|
|
上肢康复机器人现状研究
|
Abstract:
随着人口老龄化加剧，脑卒中患者的数量也在增多。在康复治疗方面面临着康复治疗师数量不足、人力成本高等问题，康复治疗需求广泛。康复机器人对解决此类问题有着准确性、高效性和可控性的优点，并且可以准确的获得患者康复治疗时的数据，便于对康复治疗进行评估，所以康复机器人在康复治疗方面潜力巨大。自上肢康复机器人问世起，其结构设计与控制方式多种多样。本文从上肢康复机器人末端执行器式与外骨骼式的结构设计和主动与被动的控制策略出发，总结了其优缺点与对康复治疗效果的影响，为上肢康复机器人的设计和应用提供了参考。最后对上肢康复机器人进行总结与展望，对上肢康复机器人未来的发展提出建议。
With the aging of the population, the number of stroke patients is also increasing. In terms of rehabilitation treatment, there are problems of insufficient number of rehabilitation therapists and high labour cost, and rehabilitation treatment needs are extensive. Rehabilitation robots have the advantages of accuracy, efficiency and controllability in solving such problems, and can accurately obtain the data of patients during rehabilitation treatment, which is convenient for evaluating rehabilitation treatment. Therefore, rehabilitation robots have great potential in rehabilitation treatment. Since the advent of upper limb rehabilitation robots, there have been various structural designs and control methods. Starting from the structural design of the end effector and exoskeleton of the upper limb rehabilitation robot and the active and passive control strategies, this paper summarizes its advantages and disadvantages and its impact on the effect of rehabilitation treatment, which provides a reference for the design and application of the upper limb rehabilitation robot. Finally, the upper limb rehabilitation robot is summarized and prospected, and suggestions for the future development of the upper limb rehabilitation robot are put forward.
| [1] | 王杰秀, 安超. 全球老龄化: 事实？影响与政策因应[J]. 社会保障评论, 2018, 2(4): 14-30. |
| [2] | 第七次全国人口普查结果: 中国人口14.1178亿[J]. 新民周刊, 2021(17): 35. |
| [3] | 王陇德, 彭斌, 张鸿祺, 等. 《中国脑卒中防治报告2020》概要[J]. 中国脑血管病杂志, 2022, 19(2): 136-144. |
| [4] | 王亚楠, 吴思缈, 刘鸣. 中国脑卒中15年变化趋势和特点[J]. 华西医学, 2021, 36(6): 803-807. |
| [5] | 陈礼静, 李娟, 储静. 康复机器人在卒中患者中的应用[J]. 上海护理, 2023, 23(3): 72-76. |
| [6] | 石男强, 刘刚峰, 郑天骄, 等. 下肢康复机器人的研究进展与临床应用[J]. 信息与控制, 2021, 50(1): 43-53. |
| [7] | Dorrance, A.M. and Fink, G. (2015) Effects of Stroke on the Autonomic Nervous System. Comprehensive Physiology, 5, 1241-1263. https://doi.org/10.1002/cphy.c140016 |
| [8] | 喻洪流. 康复机器人: 未来十大远景展望[J]. 中国康复医学杂志, 2020, 35(8): 900-902. |
| [9] | 余灵, 喻洪流. 上肢康复机器人研究进展[J]. 生物医学工程学进展, 2020, 41(3): 134-138, 143. |
| [10] | 冷冰, 李旺鑫, 刘斌. 上肢康复机器人研究及发展[J]. 科学技术与工程, 2021, 21(11): 4311-4322. |
| [11] | Nelson, C.A., Nouaille, L. and Poisson, G. (2020) A Redundant Rehabilitation Robot with a Variable Stiffness Mechanism. Mechanism and Machine Theory, 150, Article ID: 103862.
https://doi.org/10.1016/j.mechmachtheory.2020.103862 |
| [12] | Passon, A., Schauer, T. and Seel, T. (2022) Inertial-Robotic Motion Tracking in End-Effector-Based Rehabilitation Robots. Frontiers in Robotics and AI, 7, Article 554639. https://doi.org/10.3389/frobt.2020.554639 |
| [13] | Fraile, C.J., Pérez-Turiel, J., Baeyens, E., et al. (2016) E2rebot: A Robotic Platform for Upper Limb Rehabilitation in Patients with Neuromotor Disability. Advances in Mechanical Engineering, 8, 1-13.
