Ma'touq Jumana, Hu Tingli, Haddadin Sami
a Institute of Automatic Control, Gottfried Wilhelm Leibniz Universität Hannover , Hannover , Germany.
b Munich School of Robotics and Machine Intelligence , Technical University of Munich , Munich , Germany.
Comput Methods Biomech Biomed Engin. 2019 May;22(7):727-739. doi: 10.1080/10255842.2019.1588256. Epub 2019 Mar 18.
Neuromusculoskeletal models provide a mathematical tool for understanding and simulating human motor control and neuromechanics. In this work, we propose a combined computational model for the musculotendon paths and muscle-joint kinematics for the human hand, including all extrinsic and intrinsic muscles. This model is implemented based on the anatomical descriptions and a human hand dissection study. The model takes joint angles as input and estimates the musculotendon lengths, length change rates, and excursion moment arms. The proposed model is simulated to generate according moment arms, which are compared with cadaver measurements available from literature in terms of similarity coefficient s. For most muscles compared, high similarity with for 92% of cases is achieved between the modeled and the measured moment arms. These results suggest the correctness of modeled moment arms and imply the feasibility of modeled musculotendon paths, lengths, and length change rates.
神经肌肉骨骼模型为理解和模拟人类运动控制及神经力学提供了一种数学工具。在这项工作中，我们提出了一种针对人类手部肌肉肌腱路径和肌肉 - 关节运动学的组合计算模型，包括所有外在肌和内在肌。该模型是基于解剖学描述和一项人类手部解剖研究实现的。该模型以关节角度作为输入，并估计肌肉肌腱长度、长度变化率和偏移力臂。对所提出的模型进行模拟以生成相应的力臂，并根据相似系数s将其与文献中可用的尸体测量值进行比较。对于大多数比较的肌肉，在建模力臂和测量力臂之间，92%的情况实现了高度相似。这些结果表明建模力臂的正确性，并暗示了建模的肌肉肌腱路径、长度和长度变化率的可行性。
