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Design of soft smart shoes for joint angle estimation in human gait

机译:人体步态联合角估计软智能鞋设计

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Human gait involves activities in nervous and biomechanics of the musculoskeletal system.Thus,approaching the dynamics may be challenging.This paper aims to present the design of soft smart shoes for joint angle estimation in human gait.There are three pneumatic chambers at the heel,arch,and forefoot of the soft sole.Barometers embedded in every chambers are used to measure the ground reaction forces (GRFs).The inertia! sensors are installed on the outsole of shoes to detect the foot attitudes.The soft soles are made of silicone rubber to provide good compliance and ensure the comfort of human.Gaussian process regression (GPR) is established and serves as the mathematics foundation to explore the deep layer correlation between the joint angle and GRFs and foot attitudes which are regarded as the inputs of the model.The statistic nature of the proposed model offers superior flexibility and encouraging estimation results of joint angles.One potential use of the novel designed shoes and the proposed joint estimation method is the high-level control of exoskeletons and prosthetic legs.Finally,experiments were conducted to verify the superiority of the proposed algorithms.
机译:人态步态涉及肌肉骨骼系统的神经和生物力学的活动。这种情况可能是挑战的。本文旨在展示人体步态的关节角度估计的软智能鞋设计。鞋跟是三个气动室,拱门和柔软的鞋底的前掌管用于测量地面反作用力(GRF)。惯性!传感器安装在鞋外的鞋上以检测脚态态度。软鞋底由硅橡胶制成,提供良好的合规性,确保建立了人类的舒适性并确保了探索的数学基础并用作数学基础被视为模型输入的关节角度和GRF和脚态态之间的深层相关性。拟议模型的统计性质提供了卓越的灵活性和令人鼓舞的关节角度的估计结果。潜在使用新颖的设计鞋提出的联合估计方法是外骨骼和假肢的高水平控制。最后,进行实验以验证所提出的算法的优越性。

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