A pelvic support weight rehabilitation system tracing the human center of mass height_Journal of Biomedical Engineering

Authors：

HE Bingze ,  SHI Ping , LI Xinwei , FAN Meng , DENG Zhipeng ,  YU Hongliu

Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China;

Corresponding author：

SHI Ping, Email: pshi@usst.edu.cn; YU Hongliu, Email: yhl98@hotmail.com

Keywords：

Body weight support; Center of mass height; Gated recurrent unit; Rehabilitation training

DOI：

10.7507/1001-5515.202103035

Video：

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The body weight support rehabilitation training system has now become an important treatment method for the rehabilitation of lower limb motor dysfunction. In this paper, a pelvic brace body weight support rehabilitation system is proposed, which follows the center of mass height (CoMH) of the human body. It aims to address the problems that the existing pelvic brace body weight support rehabilitation system with constant impedance provides a fixed motion trajectory for the pelvic mechanism during the rehabilitation training and that the patients have low participation in rehabilitation training. The system collectes human lower limb motion information through inertial measurement unit and predicts CoMH through artificial neural network to realize the tracking control of pelvic brace height. The proposed CoMH model was tested through rehabilitation training of hemiplegic patients. The results showed that the range of motion of the hip and knee joints on the affected side of the patient was improved by 25.0% and 31.4%, respectively, and the ratio of swing phase to support phase on the affected side was closer to that of the gait phase on the healthy side, as opposed to the traditional body weight support rehabilitation training model with fixed motion trajectory of pelvic brace. The motion trajectory of the pelvic brace in CoMH mode depends on the current state of the trainer so as to realize the walking training guided by active movement on the healthy side of hemiplegia patients. The strategy of dynamically adjustment of body weight support is more helpful to improve the efficiency of walking rehabilitation training.

Citation： HE Bingze, SHI Ping, LI Xinwei, FAN Meng, DENG Zhipeng, YU Hongliu. A pelvic support weight rehabilitation system tracing the human center of mass height. Journal of Biomedical Engineering, 2022, 39(1): 175-184. doi: 10.7507/1001-5515.202103035 Copy

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23.	Sawner K A, Lavigne J M, Brunnstrom S. Brunnstrom’s movement therapy in hemiplegia: A neurophysiological approach. Philadelphia: Lippincott Williams & Wilkins, 1992.
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27.	Chua K, Lim W S, Lim P H, et al. An exploratory clinical study on an automated, speed-sensing treadmill prototype with partial body weight support for hemiparetic gait rehabilitation in subacute and chronic stroke patients. Front Neurol, 2020, 11: 747.
28.	Hayes S C, White M, White H S F, et al. A biomechanical comparison of powered robotic exoskeleton gait with normal and slow walking: An investigation with able-bodied individuals. Clin Biomech (Bristol, Avon), 2020, 80: 105133.
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30.	Esser P, Dawes H, Collett J, et al. IMU: Inertial sensing of vertical CoM movement. J Biomech, 2009, 42(10): 1578-1581.

