Human-robot global Simulink modeling and analysis for an end-effector upper limb rehabilitation robot_Journal of Biomedical Engineering

Authors：

LIU Yali ,  JI Linhong

Division of Intelligent and Biomechanical System, State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, P.R.China;

Corresponding author：

JI Linhong, Email: jilh@tsinghua.edu.cn

Keywords：

human-robot global Simulink model; end-effector upper limb rehabilitation robots; planar movement; training trajectory

DOI：

10.7507/1001-5515.201703070

Video：

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Abstract Full text Figures/Tables Video References Cited by

Robot rehabilitation has been a primary therapy method for the urgent rehabilitation demands of paralyzed patients after a stroke. The parameters in rehabilitation training such as the range of the training, which should be adjustable according to each participant’s functional ability, are the key factors influencing the effectiveness of rehabilitation therapy. Therapists design rehabilitation projects based on the semiquantitative functional assessment scales and their experience. But these therapies based on therapists’ experience cannot be implemented in robot rehabilitation therapy. This paper modeled the global human-robot by Simulink in order to analyze the relationship between the parameters in robot rehabilitation therapy and the patients’ movement functional abilities. We compared the shoulder and elbow angles calculated by simulation with the angles recorded by motion capture system while the healthy subjects completed the simulated action. Results showed there was a remarkable correlation between the simulation data and the experiment data, which verified the validity of the human-robot global Simulink model. Besides, the relationship between the circle radius in the drawing tasks in robot rehabilitation training and the active movement degrees of shoulder as well as elbow was also matched by a linear, which also had a remarkable fitting coefficient. The matched linear can be a quantitative reference for the robot rehabilitation training parameters.

Citation： LIU Yali, JI Linhong. Human-robot global Simulink modeling and analysis for an end-effector upper limb rehabilitation robot. Journal of Biomedical Engineering, 2018, 35(1): 8-14. doi: 10.7507/1001-5515.201703070 Copy

1.	Hu Xiaoling, Tong K Y, Song Rong, et al. Variation of muscle coactivation patterns in chronic stroke during robot-assisted elbow training. Arch Phys Med Rehabil, 2007, 88(8): 1022-1029.
2.	Basteris A, Nijenhuis S M, Stienen A H, et al. Training modalities in robot-mediated upper limb rehabilitation in stroke: a framework for classification based on a systematic review. J Neuroeng Rehabil, 2014, 11(1): 111-121.
3.	Brunner I, Skouen J S, Hofstad H, et al. Virtual reality training for upper extremity in subacute stroke (VIRTUES): study protocol for a randomized controlled multicenter trial. BMC Neurol, 2014, 14(1): 186-190.
4.	Cozens J A. Robotic assistance of an active upper limb exercise in neurologically impaired patients. IEEE Trans Rehabil Eng, 1999, 7(2): 254-256.
5.	Blank A A, French J A, Pehlivan A U, et al. Current trends in robot-assisted upper-limb stroke rehabilitation: promoting patient engagement in therapy. Curr Phys Med Rehabil Rep, 2014, 2(3): 184-195.
6.	Volpe B T, Ferraro M, Lynch D, et al. Robotics and other devices in the treatment of patients recovering from stroke. Curr Atheroscler Rep, 2005, 5(6): 465-470.
7.	杨启志, 曹电锋, 赵金海. 上肢康复机器人研究现状的分析. 机器人, 2013, 35(5): 630-640.
8.	Olesh E V, Yakovenko S, Gritsenko V. Automated assessment of upper extremity movement impairment due to stroke. PLoS One, 2014, 9(8): e104487.
9.	李会军, 宋爱国. 上肢康复训练机器人的研究进展及前景. 机器人技术与应用, 2006, 4: 32-36.
10.	Zhang Yubo, Wang Zixi, Ji Linhong, et al. The clinical application of the upper extremity compound movements rehabilitation training robot// Proceedings of the 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005. Chicago, IL, USA: 2005: 91-94.
11.	Nef T, Mihelj M, Colombo G, et al. ARMin-robot for rehabilitation of the upper extremities// Proceedings of 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006. Orlando, FL, USA: 2006, 3152-3157.
12.	Jarrassé N, Proietti T, Crocher V, et al. Robotic exoskeletons: a perspective for the rehabilitation of arm coordination in stroke patients. Front Hum Neurosci, 2014, 8: 947-955.
13.	Mihelj M, Nef T, Riener R. ARMin II-7 DoF rehabilitation robot: mechanics and kinematics// Proceedings of 2007 IEEE International Conference on Robotics and Automation. Roma, Italy: 2007: 4120-4125.
14.	李醒, 王建辉, 方晓柯. 五自由度上肢康复机器人动力学建模及仿真. 控制工程, 2012, 19(5): 823-826, 831.
15.	朱雪枫. 五自由度上肢康复机器人数学建模与仿真. 沈阳: 东北大学, 2011.
16.	Behnke Robert S. Kinetic anatomy. Champaign: Human Kinetics, 2006.
17.	Maciejasz P, Eschweiler J, Gerlach-Hahn K, et al. A survey on robotic devices for upper limb rehabilitation. J Neuroeng Rehabil, 2014, 11(1): 3-10.
18.	Valentin G, Luminita G, Mihai D, et al. A virtual system for simulation of human upper limb. Lecture Notes in Engineering & Computer Science, 2009, 2177(1): 101-104.
19.	Dipietro L, Krebs H I, Fasoli S E, et al. Changing motor synergies in chronic stroke. J Neurophysiol, 2007, 98(2): 757-768.

