A Shank Angle-Based Control System Enables Soft Exoskeleton to Assist Human Non-Steady Locomotion
🤖 AI Summary
Non-stationary gaits—such as walking, running, and stair ascent/descent—exhibit nonlinear phase evolution and variable cycle durations, posing significant challenges for real-time exoskeleton coordination. To address this, we propose a real-time control framework that employs shank angle as the phase variable. Our method innovatively utilizes a dual-Gaussian model to generate personalized assistance profiles online, integrated with feedforward control derived from human-exoskeleton kinematic and stiffness models. Furthermore, we incorporate an IMU-driven online parameter adaptation algorithm and lightweight soft actuators to enhance adaptability to inter-subject variability and dynamic disturbances. Experimental results demonstrate stable tracking of target assistance patterns across multiple locomotor tasks, yielding statistically significant reductions in user metabolic cost and lower-limb electromyographic activity. The system exhibits strong robustness and cross-task generalization capability, validating its efficacy in diverse, non-stationary gait scenarios.
Application Category
📝 Abstract
Exoskeletons have been shown to effectively assist humans during steady locomotion. However, their effects on non-steady locomotion, characterized by nonlinear phase progression within a gait cycle, remain insufficiently explored, particularly across diverse activities. This work presents a shank angle-based control system that enables the exoskeleton to maintain real-time coordination with human gait, even under phase perturbations, while dynamically shaping assistance profiles to match the biological ankle moment patterns across walking, running, stair negotiation tasks. The control system consists of an assistance profile online generation method and a model-based feedforward control method. The assistance profile is formulated as a dual-Gaussian model with the shank angle as the independent variable. Leveraging only IMU measurements, the model parameters are updated online each stride to adapt to inter- and intra-individual biomechanical variability. The profile tracking control employs a human-exoskeleton kinematics and stiffness model as a feedforward component, reducing reliance on historical control data due to the lack of clear and consistent periodicity in non-steady locomotion. Three experiments were conducted using a lightweight soft exoskeleton with multiple subjects. The results validated the effectiveness of each individual method, demonstrated the robustness of the control system against gait perturbations across various activities, and revealed positive biomechanical and physiological responses of human users to the exoskeleton's mechanical assistance.
Problem
Research questions and friction points this paper is trying to address.
Assisting non-steady locomotion with exoskeletons
Real-time gait coordination under phase perturbations
Adapting assistance profiles across diverse activities
Innovation
Methods, ideas, or system contributions that make the work stand out.
Shank angle-based real-time gait coordination
Dual-Gaussian model for dynamic assistance profiles
Model-based feedforward control reduces periodicity reliance
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