LLMKA: A Matlab-based toolbox for musculoskeletal kinematics analysis of lower limbs_Chinese Journal of Reparative and Reconstructive Surgery

Authors：

LI Shiqi ¹ , NIE Yong ² , WANG Junqing ³ ,  LI Kang ³ ,  SHEN Bin ²

1. College of Electrical Engineering, Sichuan University, Chengdu Sichuan, 610041, P. R. China;
2. Orthopedic Research Institute, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu Sichuan, 610041, P. R. China;
3. West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu Sichuan, 610041, P. R. China;

Corresponding author：

LI Kang, Email: likang@wchscu.cn; SHEN Bin, Email: shenbin_1971@163.com

Keywords：

OpenSim; LLMKA toolbox; musculoskeletal kinematics analysis; consistency; efficiency improvement

DOI：

10.7507/1002-1892.202202033

Video：

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Objective To develop a Matlab toolbox to improve the efficiency of musculoskeletal kinematics analysis while ensuring the consistency of musculoskeletal kinematics analysis process and results. Methods Adopted the design concept of “Batch processing tedious operation”, based on the Matlab connection OpenSim interface function ensures the consistency of musculoskeletal kinematics analysis process and results, the functional programming was applied to package the five steps for scale, inverse kinematics analysis, residual reduction algorithm, static optimization analysis, and joint reaction analysis of musculoskeletal kinematics analysis as functional functions, and command programming was applied to analyze musculoskeletal movements in large numbers of patients. A toolbox called LLMKA (Lower Limbs Musculoskeletal Kinematics Analysis) was developed. Taking 120 patients with medial knee osteoarthritis as the research object, a clinical researcher was selected using the LLMKA toolbox and OpenSim to test whether the analysis process and results were consistent between the two methods. The researcher used the LLMKA toolbox again to conduct musculoskeletal kinematics analysis in 120 patients to verify whether the use of this toolbox could improve the efficiency of musculoskeletal kinematics analysis compared with using OpenSim. Results Using the LLMKA toolbox could analyze musculoskeletal kinematics analysis in a large number of patients, and the analysis process and results were consistent with the use of OpenSim. Compared to using OpenSim, musculoskeletal kinematics analysis was completed in 120 patients using the LLMKA toolbox with only 2 operations were needed to enter the patient body mass data, operating steps decreased by 99.19%, total analysis time by 66.84%, and manual participation time by 99.72%, just need 0.079 1 hour (4 minutes and 45 seconds). Conclusion The LLMKA toolbox can complete a large number of musculoskeletal kinematics analysis in patients with one click in a way that is consistent in process and results with using OpenSim, reducing the total time of musculoskeletal kinematics analysis, and liberating clinical researchers from cumbersome steps, making more energy into the clinical significance of musculoskeletal kinematics analysis results.

Citation： LI Shiqi, NIE Yong, WANG Junqing, LI Kang, SHEN Bin. LLMKA: A Matlab-based toolbox for musculoskeletal kinematics analysis of lower limbs. Chinese Journal of Reparative and Reconstructive Surgery, 2022, 36(5): 525-533. doi: 10.7507/1002-1892.202202033 Copy

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22.	王学瑞. 函数式编程语言发展及应用. 计算机光盘软件与应用, 2012, 15(23): 181-182.
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24.	Bunce C. Correlation, agreement, and Bland-Altman analysis: statistical analysis of method comparison studies. Am J Ophthalmol, 2009, 148(1): 4-6.
25.	Mansouri M, Reinbolt JA. A platform for dynamic simulation and control of movement based on OpenSim and MATLAB. J Biomech, 2012, 45(8): 1517-1521.

