Yang Yangyang, Wang Yufan, Zheng Nan, Cheng Rongshan, Zou Diyang, Zhao Jie, Tsai Tsung-Yuan
School of Biomedical Engineering & Med-X Research Institute, Shanghai Jiao Tong University, Shanghai 200230, China.
Department of Orthopedics, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China.
Bioengineering (Basel). 2023 Aug 25;10(9):1006. doi: 10.3390/bioengineering10091006.
In vitro biomechanical experiments utilizing cadaveric specimens are one of the most effective methods for rehearsing surgical procedures, testing implants, and guiding postoperative rehabilitation. Applying dynamic physiological muscle force to the specimens is a challenge to reconstructing the environment of bionic mechanics in vivo, which is often ignored in the in vitro experiment. The current work aims to establish a hardware platform and numerical computation methods to reproduce dynamic muscle forces that can be applied to mechanical testing on in vitro specimens. Dynamic muscle loading is simulated through numerical computation, and the inputs of the platform will be derived. Then, the accuracy and robustness of the platform will be evaluated through actual muscle loading tests in vitro. The tests were run on three muscles (gastrocnemius lateralis, the rectus femoris, and the semitendinosus) around the knee joint and the results showed that the platform can accurately reproduce the magnitude of muscle strength (errors range from -6.2% to 1.81%) and changing pattern (goodness-of-fit range coefficient ranges from 0.00 to 0.06) of target muscle forces. The robustness of the platform is mainly manifested in that the platform can still accurately reproduce muscle force after changing the hardware combination. Additionally, the standard deviation of repeated test results is very small (standard ranges of hardware combination 1: 0.34 N2.79 N vs. hardware combination 2: 0.68 N2.93 N). Thus, the platform can stably and accurately reproduce muscle forces in vitro, and it has great potential to be applied in the future musculoskeletal loading system.
利用尸体标本进行的体外生物力学实验是演练手术程序、测试植入物和指导术后康复的最有效方法之一。向标本施加动态生理肌肉力是重建体内仿生力学环境的一项挑战，而这在体外实验中常常被忽视。当前的工作旨在建立一个硬件平台和数值计算方法，以再现可应用于体外标本力学测试的动态肌肉力。通过数值计算模拟动态肌肉负荷，并得出平台的输入参数。然后，通过体外实际肌肉负荷测试评估平台的准确性和鲁棒性。在膝关节周围的三块肌肉（外侧腓肠肌、股直肌和半腱肌）上进行了测试，结果表明该平台能够准确再现目标肌肉力的大小（误差范围为-6.2%至1.81%）和变化模式（拟合优度范围系数范围为0.00至0.06）。该平台的鲁棒性主要体现在改变硬件组合后仍能准确再现肌肉力。此外，重复测试结果的标准差非常小（硬件组合1的标准差范围：0.34 N2.79 N，硬件组合2的标准差范围：0.68 N2.93 N）。因此，该平台能够在体外稳定且准确地再现肌肉力，并且在未来的肌肉骨骼负荷系统中具有巨大的应用潜力。
