## 1 Introduction  
Compression garments have numerous therapeutic benefits in medical and clinical settings, such as enhancing blood flow, reducing swelling, preventing hypertrophic burn scars, and aiding in wound healing [1]. These garments are engineered to apply targeted pressure at specific body locations to achieve the intended therapeutic outcomes. The compression level is carefully calibrated to meet specific medical needs, making these garments crucial in managing conditions like venous disorders, lymphedema, and postoperative recovery [2, 3]. Their efficacy in promoting venous return, reducing edema, and improving wound healing through improved microcirculation is well documented [4, 5]. This strategic application of mechanical pressure underscores the need for precision in garment design to optimize clinical outcomes. Despite their effectiveness, compression garment design must strike a balance between therapeutic pressure and wearer comfort [6]. Poorly designed garments can negatively impact both the comfort and therapeutic effectiveness. Insufficient pressure limits the garment's therapeutic benefits, while excessive pressure can cause discomfort or numbness or even impede movement and breathing [7]. Compression garments are typically categorized based on the pressure that they exert, which is measured in millimeters of mercury (mmHg) and can be converted to kilopascals (kPa) for precision. The pressure ranges considered in this study include mild (1-1.9 kPa), moderate (2-2.66 kPa), firm (3-4 kPa), extra firm (4.1-5.3 kPa), and prescription-level (5.4-6.6 kPa). These ranges are critical in treating conditions such as mild to advanced venous insufficiency, lymphedema, and post-surgical recovery [8; 9]. The effectiveness of each pressure range depends on the pathology being addressed and the specific therapeutic outcomes required [7; 10]. Recent advancements in virtual fit technology, particularly 3D garment simulation (3 DGS), have shown significant promise in addressing the challenges of accurately simulating fabric behavior and enhancing garment performance. In this context, 3 DGS enables the precise modeling of garments under various real-world conditions without extensive physical testing. For instance, [PERSON], et al. (2024) demonstrated that the virtual fabric parameters closely aligned with the physical properties in their comparative study of physical versus virtual drape tests using commercial 3D garment software, CLO 3D (Version 7.2, CLO Virtual Fashion, Seoul, South Korea) [11]. Although 3 DGS is widely used for visual garment prototyping, there are few studies focused on developing functional garment designs, utilizing 3D fashion design software for medical or functional garment design purposes, due to the unverified accuracy of mechanical property simulations [12; 13]. To address this gap, researchers have begun exploring virtual mechanical representation in terms of garment stress, strain, and pressure using various 3D garment simulation programs, including Browzwear, Optitex, CLO3D, and Lectra [11; 12; 13; 14]. Recent studies, such as those by [PERSON] et al. (2023) [14], have explored the potential of 3 DGS to replicate the actual garment pressure in both static and dynamic settings. Their research utilized the Optitex Pattern Design Software (Version 11, EFI Optitex, Rosh Hayin, Israel) to simulate the fit of compression garments, like sports tights and tops, on virtual avatars. Their study involved comparisons across 13 body scan avatars, measuring the pressure at 22 specific points in both in vivo and virtual settings for a single female model. The findings indicated a general lack of correlation between the virtual and in vivo pressure values, except at the shoulder blade location. Additionally, other research using Vstitcher has highlighted challenges in simulating complex men's compression tops, showing mixed results in accurately simulating the pressure distribution across the torso [15].