https://doi.org/10.1177/1687814016659050 |
| [14] | Li, L.Y., Han, J., Li, X., et al. (2022) A Novel End-Effector Upper Limb Rehabilitation Robot: Kinematics Modeling Based on Dual Quaternion and Low-Speed Spiral Motion Tracking Control. International Journal of Advanced Robotic Systems, 19, 1-15. https://doi.org/10.1177/17298806221118855 |
| [15] | Dong, M.J., Fan, W., Li, J. and Zhang, P.F. (2022) Patient-Specific Exercises with the Development of an End-Effector Type Upper Limb Rehabilitation Robot. Journal of Healthcare Engineering, 2022, Article ID: 4125606.
https://doi.org/10.1155/2022/4125606 |
| [16] | Lo, H.S. and Xie, S.Q. (2012) Exoskeleton Robots for Upper-Limb Rehabilitation: State of the Art and Future Prospects. Medical Engineering & Physics, 34, 261-268. https://doi.org/10.1016/j.medengphy.2011.10.004 |
| [17] | Brihmat, N., Loubinoux, I., Castel-Lacanal, E., et al. (2020) Parameters Obtained with the ArmeoSpring for Upper-Limb Assessment after Stroke: A Reliability and Learning Effect Study for Guiding Parameter Use. Journal of Neuroengineering and Rehabilitation, 17, Article No. 130. https://doi.org/10.1186/s12984-020-00759-2 |
| [18] | Zimmermann, Y., Forino, A., Riener, R. and Hutter, M. (2019) ANYexo: A Versatile and Dynamic Upper-Limb Rehabilitation Robot. IEEE Robotics and Automation Letters, 4, 3649-3656. https://doi.org/10.1109/LRA.2019.2926958 |
| [19] | Perry, J.C, Rosen, J. and Burns, S. (2007) Upper-Limb Powered Exoskeleton Design. IEEE/ASME Transactions on Mechatronics, 12, 408-417. https://doi.org/10.1109/TMECH.2007.901934 |
| [20] | Sanjuan, J.D., Castillo, A.D., Padilla, M.A., et al. (2020) Cable Driven Exoskeleton for Upper-Limb Rehabilitation: A Design Review. Robotics and Autonomous Systems, 126, Article ID: 103445.
https://doi.org/10.1016/j.robot.2020.103445 |
| [21] | Chen, C.T., Lien, W.Y., Chen, C.T. and Wu, Y.C. (2020) Implementation of an Upper-Limb Exoskeleton Robot Driven by Pneumatic Muscle Actuators for Rehabilitation. Actuators, 9, Article 106. https://doi.org/10.3390/act9040106 |
| [22] | 刘冰, 李宁, 于鹏, 等. 上肢康复外骨骼机器人控制方法进展研究[J]. 电子科技大学学报, 2020, 49(5): 643-651. |
| [23] | 朱雪枫. 康复机器人上肢运动系统控制策略研究[D]: [博士学位论文]. 沈阳: 东北大学, 2017. |
| [24] | Han, J. (2009) From PID to Active Disturbance Rejection Control. IEEE Transactions on Industrial Electronics, 56, 900-906. https://doi.org/10.1109/TIE.2008.2011621 |
| [25] | Ahmed, T., Islam, M.R., Brahmi, B. and Rahman, M.H. (2022) Robustness and Tracking Performance Evaluation of PID Motion Control of 7 DOF Anthropomorphic Exoskeleton Robot Assisted Upper Limb Rehabilitation. Sensors, 22, Article 3747. https://doi.org/10.3390/s22103747 |
| [26] | Hu, B.S., Mao, B.H., Lu, S. and Yu, H.L. (2022) Design and Torque Control Base on Neural Network PID of a Variable Stiffness Joint for Rehabilitation Robot. Frontiers in Neurorobotics, 16, Article 1007324.
https://doi.org/10.3389/fnbot.2022.1007324 |
| [27] | Joyo, M.K, Raza, Y., Ahmed, S.F., et al. (2019) Optimized Proportional-Integral-Derivative Controller for Upper Limb Rehabilitation Robot. Electronics, 8, Article 826. https://doi.org/10.3390/electronics8080826 |
| [28] | Qiao, L. and Zhang, W. (2020) Trajectory Tracking Control of AUVs via Adaptive Fast Nonsingular Integral Terminal Sliding Mode Control. IEEE Transactions on Industrial Informatics, 16, 1248-1258.
