Despite recent innovations in exoskeleton design and control, predicting subject-specific impacts of exoskeletons on gait remains challenging. We evaluated the ability of three classes of subject-specific phase-varying (PV) models to predict kinematic and myoelectric responses to ankle exoskeletons during walking, without requiring prior knowledge of specific user characteristics. Each model—PV, linear PV (LPV) and nonlinear PV (NPV)—leveraged Floquet theory to predict deviations from a nominal gait cycle due to exoskeleton torque, though the models differed in complexity and expected prediction accuracy. For 12 unimpaired adults walking with bilateral passive ankle exoskeletons, we predicted kinematics and muscle activity in response to three exoskeleton torque conditions. The LPV model's predictions were more accurate than the PV model when predicting less than 12.5% of a stride in the future and explained 49–70% of the variance in hip, knee and ankle kinematic responses to torque. The LPV model also predicted kinematic responses with similar accuracy to the more-complex NPV model. Myoelectric responses were challenging to predict with all models, explaining at most 10% of the variance in responses. This work highlights the potential of data-driven PV models to predict complex subject-specific responses to ankle exoskeletons and inform device design and control.

中文翻译：

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使用数据驱动模型预测步行对脚踝外骨骼的反应

尽管最近在外骨骼设计和控制方面取得了创新，但预测外骨骼对步态的特定主题影响仍然具有挑战性。我们评估了三类特定主题的相变 (PV) 模型在步行过程中预测对脚踝外骨骼的运动学和肌电反应的能力，而不需要特定用户特征的先验知识。每个模型——PV、线性 PV (LPV) 和非线性 PV (NPV)——利用 Floquet 理论来预测由于外骨骼扭矩引起的与标称步态周期的偏差，尽管这些模型在复杂性和预期预测精度上有所不同。对于使用双侧被动踝外骨骼行走的 12 名未受损成年人，我们预测了响应三种外骨骼扭矩条件的运动学和肌肉活动。LPV 模型 当预测未来的步幅小于 12.5% 时，s 的预测比 PV 模型更准确，并解释了髋、膝和踝关节运动学响应对扭矩的 49-70% 的差异。LPV 模型还以与更复杂的 NPV 模型相似的精度预测运动学响应。肌电反应很难用所有模型进行预测，最多只能解释 10% 的反应差异。这项工作突出了数据驱动的 PV 模型在预测复杂的受试者对脚踝外骨骼的特定反应并为设备设计和控制提供信息方面的潜力。肌电反应很难用所有模型进行预测，最多只能解释 10% 的反应差异。这项工作突出了数据驱动的 PV 模型在预测复杂的受试者对脚踝外骨骼的特定反应并为设备设计和控制提供信息方面的潜力。肌电反应很难用所有模型进行预测，最多只能解释 10% 的反应差异。这项工作突出了数据驱动的 PV 模型在预测复杂的受试者对脚踝外骨骼的特定反应并为设备设计和控制提供信息方面的潜力。