王 森彤

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 in vivo 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 in vivo 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.

The biomechanical variation in the knee during walking that accompanies medial meniscal radial tears stemming from knee osteoarthritis (OA) has not been explored. This study introduced a finite element musculoskeletal model using concurrent lower limb musculoskeletal dynamics and knee joint finite element analysis in a single framework and expanded the models to include knees with medial meniscal radial tears and total medial meniscectomy. The radial tears involved three locations: anterior horn, midbody, and posterior horn with grades of 33%, 50%, and 83% of the meniscus width. The shear and hoop stresses of the tear meniscus and tibial cartilage contact load, accompanying tears, and postmeniscectomy were evaluated during the stance phase of the gait cycle using the models. In the 83% width midbody tear group, shear stress at the end of the tear was significantly greater than in the intact meniscus and other tear groups, and the maximum shear stress was increased by 310% compared to the intact meniscus. A medial meniscus radial tear has a much smaller effect on the tibial cartilage load (even though in the 83% width tear, the cartilage/total load ratio increased by only 9%). However, the contact force on the tibial cartilage with total postmeniscectomy was increased by 178.93% compared with a healthy intact meniscus, and the peak contact pressure after meniscectomy increased from 11.94 to 12.45 MPa to 17.64 and 13.76 MPa, at the maximum weight acceptance and push-off, respectively. Our study shows that radial tears with larger medial meniscus widths are prone to high stress concentrations at the end of the tears, leading to the potential risk of complete meniscal rupture. Furthermore, although the tears did not change the cartilage load distribution, they disrupted the circumferential stress-transmitting function of the meniscus, thus greatly increasing the likelihood of the onset of knee OA. The significant increase in the tibial cartilage load with total postmeniscectomy indicates a potential risk of OA flare-ups. This study contributes to a better understanding of meniscal tear-induced OA biomechanical changes during human activities and offers some potential directions for surgical guidance of meniscectomies and the prophylaxis and treatment of OA.

Finite element musculoskeletal (FEMS) approaches using concurrent musculoskeletal (MS) and finite element (FE) models driven by motion data such as marker-based motion trajectory can provide insight into the interactions between the knee joint secondary kinematics, contact mechanics, and muscle forces in subject-specific biomechanical investigations. However, these data-driven FEMS systems have two major disadvantages that make them challenging to apply in clinical environments: they are computationally expensive and they require expensive and inconvenient equipment for data acquisition. In this study, we developed an FEMS model of the lower limb, driven solely by inertial measurement unit (IMU) sensors, that includes the tissue geometries of the intact knee joint and combines muscle modeling and elastic foundation (EF) theory-based contact analysis of a knee into a single framework. The model requires only the angular velocities and accelerations measured by the sensors as input, and the target outputs (knee contact mechanics, secondary kinematics, and muscle forces) are predicted from the convergence results of iterative calculations of muscle force optimization and knee contact mechanics. To evaluate its accuracy, the model was compared with in vivo experimental data during gait. The maximum contact pressure (12.6 MPa) in the rigid body contact analysis occurred on the medial side of the cartilage at the maximum loading response. The proposed computationally efficient framework drastically reduced the computational time (97.5% reduction) in comparison with the conventional deformable FE analysis. The developed framework combines measurement convenience and computational efficiency and shows promise for clinical applications aimed at understanding subject-specific interactions between the knee joint secondary kinematics, contact mechanics, and muscle forces.