1. Winter D A, Patla A E, Frank J S. Assessment of balance control in humans. Med Prog Technol, 1990, 16(1-2): 31-51.
2. 马关坡, 徐秀林. 下肢康复训练减重支撑系统的研究现状. 中国医学物理学杂志, 2014, 31(1): 4694-4698.
3. Monthaporn S, Betty M N, Protas E J. Supported treadmill training for gait and balance in a patient with progressive supranuclear palsy. Phys Ther Rehabil, 2002, 82(5): 485-495.
4. Danielson A, Sunnerhagen K S. Oxygen consumption during treadmill walking with and without bodyweight support in patients with hemiparesis after stroke and in healthy subjects. Arch Phys Med Rehabil, 2000, 81(7): 953-957.
5. Trueblood P R. Partial body weight treadmill training in persons with chronic stroke. NeuroRehabilitation, 2001, 16(3): 141-153.
6. Miller E W. Body weight supported treadmill and overground training in a patient post cerebrovascular accident. NeuroRehabilitation, 2001, 16(3): 155-163.
7. Hesse S, Konrad M, Uhlenbrock D. Treadmill walking with partial body weight support venus floor walking in himiparetie subjects. Arch Phys Med Rehabil, 1999, 80(4): 421-427.
8. Visintin M, Barbeau H, Korner-Bitensky N, et al. A new approach to retrain gait in stroke patients through body weight support and treadmill stimulation. Stroke, 1998, 29(6): 1122-1128.
9. Colby S M, Kirkendall D T, Bruzga R F. Electromyographic analysis and energy expenditure of harness supported treadmill walking: implications for knee rehabilitation. Gait Posture, 1999, 10(3): 200-205.
10. MacKay-Lyons M, Makrides L, Speth S. Effect of 15% body weight support on exercise capacity of adults without impairments. Phys Ther, 2001, 81(11): 1790-1800.
11. Ma O, Diao X, Martinez L, et al. Dynamically removing partial body mass using acceleration feedback for neural training// 2007 IEEE 10th International Conference on Rehabilitation Robotics. Norway: IEEE, 2007: 1102-1107.
12. 方彬, 沈林勇, 章亚男, 等. 步行训练机器人主动减重控制方法. 上海大学学报(自然科学版), 2011, 17(6): 719-723.
13. Mirzaee A, Moghadam M M, Saba A M. Conceptual design of an active body weight supports ystem using a linear series elastic actuator// 2019 7th International Conference on Robotics and Mechatronics (ICRoM 2019). Tehran: IEEE, 2019: 80-85.
14. Pacer Gait Trainers[EB/OL]. (2016-03) [2021-05-10]. https://www.rifton.com/resources/webinars/2016/dynamic-pacer.
15. 朱文超, 徐姚, 马张. 压差式气动减重康复步行训练系统的设计. 生物医学工程学杂志, 2017, 34(4): 565-571.
16. Morbi A, Ahmadi M, Nativ A. GaitEnable: An omnidirectional robotic system for gait rehabilitation// IEEE International Conference on Mechatronics and Automation (ICMA 2012). Chengdu: IEEE, 2012: 936-941.
17. Mun K-R, Lim S B, Guo Z, et al. Biomechanical effects of body weight support with a novel robotic walker for over-ground gait rehabilitation. Med Biol Eng Comput, 2017, 55(2): 315-326.
18. Patton J, Brown D A, Peshkin M, et al. KineAssist: Design and development of a robotic overground gait and balance therapy device. Top Stroke Rehabil, 2008, 15(2): 131-139.
19. Gordon K E, Svendsen B, Harkema S, et al. Closed-loop force controlled body weight support system: CA2464128. 2011-09-20.
20. Frey M, Colomabo G, Vaglio M, et al. A novel mechatronic body weight support system. IEEE Trans Neural Syst Rehabil Eng, 2006, 14(3): 311-321.
21. Cho K, Van Merrienboer B, Bahdanau D, et al. On the properties of neural machine translation: Encoder-decoder approaches. arXiv preprint arXiv, 2014: 1409.1259.
22. Liang C, Li H, Lei M, et al. Dongting Lake water level forecast and its relationship with the Three Gorges Dam based on a Long Short-Term Memory network. Water, 2018, 10(10): 1389.
23. Sawner K A, Lavigne J M, Brunnstrom S. Brunnstrom’s movement therapy in hemiplegia: A neurophysiological approach. Philadelphia: Lippincott Williams & Wilkins, 1992.
24. Karaharju-Huisnan T, Taylor S, Begg R, et al. Gait symmetry quantification during treadmill walking// The Seventh Australian and New Zealand Intelligent Information Systems Conference. Perth: IEEE, 2001: 203-206.
25. Page S, Wilson R, Chae J. A randomized controlled trial comparing EMG-triggered, cyclic, and sensory electrical stimulation. Arch Phys Med Rehabil, 2016, 30(10): 978-987.
26. 明东, 蒋晟龙, 王忠鹏, 等. 基于人机信息交互的助行外骨骼机器人技术进展. 自动化学报, 2017, 43(7): 1089-1100.
27. Chua K, Lim W S, Lim P H, et al. An exploratory clinical study on an automated, speed-sensing treadmill prototype with partial body weight support for hemiparetic gait rehabilitation in subacute and chronic stroke patients. Front Neurol, 2020, 11: 747.
28. Hayes S C, White M, White H S F, et al. A biomechanical comparison of powered robotic exoskeleton gait with normal and slow walking: An investigation with able-bodied individuals. Clin Biomech (Bristol, Avon), 2020, 80: 105133.
29. Hwang J, Shin Y, Park J H, et al. Effects of walkbot gait training on kinematics, kinetics, and clinical gait function in paraplegia and quadriplegia. NeuroRehabilitation, 2018, 42(4): 481-489.
30. Esser P, Dawes H, Collett J, et al. IMU: Inertial sensing of vertical CoM movement. J Biomech, 2009, 42(10): 1578-1581.

Journal of Biomedical Engineering

A pelvic support weight rehabilitation system tracing the human center of mass height

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