https://doi.org/10.1109/TII.2019.2949007 |
| [29] | Zhang, G.W, Wang, J., Yang, P. and Guo, S.J. (2021) Iterative Learning Sliding Mode Control for Output-Constrained Upper-Limb Exoskeleton with Non-Repetitive Tasks. Applied Mathematical Modelling, 97, 366-380.
https://doi.org/10.1016/j.apm.2021.03.049 |
| [30] | Liu, Q., Liu Y., Zhu, C., et al. (2021) Design and Control of a Reconfigurable Upper Limb Rehabilitation Exoskeleton with Soft Modular Joints. IEEE Access, 9, 166815-166824. https://doi.org/10.1109/ACCESS.2021.3136242 |
| [31] | Mushage, B.O., Chedjou, J.C. and Kyamaky, A.K. (2017) Fuzzy Neural Network and Observer-Based Fault-Tolerant Adaptive Nonlinear Control of Uncertain 5-DOF Upper-Limb Exoskeleton Robot for Passive Rehabilitation. Nonlinear Dynamics, 87, 2021-2037. https://doi.org/10.1007/s11071-016-3173-7 |
| [32] | Rodríguez-Tapia, B., Soto, I., Martínez, D.M. and Arballo, N.C. (2020) Myoelectric Interfaces and Related Applications: Current State of EMG Signal Processing—A Systematic Review. IEEE Access, 8, 7792-7805.
https://doi.org/10.1109/ACCESS.2019.2963881 |
| [33] | Foroutannia, A., Akbarzadeh-T, M.R., Akbarzadeh, A. and Tahamipour-Z, S.M. (2023) Adaptive Fuzzy Impedance Control of Exoskeleton Robots with Electromyography-Based Convolutional Neural Networks for Human Intended Trajectory Estimation. Mechatronics, 91, Article ID: 102952. https://doi.org/10.1016/j.mechatronics.2023.102952 |
| [34] | 刘鹏, 葛小青, 李宇, 等. 上肢康复机器人主动康复训练控制策略[J]. 中国科学院大学学报, 2019, 36(4): 570-576. |
| [35] | 侯增广, 赵新刚, 程龙, 等. 康复机器人与智能辅助系统的研究进展[J]. 自动化学报, 2016, 42(12): 1765-1779. |
| [36] | Lotze, M., Braun, C., Birbaumer, N., Anders, S. and Cohen, L.G. (2003) Motor Learning Elicited by Voluntary Drive. Brain, 126, 866-872. https://doi.org/10.1093/brain/awg079 |
| [37] | Hogan, N. (1985) Impedance Control: An Approach to Manipulation: Part II—Implementation. Journal of Dynamic Systems, Measurement and Control, 107, 8-16. https://doi.org/10.1115/1.3140713 |
| [38] | Bai, J., Song, A.J., Wang, T. and Li, H.J. (2019) A Novel Backstepping Adaptive Impedance Control for an Upper Limb Rehabilitation Robot. Computers & Electrical Engineering, 80, Article ID: 106465.
https://doi.org/10.1016/j.compeleceng.2019.106465 |
| [39] | Wu, Q.C. and Chen, Y. (2023) Variable Admittance Time-Delay Control of an Upper Limb Rehabilitation Robot Based on Human Stiffness Estimation. Mechatronics, 90, Article ID: 102935.
https://doi.org/10.1016/j.mechatronics.2022.102935 |
| [40] | Wu, Q.S. and Chen, Y. (2020) Development of an Intention-Based Adaptive Neural Cooperative Control Strategy for Upper-Limb Robotic Rehabilitation. IEEE Robotics and Automation Letters, 6, 335-342.
https://doi.org/10.1109/LRA.2020.3043197 |
| [41] | Hu, Y., Meng, J.Y., Li, G.N., et al. (2023) Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot. Sensors, 23, Article 4042. https://doi.org/10.3390/s23084042 |
| [42] | Razzaghian, A. (2022) A Fuzzy Neural Network-Based Fractional-Order Lyapunov-Based Robust Control Strategy for Exoskeleton Robots: Application in Upper-Limb Rehabilitation. Mathematics and Computers in Simulation, 193, 567-583. https://doi.org/10.1016/j.matcom.2021.10.022 |
