研究踝部外骨骼在行走与负重时的生物力学表现，为智能控制提供评估框架。
Ankle Exoskeletons in Walking and Load-Carrying Tasks: Insights into Biomechanics and Human-Robot Interaction
- 通过运动捕捉、肌电和扭矩传感器，系统分析外骨骼对步态的影响。
- 外骨骼减少肌肉活动，但轻微限制踝关节活动范围，负载时效果更明显。
- 结果适用于个性化外骨骼设计，适合康复与增强领域研究者参考。
背景：下肢外骨骼可提升生活质量，但缺乏评估其生物力学与人机交互影响的系统框架，制约了自适应个性化控制策略的发展。理解对关节运动学、肌电活动及人机交互（HRI）力矩的影响，是提升可穿戴机器人可用性的关键。目标：提出一种系统方法，评估踝部外骨骼在步行与负重（10 kg前背包）任务中的影响，重点关注关节运动学、肌电活动与HRI力矩信号。方法：采用Xsens MVN（惯性运动捕捉）、Delsys EMG与单侧外骨骼，开展三项实验：（1）孤立背屈/跖屈；（2）步态分析（两受试者，被动/主动模式）；（3）辅助状态下的负重行走。结果与结论：第一项实验确认HRI传感器可捕捉主动与被动力矩，提供方向性力矩信息。第二项实验显示设备轻微限制踝关节活动范围（RoM），但支持正常步态模式，所有辅助模式下肌电活动下降，尤其在主动模式中显著。HRI力矩随步态相位变化，同步性降低，提示需优化支持策略。第三项实验发现负重增加胫骨前肌（TA）与腓肠肌（GM）活动，但外骨骼部分缓解用户负荷，较无辅助步行时肌电活动降低。同时HRI力矩上升，揭示负载下人机动态特性。结果表明，应针对特定设备与个体定制评估方法，并为未来外骨骼生物力学与人机交互研究提供通用框架。
原文摘要 · Abstract (English)
Background: Lower limb exoskeletons can enhance quality of life, but widespread adoption is limited by the lack of frameworks to assess their biomechanical and human-robot interaction effects, which are essential for developing adaptive and personalized control strategies. Understanding impacts on kinematics, muscle activity, and HRI dynamics is key to achieve improved usability of wearable robots. Objectives: We propose a systematic methodology evaluate an ankle exoskeleton's effects on human movement during walking and load-carrying (10 kg front pack), focusing on joint kinematics, muscle activity, and HRI torque signals. Materials and Methods: Using Xsens MVN (inertial motion capture), Delsys EMG, and a unilateral exoskeleton, three experiments were conducted: (1) isolated dorsiflexion/plantarflexion; (2) gait analysis (two subjects, passive/active modes); and (3) load-carrying under assistance. Results and Conclusions: The first experiment confirmed that the HRI sensor captured both voluntary and involuntary torques, providing directional torque insights. The second experiment showed that the device slightly restricted ankle range of motion (RoM) but supported normal gait patterns across all assistance modes. The exoskeleton reduced muscle activity, particularly in active mode. HRI torque varied according to gait phases and highlighted reduced synchronization, suggesting a need for improved support. The third experiment revealed that load-carrying increased GM and TA muscle activity, but the device partially mitigated user effort by reducing muscle activity compared to unassisted walking. HRI increased during load-carrying, providing insights into user-device dynamics. These results demonstrate the importance of tailoring exoskeleton evaluation methods to specific devices and users, while offering a framework for future studies on exoskeleton biomechanics and HRI.
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