用全身肌肉模型模拟人类站立平衡与跌倒，揭示损伤影响与外骨骼辅助效果。
Bipedal Balance Control with Whole-body Musculoskeletal Standing and Falling Simulations
- 构建分层控制框架，基于全身体肌肉模型仿真人体平衡
- 发现肌肉损伤会显著影响平衡行为，模拟跌倒接触模式与临床一致
- 外骨骼辅助可降低扰动下肌肉负荷，适合康复与机器人研究
平衡控制对人和双足机器人系统至关重要。尽管动态行走中的平衡已受广泛关注，但静态平衡与跌倒的定量理解仍有限。本文提出一种分层控制流程，通过综合性的全身体肌肉骨骼系统模拟人体平衡。我们揭示了稳定站立时的时空平衡动态，分析了肌肉损伤对平衡行为的影响，并生成了与临床数据一致的跌倒接触模式。此外，模拟的髋关节外骨骼辅助在扰动下提升了平衡维持能力并降低了肌肉努力。该工作提供了实验难以获取的人体平衡肌级洞察，可为平衡障碍患者的靶向干预提供基础，并支持类人机器人系统的发展。
原文摘要 · Abstract (English)
Balance control is important for human and bipedal robotic systems. While dynamic balance during locomotion has received considerable attention, quantitative understanding of static balance and falling remains limited. This work presents a hierarchical control pipeline for simulating human balance via a comprehensive whole-body musculoskeletal system. We identified spatiotemporal dynamics of balancing during stable standing, revealed the impact of muscle injury on balancing behavior, and generated fall contact patterns that aligned with clinical data. Furthermore, our simulated hip exoskeleton assistance demonstrated improvement in balance maintenance and reduced muscle effort under perturbation. This work offers unique muscle-level insights into human balance dynamics that are challenging to capture experimentally. It could provide a foundation for developing targeted interventions for individuals with balance impairments and support the advancement of humanoid robotic systems.
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