The design of weight-loss walking rehabilitation training system of differential-pressure style_Journal of Biomedical Engineering

Authors：

ZHU Wenchao ,  XU Xiulin , YAO Xiaoming , MA Guanpo , ZHANG Dongheng

School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 20093, P.R.China;

Corresponding author：

XU Xiulin, Email: xxlin100@163.com

Keywords：

lower limb weight loss; rehabilitation training; walking training; differential air pressure

DOI：

10.7507/1001-5515.201512043

Video：

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This research is to develop a weight-loss walking rehabilitation training system based on differential air pressure. The system adopted Proportion-Integral-Derivative (PID) algorithm to improve the precision of weight loss, taking MSP430F149 microprocessor of Texas Instruments as the core of pressure control system. The training software is designed based on Microsoft Visual C++ 6.0 of Microsoft. The system can provide comfortable training environment for patients with lower limb motor function impediment, and can collect electromyographic signals from patients, so as to further the scientific and normative management of the patient's information. Based on this training system, the initial bearing weight, bearing weight after maximum weight loss, and maximum weight loss percentage of 10 normal adults’ lower limbs were collected. It was found that the intraclass correlation coefficient (ICC) values were all greater than 0.6. The training system has a good reliability, which can provide scientific data for clinical weight-loss lower limb rehabilitation training.

Citation： ZHU Wenchao, XU Xiulin, YAO Xiaoming, MA Guanpo, ZHANG Dongheng. The design of weight-loss walking rehabilitation training system of differential-pressure style. Journal of Biomedical Engineering, 2017, 34(4): 565-571. doi: 10.7507/1001-5515.201512043 Copy

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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. Suberamanian S K., Lourenco C B, Sveistrup H, et al. Arm motor rehabilitation in chronic stroke: Effects of two training environments. 2011 International Conference on Virtual Rehabilitation, 2011, 6: 1-2.
3. Hyunchul K, Miller L M, Fedulow I, et al. Effectiveness of executive functions training within a virtual supermarket for adults with traumatic brain injury: A pilot study. Neural Systems and Rehabilitation Engineering, 2013, 21(2): 182-190.
4. 毕胜, 季林红, 纪树荣. 机器人辅助神经康复训练的研究进展. 中国康复医学杂志, 2004, 19(12): 931-932.
5. 夏斌, 刘和玉. 脑卒中偏瘫患者重复性训练肢体功能改善的疗效观察//世界中联第三届中西医结合老年医学学术大会, 2010, 8: 282-284.
6. 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, 2011, 17(6): 719-723.
7. Hornby T G, Zemon D H, Campbell D. Robotic-assisted, body-weight-supported treadmill training in individuals following motor incomplete spinal cord injury. Phys Ther, 2005, 85(1): 52-66.
8. Colombo G, Wirz M, Dietz V. Driven gait orthosis for improvement of locomotor training in paraplegic patients. Spinal Cord, 2001, 39(5): 252-255.
9. 林健强, 孙晓敏, 龚艳菲, 等. 减重步行训练对脑卒中偏瘫患者下肢功能的影响. 全军中医药骨伤学术会议, 2009, 9: 211-214.
10. 胡聪英. 可穿戴气动减重步行助力机器人的研究. 大连: 大连理工大学, 2012.
11. 徐秀林, 邹任玲, 胡秀枋, 等. 一种用于偏瘫患者的减重多态康复评定系统的设计. 中国生物医学工程学报, 2010, 29(6): 883-888.
12. Azevedo L B, Lambert M I, Zogaib P S, et al. Maximal and submaximal physiological responses to adaptation to deep water running. J Sports Sci, 2010, 28(4): 407-414.
13. 余洪俊. 表面肌电图评价肌肉的功能状况. 中国临床康复, 2002, 6(23): 3514-3515.
14. 扬坚, 张颖. 表面肌电图在神经肌肉病损功能评估中的应用. 中国临床康复, 2004, 8(22): 4580-4581.
15. 2010国民体质公报. http://www.gov.cn/test/2012-04/19/content_ 2117320.htm.
16. 涂川川. 基于 BP 神经网络 PID 控制的温室环境控制系统的仿真研究. 长春: 吉林农业大学, 2012.
17. 郭旭东, 徐秀林, 张东衡. 基于肌电特征提取的智能电刺激仪. 生物医学工程学杂志, 2011, 28(2): 260-263.

Journal of Biomedical Engineering

The design of weight-loss walking rehabilitation training system of differential-pressure style

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