The rapid develpment of assistive devices, such as exoskeletons, prosthetics, and medical support systems, presents significant challenges in integrating mechanical devices with human physiology. Challenges still exist today because there is a subject specific tolerance to mechanical loading. Pressure ulcer development, in particular, is driven not solely by instantaneous deformation but by the cumulative tissue damage that occurs over time [2]. This abstract outlines ongoing work in our Institute, focusing on the time-dependent response of soft tissues under prolonged loading through two complementary modeling approaches The first approach investigates whether the viscoelastic properties of muscle and adipose tissues can be independently characterized using ultrasound imaging. A new ramp and hold procedure was developed to characterise the creep and force relaxation properties of thigh soft tissues using an ultrasound imaging machine. Results showed that the primary viscoelastic behavior occurs within the first 60 seconds of loading, indicating that brief ultrasound scans can effectively capture key tissue stiffness characteristics. This approach holds potential for assessing individual risk for conditions such as pressure ulcers by identifying patient-specific viscoelastic properties. Although viscoelastic models provide insights into tissue stiffness, they treat soft tissue as a single-phase material, overlooking fluid-solid interactions and the biochemical processes underlying pressure ulcer formation. To bridge this gap, we applied a poroelastic model, conceptualizing tissue as a biphasic medium to account for interactions between the solid matrix and interstitial fluid. When applied to simulate the mechanical response of human skin under extension, this poroelastic model showed close alignment with observed mechanical responses, with an RMSE of 8.84 × 10⁻³ N, highlighting its potential for clinical applications. Future work will integrate cellular and inflammatory processes into the poroelastic framework, improving predictions of tissue damage.