Bio-inspired upper limb soft exoskeleton to reduce stroke-induced complications. (24th August 2018)

• Record Type: Journal Article
• Authors: Li, Ning; Yang, Tie; Yu, Peng; Chang, Junling; Zhao, Liang; Zhao, Xingang; Elhajj, Imad H; Xi, Ning; Liu, Lianqing
• Is Part Of: Bioinspiration & biomimetics. Volume 13:Number 6(2018:Nov.)
• Publication Date: 2018-08-24
• Subjects: soft bionic exoskeleton robot -- functional anatomy -- muscle tension linearization -- biomimetic robot -- stroke-induced complication -- motion ability recovery -- lightweight and ergonomic; Biomimetics -- Periodicals; Biomedical materials -- Periodicals; Medical innovations -- Periodicals; Biomedical engineering -- Periodicals; 600
• DOI: 10.1088/1748-3190/aad8d4
• Languages: English
• ISSNs: 1748-3182

Abstract

Abstract: Stroke has become the leading cause of disability and the second-leading cause of mortality worldwide. Dyskinesia complications are the major reason of these high death and disability rates. As a tool for rapid motion function recovery in stroke patients, exoskeleton robots can reduce complications and thereby decrease stroke mortality rates. However, existing exoskeleton robots interfere with the wearer's natural motion and damage joints and muscles due to poor human-machine coupling. In this paper, a novel ergonomic soft bionic exoskeleton robot with 7 degrees of freedom was proposed to address these problems based on the principles of functional anatomy and sports biomechanics. First, the human motion system was analysed according to the functional anatomy, and the muscles were modelled as tension lines. Second, a soft bionic robot was established based on the musculoskeletal tension line model. Third, a robot control method mimicking human muscle control principles was proposed and optimized on a humanoid platform manufactured using 3D printing. After the control method was optimized, the motion trajectory similarities between humans and the platform exceeded 87%. Fourth, the force-assisted effect was tested based on electromyogram signals, and the results showed that muscle signals decreased by 58.17% after robot assistance. Finally, motion-assistance experiments were performed with stroke patients. The joint movement level increased by 174% with assistance, which allowed patients to engage in activities of daily living. With this robot, stroke patients could recover their motion functions, preventing complications and decreasing fatality and disability rates.