# Electrically Equivalent Head Tissue Materials for Electroencephalogram Study on Head Surrogates
## 5 Discussion  
In this study, we developed a multilayer electrically equivalent head tissue phantom and showed that the conductivities of individual layers as well as the overall conductivity of the four-layer and seven-layer head tissue are well within the reported values. The target conductivities of different layers of our human head tissue phantom were based on the report that summarized the conductivities of head tissue layers out of 56 independent studies [23]. We have shown that our Composite material system reasonably matches the desired conductivities, as shown in Figure 6. We argue that both our four-layer and seven-layer phantom models represent electrically equivalent phantom head tissue (Figure 1). As such, for future studies, any of these models can be used. However, our main motivation for building two different phantom tissues emanated from a specific application point of view. For instance, depending on the posture type of the human body (i.e., standing, sitting, or lying flat in a prone or supine position), the CSF layer thickness may vary, which, in turn,  
Figure 7: (**a**) SNR for 1 mV amplitude and varying frequencies. (**b**) SNR for 10 Hz frequency and varying amplitude. can alter the effective conductivity and signal intensity detected by an EEG [51]. In studies where CSF thickness variation matters the most, the four-layer model will be more suitable. When studies involve the effect of multiple factors such as CSF, skull, scalp, and depth of white matter or gray matter, then the seven-layer model should be used. The seven-layer model is also suitable for EEG studies where a more comprehensive phantom head tissue model is used. Such phantom head cases include skull, scalp, CSF, white matter, gray matter, eye, cerebellum [52], spinal cord, and dura [53]. By supplying any prerecorded data to the signal generator, the same response can be created in phantom heads, manufactured using any of these layers. Using these phantom heads, EEG equipment testing, electrode design upgrade and testing, as well as suitability testing of EEGs in various dynamic environments can be performed and compared especially when human subjects are not present. Each of the layers individually and collectively can withstand the signal generation inside them without changing the electrical and physical properties of the material. Therefore, the SNR is unaffected by the signal supply inside the phantom layers over a lengthy period. When a phantom head is constructed utilizing these layers, several experiments can be carried out when conductivity is a major issue. As such, our modular material system is suitable for a wide range of applications. This study can offer a recipe for creating the layers as well as the ability to alter their thickness and geometry for any experiments examining the effect of only a single layer's thickness on EEG errors [53; 54]. The SNR study of the manufactured layers in Figure 7a,b can provide confidence in generating synthetic brain signals for the experiment [55; 56]. It should be noted that all the studies only considered the electrical properties, mostly conductivity, but other properties like mechanical or thermal properties are not considered. For future work, head tissue layers capable of withstanding very high-frequency oscillation (VHPO) over 1000 Hz frequency [57] can be impactful in studying epileptogenic zones. The signal-to-noise ratio (SNR) for certain lower amplitude signals often exhibits negative values, indicating that the EEG receives more noise than the real signal. Such issues can be improved by changing the experimental setup or by improving the quality of the EEG probe. A full phantom head with human head geometry is not built and analyzed in this paper. So, the geometry modeling error will be present in the analysis of source localization. Most of the EEG studies conducted for detecting neurodegenerative disease, alertness level, and fatigue detection are performed by analyzing frequencies, especially the frequency power.