The pathogenesis of musculoskeletal disorders is closely associated with the cumulative damage and fatigue failure behavior of fibrous connective tissues under long-term repetitive loading. However, significant technological challenges remain in real-time dynamic monitoring of ligament fatigue life, particularly the lack of efficient computational mechanics modeling frameworks and precise assessment tools adaptable to real-world movement scenarios. The multimodal integrated framework for ligament fatigue life assessment was proposed in this study. First, the high-accuracy subject-specific musculoskeletal models were developed based on individualized medical imaging data. A coupled hyperelastic-viscoelastic constitutive model was incorporated to accurately characterize the nonlinear mechanical behavior of ligamentous tissues and their fatigue damage evolution under cyclic loading. Furthermore, by integrating continuum damage mechanics theory, a time-dependent cumulative damage evolution equation was established to systematically quantify the coupling relationship between fatigue failure probability and dynamic mechanical loading. In the data-driven prediction module, an innovative deep-learning model that integrates kinematic-dynamic coupling was developed. By integrating wearable inertial measurement units, the model enables real-time inversion of ligament loading force-fatigue failure states and prediction of fatigue life. This approach effectively overcomes the limitations of traditional mechanical modeling in long-term, multi-scenario dynamic monitoring, achieving high-precision and minimally invasive fatigue life evaluation of ligaments. The proposed computational framework breaks the static-loading constraints of conventional fatigue testing, achieving the dynamic biomechanical analysis and fatigue life prediction under real movement conditions. This work not only provides novel theoretical insights into the mechanisms and modeling of ligament fatigue damage, but also provides a generalizable tool for biomechanical injury prevention, rehabilitation planning, and soft tissue fatigue analysis in the musculoskeletal system.

Genu valgum (GV) is a common lower limb deformity that may increase the risk of anterior cruciate ligament (ACL) injury. This study used OpenSim musculoskeletal modeling and kinematic analysis to investigate the mechanical responses of the ACL under fatigue in females with GV. Eight females with GV and eight healthy controls completed a running-induced fatigue protocol. Lower limb kinematic and kinetic data were collected and used to simulate stress and strain in the anteromedial ACL (A–ACL) and posterolateral ACL (P–ACL) bundles, as well as peak joint angles and knee joint stiffness. The results showed a significant interaction effect between group and fatigue condition on A–ACL stress. In the GV group, A–ACL stress was significantly higher than in the healthy group both before and after fatigue (p < 0.001) and further increased following fatigue (p < 0.001). In the pre-fatigued state, A–ACL strain was significantly higher during the late stance phase in the GV group (p = 0.036), while P–ACL strain significantly decreased post-fatigue (p = 0.005). Additionally, post-fatigue peak hip extension and knee flexion angles, as well as pre-fatigue knee abduction angles, showed significant differences between groups. Fatigue also led to substantial changes in knee flexion, adduction, abduction, and hip/knee external rotation angles within the GV group. Notably, knee joint stiffness in this group was significantly lower than in controls and decreased further post-fatigue. These findings suggest that the structural characteristics of GV, combined with exercise-induced fatigue, exacerbate A–ACL loading and compromise knee joint stability, indicating a higher risk of ACL injury in fatigued females with GV.

Introduction: Foot progression angle affects gait and lowerlimb alignment. Altered angles may increase knee and ankle loading and produce tissue loading patterns previously linked to musculoskeletal injury. This study investigates how different foot progression angles modify knee and ankle biomechanics in young adults with flexible flatfoot. Methods: 28 participants (aged 18–35 years) with flexible flatfoot completed gait trials under three foot progression angle conditions. Kinematic and kinetic variables were analyzed using one-dimensional statistical parametric mapping. A 1D convolutional neural network was applied to classify progression angle patterns based on flexible flatfoot severity and gait biomechanics. Results: Decreasing foot progression angle reduced the ankle eversion/inversion range and knee abduction and external rotation (p < 0.05). Increasing foot progression angle lowered early stance ankle plantarflexion and increased knee abduction/external rotation (p < 0.05). Kinetically, a smaller foot progression angle reduced peak ankle plantarflexion moment and knee extension moment but increased the first peak of the knee adduction moment and rotational moment fluctuations (p < 0.05). A larger foot progression angle reduced rotational fluctuations and terminal stance knee extension moment (p < 0.05). The convolutional neural network model was most accurate for moderate flexible flatfoot cases, and ankle coronal and knee transverse biomechanics showed the strongest discriminative power. Conclusion: Modifying the foot progression angle can meaningfully alter knee and ankle loading in young adults with flexible flatfoot. Neutral or mild toe-in angles may help mitigate excessive eversion and rotational stress, suggesting a simple noninvasive adjustment that clinicians can incorporate during gait retraining or orthotic prescription. Because biomechanical responses vary across individuals, FPA modification may be the most effective when tailored to patient-specific gait characteristics. In addition, deep-learning-based gait classification shows promise for supporting personalized monitoring and guiding clinical decision-making during rehabilitation.

