Pilot study on human-in-the-loop optimization of ankle exoskeleton assistance based on plantar pressure interaction

Jianyu Chen; Jianquan Ding; Juanjuan Zhang

doi:10.1117/12.3009517

16 October 2023 Pilot study on human-in-the-loop optimization of ankle exoskeleton assistance based on plantar pressure interaction

Jianyu Chen, Jianquan Ding, Juanjuan Zhang

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Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 1280323 (2023) https://doi.org/10.1117/12.3009517
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

Lower limb exoskeletons can enhance human locomotion performance and provide aid in rehabilitation. Due to human interpersonal differences, identifying a proper assistance strategy is challenging. The uptake of embodied intelligence that learns individuals’ needs and tasks’ requirements will help exoskeleton systems achieve their potential under different scenarios. Utilizing the evolution strategy to explore human reaction under exoskeleton assistance, “human-in-the- loop” (HIL) optimization is promising to obtain suitable assistance patterns. However, most current HIL optimizations use physiological signals, such as metabolic consumption and muscle activity, as the objective function to minimize, which need a long time to be evaluated and are inconvenient for real-life use. In the study, we aimed to construct a HIL optimization strategy to search effective exoskeleton assistance patterns based on the human-robot interactive force measured by wearable sensors. We first used a unilateral cable-driven ankle exoskeleton to explore the characteristics of human-robot interaction under 20 assistance patterns. A plantar-pressure-based cost function was constructed and real-timely evaluated for HIL optimization. A pilot experiment was conducted with a single participant. Optimized exoskeleton assistance can improve the individual walking economy by a 41.2% reduction in soleus muscle activity and a 21.3% decrease in metabolic cost. The proposed method is promising to improve the HIL optimization time efficiency and promote more effective real-life exoskeleton applications.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Jianyu Chen, Jianquan Ding, and Juanjuan Zhang "Pilot study on human-in-the-loop optimization of ankle exoskeleton assistance based on plantar pressure interaction", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 1280323 (16 October 2023); https://doi.org/10.1117/12.3009517

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KEYWORDS

Muscles

Gait analysis

Electromyography

Sensors

Reflection

Covariance matrices

Resistance

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