Study on gait symmetry based on simulation and evaluation system of prosthesis gait_Journal of Biomedical Engineering

Authors：

YU Beibei ^1,2,3 , YU Hongliu ^1,3 ,  MENG Qingyun ^2,3 , MENG Qiaoling ^1,3 , CAO Wujing ^1,3

1. Institute of Biomechanics and Rehabilitation Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P.R.China;
2. Shanghai University of Medicine & Health Science, Shanghai 201318, P.R.China;
3. Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, P.R.China;

Corresponding author：

MENG Qingyun, Email: mengqy1996@126.com

Keywords：

intelligent knee joint; artificial limbs; gait simulation and evaluation; symmetry; the machine test

DOI：

10.7507/1001-5515.201811038

Video：

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Abstract Full text Figures/Tables Video References Cited by

A software and hardware platform for gait simulation and system evaluation for lower limb intelligent prosthesis is proposed and designed, in order that the wearable symmetry effect of the intelligent knee prosthesis can be quantitatively analyzed by machine test instead of human wear test. The whole-body three-dimensional gait and motion analysis system instrument, a device to collect gait data such as joint angle and stride of adults, was used for extracting simulated gait characteristic curve. Then, the gait curve was fitted based on the corresponding joint to verify the feasibility of the test platform in the experiment. Finally, the developed artificial knee prosthesis was worn on the prosthetic evaluation system to quantitatively analyze the gait symmetry effect. The results showed that there was no significant difference in gait symmetry between the developed knee joints at different speeds, which could reach more than 88%. The simulation and evaluation of the prosthetic gait have good effects on the functional simulation and evaluation of the lower limb intelligent prosthesis.

Citation： YU Beibei, YU Hongliu, MENG Qingyun, MENG Qiaoling, CAO Wujing. Study on gait symmetry based on simulation and evaluation system of prosthesis gait. Journal of Biomedical Engineering, 2019, 36(6): 924-929. doi: 10.7507/1001-5515.201811038 Copy

1.	Ko C Y, Kim S B, Kim J K, et al. Biomechanical features of level walking by transtibial amputees wearing prosthetic feet with and without adaptive ankles. J Mech Sci Technol, 2016, 30(6): 2907-2914.
2.	Raschke S U, Orendurff M S, Mattie J L, et al. Biomechanical characteristics, patient preference and activity level with different prosthetic feet: A randomized double blind trial with laboratory and community testing. J Biomech, 2015, 48(1): 146-152.
3.	Arifin N, Abu Osman N A, Ali S, et al. Evaluation of postural steadiness in below-knee amputees when wearing different prosthetic feet during various sensory conditions using the Biodex^® Stability System. Proc Inst Mech Eng H, 2015, 229(7): 491-498.
4.	Graham L E, Datta D, Heller B, et al. A comparative study of conventional and energy-storing prosthetic feet in high-functioning transfemoral amputees. Arch Phys Med Rehabil, 2007, 88(6): 801-806.
5.	Johansson J L, Sherrill D M, Riley P O, et al. A clinical comparison of variable-damping and mechanically passive prosthetic knee devices. Am J Phys Med Rehabil, 2005, 84(8): 563-575.
6.	Yilmaz A, Orhanli T. A test platform design for testing knee prostheses// 2014 18th National Biomedical Engineering Meeting. Istanbul: IEEE, 2014: 1-4.
7.	Maqbool H F, Husman M A, Awad M I, et al. A real-time gait event detection for lower limb prosthesis control and evaluation. IEEE Trans Neural Syst Rehabil Eng, 2017, 25(9): 1500-1509.
8.	Yunardi R T, Firdaus A A, Agustin E I. Implementation of motion capture system for trajectory planning of leg swing simulator// 2017 International Seminar on Sensors, Instrumentation, Measurement and Metrology. Surabaya: IEEE, 2017: 11-16.
9.	焦伟. 假肢膝关节测试平台模糊PID控制系统研究. 南京: 东南大学, 2015.
10.	Richter H, Simon D, Smith W A, et al. Dynamic modeling, parameter estimation and control of a leg prosthesis test robot. Appl Math Model, 2015, 39(2): 559-573.
11.	Prakash C, Mishra U, Jain M, et al. Automated kinematic analysis using holistic based human gait motion for biomedical applications// 2018 8th International Conference on Cloud Computing, Data Science & Engineering. Noida: IEEE, 2018: 700-706.
12.	Sun Ningping, Sakai Y. New approaches to human gait simulation using motion sensors// 2017 31st IEEE International Conference on Advanced Information Networking and Applications Workshops. Taipei: IEEE, 2017: 126-131.
13.	Park S E, Ho Y J, Moon Y, et al. Analysis of gait pattern during stair walk for improvement of gait training robot// 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Seogwipo: IEEE, 2017: 1905-1908.
14.	Babaee M, Li Linwei, Rigoll G. Gait recognition from incomplete gait cycle// The 25th IEEE International Conference on Image Processing (ICIP). Athens: IEEE, 2018: 768-772.
15.	Wang Fei, Kim K, Wen Shiguang, et al. Study of gait symmetry quantification and its application to intelligent prosthetic leg development// 2011 IEEE International Conference on Robotics and Biomimetics. Karon Beach: IEEE, 2011: 1361-1366.
16.	曹武警, 魏小东, 赵伟亮, 等. 基于生理步态的智能膝关节结构设计及训练方法研究. 生物医学工程学杂志, 2018, 35(5): 75-81.

