Wang Sentong, Hase Kazunori, Funato Tetsuro
Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan.
Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan.
Front Bioeng Biotechnol. 2023 Jul 18;11:1130219. doi: 10.3389/fbioe.2023.1130219. eCollection 2023.
Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.
先前的研究表明，中枢神经系统以模块模式激活肌肉，以降低在产生运动时控制每块肌肉所需的复杂性，这被称为肌肉协同作用。在以往基于肌肉骨骼模型的肌肉协同作用分析研究中，由于关节简化，传统的刚体连杆肌肉骨骼模型未能体现肌肉激活与关节运动学之间的生理相互作用。然而，肌肉水平与关节水平之间存在的相互作用是影响肌肉骨骼系统生物力学和神经生理学的重要关系。在本研究中，使用了一种耦合详细关节表示（包括复杂接触行为和材料表示）的下肢肌肉骨骼模型，采用非负矩阵分解（NMF）分解方法进行肌肉协同作用分析。肌肉骨骼系统中关节表示的复杂性有助于研究肌肉骨骼系统上的生理相互作用，从而促进肌肉协同作用的分解。结果表明，步态站立期下肢20块肌肉的活动可由三种肌肉协同作用控制，协同作用占总方差的86.42%。肌肉协同作用和肌肉骨骼生物力学的特征与结果一致，从而通过肌肉协同作用和中枢神经系统降低控制问题的维度来解释步态期间下肢运动的形成机制。
