发表机构
Carnegie Mellon University（卡内基梅隆大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出以关节运动学为中间表示解耦硬件传感，使仅用开源数据训练的关节力矩估计器可跨髋/膝外骨骼及IMU平台使用，RMSE达0.15-0.19 Nm/kg，R2达0.62-0.85。
AI 中文摘要
目的：用于估计生理状态（特别是生物关节力矩）的数据驱动模型广泛用于外骨骼控制。然而，这些估计器通常与设备特定的传感器配置耦合，限制了控制器的迁移以及开源生物力学数据集的使用。方法：我们提出将关节运动学作为中间表示，将硬件特定的感知与下游的生物关节力矩估计解耦。一个使用关节角度和角速度的关节力矩估计器仅在开源生物力学数据上训练，并使用来自髋部外骨骼、膝部外骨骼和惯性测量单元（IMU）传感器套件的运动学数据进行评估，覆盖水平地面、上坡和下坡行走。结果：该估计器在使用髋部外骨骼运动学数据时实现了0.17 Nm/kg的均方根误差（RMSE）和0.79的决定系数（R2），使用膝部外骨骼运动学数据时为0.19 Nm/kg和0.62，使用来自IMU的双侧髋、膝和踝关节运动学数据时为0.15 Nm/kg和0.85。结论：关节运动学使得仅基于开源数据训练的估计器能够在不同的可穿戴平台上运行。意义：该框架可能减少目标设备的数据收集，并支持用于外骨骼控制和可穿戴生物力学的可迁移生物关节力矩估计。
英文摘要
Objective: Data-driven models that estimate physiological states, particularly biological joint moments, are widely used in exoskeleton control. However, these estimators are often coupled to device-specific sensor configurations, limiting controller transfer and the use of open-source biomechanics datasets. Methods: We proposed joint kinematics as an intermediate representation that decouples hardware-specific sensing from downstream biological joint moment estimation. A joint-moment estimator using joint angles and angular velocities was trained exclusively on open-source biomechanics data and evaluated using kinematics from a hip exoskeleton, knee exoskeleton, and inertial measurement unit (IMU) sensor suite during level-ground, ramp-ascent, and ramp-descent walking. Results: The estimator achieved an root mean square error (RMSE) of 0.17 Nm/kg and coefficient of determination (R2) of 0.79 using hip exoskeleton kinematics, 0.19 Nm/kg and 0.62 using knee exoskeleton kinematics, and 0.15 Nm/kg and 0.85 using kinematics derived from IMUs across bilateral hip, knee, and ankle joints. Conclusion: Joint kinematics enabled an estimator trained only on open-source data to operate across distinct wearable platforms. Significance: This framework may reduce target-device data collection and support transferable biological joint moment estimation for exoskeleton control and wearable biomechanics.
CommentsThis work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
