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Yu S, Huang TH, Di Lallo A, Zhang S, Wang T, Fu Q, Su H. Bio-inspired design of a self-aligning, lightweight, and highly-compliant cable-driven knee exoskeleton. Front Hum Neurosci 2022; 16:1018160. [PMID: 36419645 PMCID: PMC9677347 DOI: 10.3389/fnhum.2022.1018160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 10/19/2022] [Indexed: 04/07/2024] Open
Abstract
Powered knee exoskeletons have shown potential for mobility restoration and power augmentation. However, the benefits of exoskeletons are partially offset by some design challenges that still limit their positive effects on people. Among them, joint misalignment is a critical aspect mostly because the human knee joint movement is not a fixed-axis rotation. In addition, remarkable mass and stiffness are also limitations. Aiming to minimize joint misalignment, this paper proposes a bio-inspired knee exoskeleton with a joint design that mimics the human knee joint. Moreover, to accomplish a lightweight and high compliance design, a high stiffness cable-tension amplification mechanism is leveraged. Simulation results indicate our design can reduce 49.3 and 71.9% maximum total misalignment for walking and deep squatting activities, respectively. Experiments indicate that the exoskeleton has high compliance (0.4 and 0.1 Nm backdrive torque under unpowered and zero-torque modes, respectively), high control bandwidth (44 Hz), and high control accuracy (1.1 Nm root mean square tracking error, corresponding to 7.3% of the peak torque). This work demonstrates performance improvement compared with state-of-the-art exoskeletons.
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Affiliation(s)
- Shuangyue Yu
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
| | - Tzu-Hao Huang
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
| | - Antonio Di Lallo
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
| | - Sainan Zhang
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
- Department of Mechanical Engineering, City College of New York, New York, NY, United States
| | - Tian Wang
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
| | - Qiushi Fu
- Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL, United States
- NeuroMechanical Systems Laboratory, Biionix (Bionic Materials, Implants & Interfaces) Cluster, University of Central Florida, Orlando, FL, United States
| | - Hao Su
- Lab of Biomechatronics and Intelligent Robotics, Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States
- Joint North Carolina State University/The University of North Carolina Department of Biomedical Engineering, NC State University, Raleigh, NC, United States
- Joint North Carolina State University/The University of North Carolina Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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