1. Loeb GE, Davoodi R. Musculoskeletal mechanics and modeling. Scholarpedia, 2016, 11(11): 12389. doi:10.4249/scholarpedia.12389.
2. Saxby DJ, Modenese L, Bryant AL, et al. Tibiofemoral contact forces during walking, running and sidestepping. Gait Posture, 2016, 49: 78-85.
3. 游永豪, 卢桂兵, 邵梦霓, 等. 双膝骨关节炎对女性老年人踝关节策略动态平衡能力的影响. 医用生物力学, 2021, 36(3): 459-464.
4. 朱正飞, 王玲, 李涤尘, 等. 膝骨性关节炎合并内翻畸形患者运动特征研究. 生物医学工程学杂志, 2018, 35(1): 38-44.
5. 杜刚, 李政甜, 劳山, 等. 机器人辅助膝关节单髁置换术对坐起动作时膝关节生物力学的影响. 中国修复重建外科杂志, 2021, 35(10): 1259-1264.
6. 宋和胜, 钱竞光, 唐潇. 基于软件OpenSim的人体运动建模理论及其应用领域概述. 医用生物力学, 2015, 30(4): 373-379.
7. 罗林聪, 马立敏, 林泽, 等. 基于AnyBody骨骼肌肉多体动力学分析的有限元仿真. 医用生物力学, 2019, 34(3): 237-242, 250.
8. 穆雪莲, 周兴龙. OpenSim工作原理及其应用概述. 第十九届全国运动生物力学学术交流大会, 2017.
9. 郭超, 何育民, 孙朝阳, 等. OpenSim环境下人体下肢行走生物力学特性研究. 机械科学与技术, 2021, 40(9): 1355-1360.
10. Yu J, Zhang S, Wang A, et al. Human gait analysis based on OpenSim. 2020 International Conference on Advanced Mechatronic Systems (ICAMechS), 2020: 278-281.
11. Seth A, Sherman M, Reinbolt JA, et al. OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange. Procedia IUTAM, 2011, 2: 212-232.
12. Barre A, Armand S. Biomechanical ToolKit: Open-source framework to visualize and process biomechanical data. Comput Methods Programs Biomed, 2014, 114(1): 80-87.
13. Mantoan A, Pizzolato C, Sartori M, et al. MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation. Source Code Biol Med, 2015, 10: 12. doi: 10.1186/s13029-015-0044-4.
14. Sun K, Wang H, Bai Y, et al. MRIES: A Matlab toolbox for mapping the responses to intracranial electrical stimulation. Front Neurosci, 2021, 15: 652841. doi: 10.3389/fnins.2021.652841.
15. Deng QY, Chen X. An image processing toolbox based on MATLAB GUI. J Phys Conf Ser, 2021. doi:10.1088/1742-6596/2010/1/012137.
16. Muller A, Pontonnier C, Puchaud P, et al. CusToM: a Matlab toolbox for musculoskeletal simulation. Journal of Open Source Software, 2019, 4(33): 927. doi: 10.21105/joss.00927.
17. Shourijeh MS, Smale KB, Potvin BM, et al. A forward-muscular inverse-skeletal dynamics framework for human musculoskeletal simulations. J Biomech, 2016, 49(9): 1718-1723.
18. Bedo BLS, Mantoan A, Catelli DS, et al. BOPS: a Matlab toolbox to batch musculoskeletal data processing for OpenSim. Comput Methods Biomech Biomed Engin, 2021, 24(10): 1104-1114.
19. Lee LF, Umberger BR. Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. PeerJ, 2016, 4: e1638. doi: 10.7717/peerj.1638.
20. 王雨昕. 基于OpenSim/MATLAB的膝关节康复训练控制研究. 哈尔滨: 哈尔滨工程大学, 2019.
21. 孙利鑫, 陈骐, 郝卫亚. 两种不同肌肉力求解算法的对比分析. 医用生物力学, 2022. http://kns.cnki.net/kcms/detail/31.1624.R.20210924.2149.005.html.
22. 王学瑞. 函数式编程语言发展及应用. 计算机光盘软件与应用, 2012, 15(23): 181-182.
23. Doğan NÖ. Bland-Altman analysis: A paradigm to understand correlation and agreement. Turk J Emerg Med, 2018, 18(4): 139-141.
24. Bunce C. Correlation, agreement, and Bland-Altman analysis: statistical analysis of method comparison studies. Am J Ophthalmol, 2009, 148(1): 4-6.
25. Mansouri M, Reinbolt JA. A platform for dynamic simulation and control of movement based on OpenSim and MATLAB. J Biomech, 2012, 45(8): 1517-1521.

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