[Pubmed] Research on Exoskeleton Human-Machine Interaction for Walking Assistance in Myasthenia

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[Pubmed] Research on Exoskeleton Human-Machine Interaction for Walking Assistance in Myasthenia

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Zhongguo Yi Liao Qi Xie Za Zhi. 2026 Jul 30;50(4):430-439. doi: 10.12455/j.issn.1671-7104.250593.

ABSTRACT

To address the insufficient human-machine interaction adaptability in current lower-limb rehabilitation exoskeletons, this study proposes a lower-limb assistive exoskeleton featuring active actuation at the hip and knee joints and passive following at the ankle joint. A rigid self-adaptive human-machine interface is adopted to provide both effective assistive torque and structural compliance, aiming to deliver gait assistance for individuals with muscle weakness while improving wearing comfort. First, a bionic geometric structure of the exoskeleton was constructed based on human lower-limb biomechanics, and passive degrees of freedom in the attachment components were designed using a serial-chain topology. The forward kinematics model of the exoskeleton was then established and verified using the D-H method. Finally, a human-exoskeleton coupled model was built on the OpenSim platform, in which the human model was configured to three muscle strength conditions (100%, 80% and 60% of the maximal isometric force). The assistive performance and interaction characteristics of the designed exoskeleton were evaluated through changes in two key indicators-overall metabolic consumption and human-robot interaction forces-as well as variations in hip and knee flexor-extensor muscle forces. The results show that the proposed exoskeleton effectively reduces human-machine interaction forces, with peak interaction forces at the thigh decreasing from 70 N to 20 N and those at the shank decreasing from 150 N to 30 N. The overall metabolic cost of the wearer was reduced by 13.8%-15.4%, and the muscle force outputs of major hip and knee muscle groups markedly decreased. These findings validate the rationality of the design and demonstrate its performance in adaptive human-machine interaction assistance, highlighting its application potential in rehabilitation training and gait assistance for individuals with muscle weakness.

PMID:42675844 | DOI:10.12455/j.issn.1671-7104.250593


Source: https://pubmed.ncbi.nlm.nih.gov/4267584 ... 9&v=2.20.1
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