Li Shiqi, Nie Yong, Wang Junqing, Li Kang, Shen Bin
College of Electrical Engineering, Sichuan University, Chengdu Sichuan, 610041, P. R. China.
Orthopedic Research Institute, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu Sichuan, 610041, P. R. China.
Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi. 2022 May 15;36(5):525-533. doi: 10.7507/1002-1892.202202033.
To develop a Matlab toolbox to improve the efficiency of musculoskeletal kinematics analysis while ensuring the consistency of musculoskeletal kinematics analysis process and results.
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.
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).
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.
开发一个Matlab工具箱，以提高肌肉骨骼运动学分析的效率，同时确保肌肉骨骼运动学分析过程和结果的一致性。
采用“批量处理繁琐操作”的设计理念，基于Matlab连接OpenSim接口函数确保肌肉骨骼运动学分析过程和结果的一致性，应用函数式编程将肌肉骨骼运动学分析的缩放、逆运动学分析、残差减少算法、静态优化分析和关节反应分析这五个步骤打包为功能函数，并应用命令式编程对大量患者的肌肉骨骼运动进行分析。开发了一个名为LLMKA（下肢肌肉骨骼运动学分析）的工具箱。以120例膝内侧骨关节炎患者为研究对象，选取一名临床研究人员使用LLMKA工具箱和OpenSim测试两种方法的分析过程和结果是否一致。该研究人员再次使用LLMKA工具箱对120例患者进行肌肉骨骼运动学分析，以验证使用该工具箱与使用OpenSim相比是否能提高肌肉骨骼运动学分析的效率。
使用LLMKA工具箱能够对大量患者进行肌肉骨骼运动学分析，且分析过程和结果与使用OpenSim一致。与使用OpenSim相比，使用LLMKA工具箱对120例患者进行肌肉骨骼运动学分析时，仅需2次操作输入患者体重数据，操作步骤减少了99.19%，总分析时间减少了66.84%，人工参与时间减少了99.72%，仅需0.079 1小时（4分45秒）。
LLMKA工具箱能够以与使用OpenSim过程和结果一致的方式一键完成大量患者的肌肉骨骼运动学分析，减少了肌肉骨骼运动学分析的总时间，将临床研究人员从繁琐步骤中解放出来，使其能更多精力投入到肌肉骨骼运动学分析结果的临床意义中。
