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Purpose of Study Assessment of an individual's postural stability serves as an indirect measure for both physiological and biomechanical stresses placed on an individual. More recently, some individuals after COVID-19 (SARS-CoV-2) infection have been identified with neurological complaints (Post-Acute Sequelae of Covid - PASC). These individuals can also be predisposed to decreased postural stability and an increased risk for falls. The purpose of the project was to incorporate two different wearable technology (virtual reality (VR) based virtual immersive sensorimotor test - VIST and pressure senor-based smart sock) to assess postural stability among healthy and individuals with PASC to quantify the overall status of the postural control system. Methods Used All methods were conducted based on the University's Institutional Review Board (IRB# 21-296) with informed consent. A total of 12 males and females (six healthy and six with self-reported complaints of PASC) have completed the study so far. All participants were tested using the VIST, while standing on a force platform and wearing the smart sock simultaneously. The (VIST uses a VR headset and proprietary software to test an individual's integrated sensory, motor, and cognitive processes through eight unique tests (smooth pursuits, saccades, convergence, peripheral vision, object discrimination, gaze stability, head-eye coordination, cervical neuromotor control). Center of pressure (COP) data from force platform and pressure sensor data from the smart socks were used to calculate anterior-posterior and medial-lateral postural sway variables. These postural sway variables were analyzed using an independent samples t-test between the healthy and PASC groups at an alpha set at 0.05. Summary of 

Abstract Computational approaches, especially finite element analysis (FEA), have been rapidly growing in both academia and industry during the last few decades. FEA serves as a powerful and efficient approach for simulating real-life experiments, including industrial product development, machine design, and biomedical research, particularly in biomechanics and biomaterials. Accordingly, FEA has been a “go-to” high biofidelic software tool to simulate and quantify the biomechanics of the foot–ankle complex, as well as to predict the risk of foot and ankle injuries, which are one of the most common musculoskeletal injuries among physically active individuals. This paper provides a review of the in silico FEA of the foot–ankle complex. First, a brief history of computational modeling methods and finite element (FE) simulations for foot–ankle models is introduced. Second, a general approach to build an FE foot and ankle model is presented, including a detailed procedure to accurately construct, calibrate, verify, and validate an FE model in its appropriate simulation environment. Third, current applications, as well as future improvements of the foot and ankle FE models, especially in the biomedical field, are discussed. Finally, a conclusion is made on the efficiency and development of FEA as a computational approach in investigating the biomechanics of the foot–ankle complex. Overall, this review integrates insightful information for biomedical engineers, medical professionals, and researchers to conduct more accurate research on the foot–ankle FE models in the future.