Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/170247
Title: Jamming enabled variable stiffness wrist exoskeleton for tremor suppression
Authors: Wang, Guohui
Wang, Hailu
Gao, Weinan
Yang, Xudong
Wang, Yifan
Keywords: Engineering::Mechanical engineering
Issue Date: 2023
Source: Wang, G., Wang, H., Gao, W., Yang, X. & Wang, Y. (2023). Jamming enabled variable stiffness wrist exoskeleton for tremor suppression. IEEE Robotics and Automation Letters, 8(6), 3693-3700. https://dx.doi.org/10.1109/LRA.2023.3270747
Project: M21K2c0118 
A2084c0162 
MOH-001184-01
NAP (020482) 
Journal: IEEE Robotics and Automation Letters
Abstract: Parkinson's disease is a chronic disorder that affects the central nervous system of patients. It affects millions of aging populations around the world every year. Approximately 80% of Parkinson's disease patients suffer from tremors which significantly reduce their life quality. In this study, we present a variable stiffness wrist exoskeleton (VSW-Exo) that is lightweight (less than 300 g on the wrist) and can effectively suppress wrist tremors in all three degrees of freedom. The functioning material of the variable stiffness unit is a novel chain mail-like structured fabric whose stiffness can be pneumatically controlled over a wide range under the jamming transition. Bending and Torsion tests are performed to characterize the VSW-Exo's damping force and torque. To evaluate the VSW-Exo's performance on human bodies, we devise vibration experiments to evaluate the prototype's performance on tremor suppression. The testing results show that our VSW-Exo's tremor suppression efficiency can reach up from 64.11 ± 10.92% to 67.24 ± 6.74%. Compared to other tremor suppression devices, our VSW-Exo can provide enough damping forces and torques to suppress tremors in all 3 directions with high efficiency and low weight on the wrist.
URI: https://hdl.handle.net/10356/170247
ISSN: 2377-3766
DOI: 10.1109/LRA.2023.3270747
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2023 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:MAE Journal Articles

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