaker layer.
Figure 6
Figure 6
A multilayer feedforward ANN with one hidden layer.
Figure 7
Figure 7
Learning curves of the neural network for PFA antenna (a) and for tuned antenna (b).
See this image and copyright information in PMC

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