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An eight-degree-of-freedom upper extremity exoskeleton rehabilitation robot: design, optimization, and validation

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Abstract

Upper extremity exoskeleton rehabilitation robots can be used for the training of patients with upper extremity motor dysfunction. In most cases, the design of such robots focuses on the configuration and the human-machine compatibility. For patients, the use of an exoskeleton rehabilitation robot mainly aims to improve their movement ability, which depends on the range of movement of the upper extremity joints. This paper proposes an eight-degree-of-freedom (DOF) upper extremity exoskeleton rehabilitation robot to improve the movement range of the patient’s upper extremity joints. The structural parameters of the shoulder joint are optimized and analyzed by the kinematic equations of the mechanism and the cyclic iteration algorithm such that the movement range of the patient joint can be maximized. The movement space of the robot is then simulated. Finally, the movement range of the rehabilitation robot joints and the movement space of the rehabilitation robot were measured. Experimental results show that the upper extremity exoskeleton rehabilitation robot can meet the patient’s shoulder, elbow, and wrist movement range, and the overlap with the human upper extremity movement space is 97.1 % and 95.7 % in the coronal and sagittal planes, respectively.

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Acknowledgments

This research was funded by the National Key Research and Development Program (2019YFB1312500), the National Natural Science Foundation of China (U1913216), and the Key Research and Development Program of Hebei (19211820D, 20371801D).

Author information

Authors and Affiliations

  1. Parallel Robot and Mechatronic System Laboratory of Hebei Province, Yanshan University, Qinhuangdao, 066004, China

    Yuansheng Ning, Hongbo Wang, Junjie Tian, Yu Tian, Congliang Yang, Jian Wei & Jianye Niu

  2. Key Laboratory of Advanced Forging & Stamping Technology and Science of Ministry of Education, Yanshan University, Qinhuangdao, 066004, China

    Yuansheng Ning, Hongbo Wang, Junjie Tian, Yu Tian, Congliang Yang, Jian Wei & Jianye Niu

  3. Academy for Engineering & Technology, Fudan University, Shanghai, 200433, China

    Hongbo Wang

  4. College of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan, China

    Hao Yan

Authors
  1. Yuansheng Ning
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  2. Hongbo Wang
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  3. Junjie Tian
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  4. Hao Yan
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  5. Yu Tian
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  6. Congliang Yang
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  7. Jian Wei
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  8. Jianye Niu
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Corresponding author

Correspondence to Jianye Niu.

Additional information

Yuansheng Ning received his M.S. degree in mechanical engineering from Taiyuan University of Science and Technology, Taiyuan, China, in 2020. He is currently pursuing his doctor’s degree in mechatronic engineering at Yanshan University, Qinhuangdao, China. His current research interests include rehabilitation robot and robotic compliance control.

HongBo Wang currently holds B.S. and M.S. degrees from the Institute of Northeast Heavy Machinery, Qiqihar, China, in 1982 and 1986, respectively. He received his Ph.D. degree from Nagasaki University, Nagasaki, Japan in 1997. Since 2009, he has been working with Yanshan University, Qinhuangdao, China as a Professor. His current research interests lie in rehabilitation and assisting robots for the disabled and the elderly.

Junjie Tian received his M.S. degree in chemical process equipment from Tianjin University, China, in 2018. He is currently pursuing his doctor’s degree in mechatronic engineering at Yanshan University, China. His current research interests include rehabilitation robot and robotic compliance control.

Hao Yan currently holds a B.S. degree in mechanical engineering and M.S. and Ph.D. degrees in mechatronic engineering from Yanshan University, Qinhuangdao, China, in 2014, 2017, and 2021, respectively. He is currently a lecturer with the Hebei University of Engineering, China. His research interests include rehabilitation robot and computer control.

Yu Tian received his B.S. degree in mechanical engineering from the Yanshan University, Qinhuangdao, China, in 2015, where he is currently pursuing his Ph.D. degree in mechatronics. His research interests include rehabilitation and nursing robots.

Congliang Yang received his B.S. degree in Mechanical Design Manufacture and Automation from the Hebei University of Science and Technology in 2020, Hebei, China. He is currently an M.A. student in the School of Mechanical Engineering, Yanshan University. His research interests include machine learning algorithms and compliance control of exoskeleton robots.

Jian Wei received his B.E. degree in mechanical engineering from Qingdao University, China, in 2020. He is currently pursuing his master’s degree in mechatronic engineering at Yanshan University, China. His current research interests include rehabilitation robot, motion planning, and dynamics.

JianYe Niu currently holds a B.S. degree in mechanical engineering and M.S. and Ph.D. degrees in mechatronic engineering from Yanshan University, Qinhuangdao, China, in 2005, 2008, and 2019, respectively. He is currently an Associate Professor in Yanshan University, China. His research interests include parallel mechanism and its application, rehabilitation robot, mechanical engineering, and artificial neural network.

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Ning, Y., Wang, H., Tian, J. et al. An eight-degree-of-freedom upper extremity exoskeleton rehabilitation robot: design, optimization, and validation. J Mech Sci Technol 36, 5721–5733 (2022). https://doi.org/10.1007/s12206-022-1034-5

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  • DOI: https://doi.org/10.1007/s12206-022-1034-5

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