(1) Background: Chronic ankle instability (CAI), a common outcome of ankle sprains, involves recurrent sprains, balance deficits, and gait impairments linked to both peripheral and central neuromuscular dysfunction. Dual-task (DT) demands further aggravate postural control, especially during stair descent, a major source of fall-related injuries. Yet the biomechanical mechanisms of stair-to-ground transition in CAI under dual-task conditions remain poorly understood. (2) Methods: Sixty individuals with CAI and age- and sex-matched controls performed stair-to-ground transitions under single- and dual-task conditions. Spatiotemporal gait parameters, center of pressure (COP) metrics, ankle inversion angle, and relative joint work contributions (Ankle%, Knee%, Hip%) were obtained using 3D motion capture, a force plate, and musculoskeletal modeling. Correlation and regression analyses assessed the relationships between ankle contributions, postural stability, and proximal joint compensations. (3) Results: Compared with the controls, the CAI group demonstrated marked control deficits during the single task (ST), characterized by reduced gait speed, increased step width, elevated mediolateral COP root mean square (COP-ml RMS), and abnormal ankle inversion and joint kinematics; these impairments were exacerbated under DT conditions. Individuals with CAI exhibited a significantly reduced ankle plantarflexion moment and energy contribution (Ankle%), accompanied by compensatory increases in knee and hip contributions. Regression analyses indicated that Ankle% significantly predicted COP-ml RMS and gait speed (GS), highlighting the pivotal role of ankle function in maintaining dynamic stability. Furthermore, CAI participants adopted a “posture-first” strategy under DT, with concurrent deterioration in gait and cognitive performance, reflecting strong reliance on attentional resources. (4) Conclusions: CAI involves global control deficits, including distal insufficiency, proximal compensation, and an inefficient energy distribution, which intensify under dual-task conditions. As the ankle is central to lower-limb kinetics, its dysfunction induces widespread instability. Rehabilitation should therefore target coordinated lower-limb training and progressive dual-task integration to improve motor control and dynamic stability.

Background: Football is one of the most popular sports in the world, and it is also a sport with a high rate of injury. The study aims to investigate the effects of physical and mental mixed fatigue (PMF) on knee biomechanics during sidestep cutting maneuvers in elite male soccer players, thereby assessing the potential mechanisms underlying non-contact knee injuries. Methods: Thirty-six elite male soccer players were recruited (age: 21.61 ± 1.22 years; body mass: 75.16 ± 6.34 kg; height: 175.8 ± 3.53 cm; shoe size: 41–44 EUR). Following a targeted fatigue induction protocol, key lower limb biomechanical data were acquired during anticipated sidestep cutting maneuvers both pre- and post-PMF. Statistical analyses were performed utilizing paired sample t-tests and one-dimensional Statistical Parametric Mapping (SPM1d). Results: Following PMF, knee valgus increased at initial contact (P = 0.022). Kinetic analysis, supported by SPM1d, revealed a marked transition from an extensor-dominant to a flexor-dominant pattern in sagittal knee moments (P = 0.007), alongside elevated knee valgus moments (P = 0.039). Neuromuscularly, quadriceps and lateral gastrocnemius activation (iEMG/RMS) significantly decreased, whereas compensatory increases were observed in the hamstrings and medial gastrocnemius (all P < 0.001). Conclusion: While PMF preserved most kinematics, the statistically significant increase in knee valgus, though small in magnitude, suggests an impaired frontal-plane control that may elevate Anterior Cruciate Ligament (ACL) strain. The shift from quadriceps to hamstring dominance reflects a compensatory neuromuscular strategy. These findings emphasize the importance of incorporating cognitive load into injury-prevention programs and monitoring mental fatigue to reduce non-contact knee injury risks.