Neuromechanical Modeling of Human Quiet Stance

With the global population aging, understanding the mechanisms of human quiet stance is crucial for preventing falls and improving quality of life. Although human quiet stance has been studied for decades, there is still no consensus on the underlying neural control mechanisms. Existing studies have proposed a variety of biomechanical simplifications and neural control models, but their fragmented development has led to persistent debates and different interpretations of experimental data. This review integrates these diverse approaches, deepens the understanding of human quiet stance, and provides practical insights for rehabilitation, prosthetic design, and humanoid robotics. We first survey biomechanical models, from the simple inverted pendulum to detailed musculoskeletal representations. Then we examine neural control models, including stiffness, continuous, intermittent, optimal control, and multisensory integration, which explain how stability is maintained. By directly comparing these models, the review clarifies the causes of existing challenges in the field and emphasizes the interconnections among different control models. Beyond theoretical significance, the review also discusses practical applications and identifies future research directions to guide the development of integrated neuromechanical models that combine biomechanical complexity with realistic neural control schemes.