1. Ko C Y, Kim S B, Kim J K, et al. Biomechanical features of level walking by transtibial amputees wearing prosthetic feet with and without adaptive ankles. J Mech Sci Technol, 2016, 30(6): 2907-2914.
2. Raschke S U, Orendurff M S, Mattie J L, et al. Biomechanical characteristics, patient preference and activity level with different prosthetic feet: A randomized double blind trial with laboratory and community testing. J Biomech, 2015, 48(1): 146-152.
3. Arifin N, Abu Osman N A, Ali S, et al. Evaluation of postural steadiness in below-knee amputees when wearing different prosthetic feet during various sensory conditions using the Biodex^® Stability System. Proc Inst Mech Eng H, 2015, 229(7): 491-498.
4. Graham L E, Datta D, Heller B, et al. A comparative study of conventional and energy-storing prosthetic feet in high-functioning transfemoral amputees. Arch Phys Med Rehabil, 2007, 88(6): 801-806.
5. Johansson J L, Sherrill D M, Riley P O, et al. A clinical comparison of variable-damping and mechanically passive prosthetic knee devices. Am J Phys Med Rehabil, 2005, 84(8): 563-575.
6. Yilmaz A, Orhanli T. A test platform design for testing knee prostheses// 2014 18th National Biomedical Engineering Meeting. Istanbul: IEEE, 2014: 1-4.
7. Maqbool H F, Husman M A, Awad M I, et al. A real-time gait event detection for lower limb prosthesis control and evaluation. IEEE Trans Neural Syst Rehabil Eng, 2017, 25(9): 1500-1509.
8. Yunardi R T, Firdaus A A, Agustin E I. Implementation of motion capture system for trajectory planning of leg swing simulator// 2017 International Seminar on Sensors, Instrumentation, Measurement and Metrology. Surabaya: IEEE, 2017: 11-16.
9. 焦伟. 假肢膝关节测试平台模糊PID控制系统研究. 南京: 东南大学, 2015.
10. Richter H, Simon D, Smith W A, et al. Dynamic modeling, parameter estimation and control of a leg prosthesis test robot. Appl Math Model, 2015, 39(2): 559-573.
11. Prakash C, Mishra U, Jain M, et al. Automated kinematic analysis using holistic based human gait motion for biomedical applications// 2018 8th International Conference on Cloud Computing, Data Science & Engineering. Noida: IEEE, 2018: 700-706.
12. Sun Ningping, Sakai Y. New approaches to human gait simulation using motion sensors// 2017 31st IEEE International Conference on Advanced Information Networking and Applications Workshops. Taipei: IEEE, 2017: 126-131.
13. Park S E, Ho Y J, Moon Y, et al. Analysis of gait pattern during stair walk for improvement of gait training robot// 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Seogwipo: IEEE, 2017: 1905-1908.
14. Babaee M, Li Linwei, Rigoll G. Gait recognition from incomplete gait cycle// The 25th IEEE International Conference on Image Processing (ICIP). Athens: IEEE, 2018: 768-772.
15. Wang Fei, Kim K, Wen Shiguang, et al. Study of gait symmetry quantification and its application to intelligent prosthetic leg development// 2011 IEEE International Conference on Robotics and Biomimetics. Karon Beach: IEEE, 2011: 1361-1366.
16. 曹武警, 魏小东, 赵伟亮, 等. 基于生理步态的智能膝关节结构设计及训练方法研究. 生物医学工程学杂志, 2018, 35(5): 75-81.

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Study on gait symmetry based on simulation and evaluation system of prosthesis gait

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