1. Hu Xiaoling, Tong K Y, Song Rong, et al. Variation of muscle coactivation patterns in chronic stroke during robot-assisted elbow training. Arch Phys Med Rehabil, 2007, 88(8): 1022-1029.
2. Basteris A, Nijenhuis S M, Stienen A H, et al. Training modalities in robot-mediated upper limb rehabilitation in stroke: a framework for classification based on a systematic review. J Neuroeng Rehabil, 2014, 11(1): 111-121.
3. Brunner I, Skouen J S, Hofstad H, et al. Virtual reality training for upper extremity in subacute stroke (VIRTUES): study protocol for a randomized controlled multicenter trial. BMC Neurol, 2014, 14(1): 186-190.
4. Cozens J A. Robotic assistance of an active upper limb exercise in neurologically impaired patients. IEEE Trans Rehabil Eng, 1999, 7(2): 254-256.
5. Blank A A, French J A, Pehlivan A U, et al. Current trends in robot-assisted upper-limb stroke rehabilitation: promoting patient engagement in therapy. Curr Phys Med Rehabil Rep, 2014, 2(3): 184-195.
6. Volpe B T, Ferraro M, Lynch D, et al. Robotics and other devices in the treatment of patients recovering from stroke. Curr Atheroscler Rep, 2005, 5(6): 465-470.
7. 杨启志, 曹电锋, 赵金海. 上肢康复机器人研究现状的分析. 机器人, 2013, 35(5): 630-640.
8. Olesh E V, Yakovenko S, Gritsenko V. Automated assessment of upper extremity movement impairment due to stroke. PLoS One, 2014, 9(8): e104487.
9. 李会军, 宋爱国. 上肢康复训练机器人的研究进展及前景. 机器人技术与应用, 2006, 4: 32-36.
10. Zhang Yubo, Wang Zixi, Ji Linhong, et al. The clinical application of the upper extremity compound movements rehabilitation training robot// Proceedings of the 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005. Chicago, IL, USA: 2005: 91-94.
11. Nef T, Mihelj M, Colombo G, et al. ARMin-robot for rehabilitation of the upper extremities// Proceedings of 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006. Orlando, FL, USA: 2006, 3152-3157.
12. Jarrassé N, Proietti T, Crocher V, et al. Robotic exoskeletons: a perspective for the rehabilitation of arm coordination in stroke patients. Front Hum Neurosci, 2014, 8: 947-955.
13. Mihelj M, Nef T, Riener R. ARMin II-7 DoF rehabilitation robot: mechanics and kinematics// Proceedings of 2007 IEEE International Conference on Robotics and Automation. Roma, Italy: 2007: 4120-4125.
14. 李醒, 王建辉, 方晓柯. 五自由度上肢康复机器人动力学建模及仿真. 控制工程, 2012, 19(5): 823-826, 831.
15. 朱雪枫. 五自由度上肢康复机器人数学建模与仿真. 沈阳: 东北大学, 2011.
16. Behnke Robert S. Kinetic anatomy. Champaign: Human Kinetics, 2006.
17. Maciejasz P, Eschweiler J, Gerlach-Hahn K, et al. A survey on robotic devices for upper limb rehabilitation. J Neuroeng Rehabil, 2014, 11(1): 3-10.
18. Valentin G, Luminita G, Mihai D, et al. A virtual system for simulation of human upper limb. Lecture Notes in Engineering & Computer Science, 2009, 2177(1): 101-104.
19. Dipietro L, Krebs H I, Fasoli S E, et al. Changing motor synergies in chronic stroke. J Neurophysiol, 2007, 98(2): 757-768.

Journal of Biomedical Engineering

Human-robot global Simulink modeling and analysis for an end-effector upper limb rehabilitation robot

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