## 2 Materials and Methods
### Analysis of Sizing System Generation Method  
With reference to previous studies related to size-system generation [24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36], applicable techniques and sample data for segmenting body sections and creating an average human body model were analyzed. Table 1 shows the results.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Division** & **Applicable Technique** & **Sample Data Type** \\ \hline Size-section & & Grid method & 2D \\ Segmentation & & Clustering method & Human body \\  & & Optimization method & measurement data \\ \hline  & & Wireframe & \\ Average & Modeling method & modeling & 3D \\ Human model & utilization & Morphing & \\ generation & & modeling & \\ \hline Database utilization & Template model fitting & \multicolumn{2}{c}{Scan-template} \\  & & & model-pair database \\ \hline \hline \end{tabular}
\end{table}
Table 1: Analysis of size-system generation method.  
Figure 1: Hardware configuration of the wearable robot.  
Statistical analysis techniques (e.g., the Grid method) are mainly used for segmenting sizing sections, and two-dimensional (2D) human body measurement data are used as sample data. The segmentation of the size section is based on the total coverage rate (e.g., 95%) and the minimum coverage rate (e.g., 2%) throughout the human body dimension database, forming a grid in the order of relatively high coverage rates until the specified coverage rate is satisfied. The segmentation of the size section can be approached in three ways: the grid method, the clustering method, and the optimization method, according to the method of determining the grid [27; 33]. The grid method generates several standardized grids to satisfy the specified total coverage rate (e.g., 95%) based on important variables [34]. The clustering method determines the appropriate number of clusters by analyzing the decreasing trend in the average distance between objects belonging to the cluster according to the change in the number of clusters (e.g., 2 to 50) [35]. The optimization method is a section segmentation method that minimizes total loss while maximizing target acceptance rate by using a loss function and an optimization algorithm [36]. Among the three methods, the grid method, which is most commonly used in the anthropometry field, was used as a method for subdividing the size section.  
Regarding the modeling techniques applicable to provide average human body model generation, wireframe modeling and morphing are generally used, and 3D human body shape model data are used as sample data. When using a database for average human body model generation, the template model-fitting technique is the most common, and the scan model database, including feature information, is used for sample data. According to a previous study [24], wireframe modeling is advantageous for various averaging practices that require high precision, and body section modeling using a human body model is performed to complement the missing body shape information between the sections of the wireframe. According to other studies [25; 26], morph modeling is advantageous for rapid averaging techniques that do not require high precision, but it requires controlling noise factors, such as polygon-count adjustments and shape removal, to ensure reliability. According to additional studies [29; 30; 31; 32], the template model-fitting technique generates an average model by matching the topology of 3D human body shape models, and it requires a database of pre-fitted scan-template model pairs. In this study, among the three approaches for average human body model generation, wireframe modeling, which is advantageous for precise averaging, was selected.