This study investigated the effects of knee braces with differing stiffness on in vivo knee kinematics and neuromuscular control during single-leg lateral landings. 14 healthy males performed landings under three conditions: no brace (Control), low-stiffness (Type-1), and high-stiffness (Type-2). Kinematics were quantified via dual fluoroscopic imaging, and sEMG recorded seven lower-limb muscles. Brace mechanics were assessed via three-point bending. Statistical analysis used repeated-measures ANOVA (α = 0.05). Kinematically, neither brace restricted knee flexion. Both significantly reduced varus angle (Type-1: 27–100% stance, p=0.043 ; Type-2: 60–100% stance, p=0.033 ), and Type-2 also lowered peak sagittal flexion acceleration (5.0 rad/s2, p=0.013 ). Neuromuscularly, Type-1 enhanced multiplanar control, advancing rectus femoris (154.7 ms vs. Type-2, p=0.005 ) and vastus lateralis (35.6 ms vs. Control, p=0.046 ) activation without increasing rotational instability. Conversely, Type-2 demonstrated a trade-off: despite earlier vastus medialis activation (43.6 ms vs. Control, p=0.011 ), it significantly delayed gluteus medius activation (23.9 ms vs. Type-1, p=0.037 ) and, critically, exacerbated compensatory internal-rotation acceleration (3.3 rad/s2 vs. Type-1, p=0.006 ) at peak flexion. The low-stiffness brace leveraged neuromuscular coordination for multiplanar stability, whereas the high-stiffness brace improved frontal-plane protection at the cost of rotational instability. These findings provide biomechanical evidence for the synergistic optimization of mechanical support and neuromuscular adaptation in knee brace design for populations with similar characteristics to the young male athletes studied herein.

Background: Insufficient vastus medialis (VM) activation and excessive patellofemoral joint loading are primary contributors to patellofemoral pain (PFP). Although electrical muscle stimulation can reduce pain and enhance strength, evidence for its efficacy in selectively strengthening the VM and improving lower-limb biomechanics in PFP patients remains limited. This study aimed to investigate the clinical efficacy of electrical stimulation combined with strength training versus conventional strength training in PFP patients. Methods: Forty-six participants were randomly assigned to an electrical muscle stimulation combined strength training (EMS) group and a muscle strength training (MST) group. Both groups completed a 6-week hip/knee strengthening program (3 sessions/week, 60 min/session) whereas the EMS group received the extra electrical stimulation of VM during the knee training. Prior to and after the intervention, participants performed stair descent and isokinetic strength tests. Subjective knee pain and functional capacity were assessed using patient-reported measures, while kinematic, kinetic, and surface electromyography data were collected during stair descent. Results: After the 6-week intervention, both groups showed reduced knee valgus angle, hip internal rotation angle, patellofemoral joint stress and reaction force, along with decreased activation of the gluteus medius, gluteus maximus, and vastus lateralis and increased VM activation during stair descent (all p < 0.05). In addition, both groups exhibited increased hip and knee muscle strength (all p < 0.05). Compared with the MST group, the EMS group demonstrated greater improvements in medial-lateral quadriceps activation ratio and knee extension strength, alongside more reductions in knee external rotation angle, hip adduction angle, and the anterior knee pain scale scores (all p < 0.05). Conclusions: EMS combined with strength training more effectively mitigated abnormal hip–knee movement patterns during stair descent, balanced the activation of the vastus medialis and lateralis, increased knee extensor strength, and alleviated pain and enhanced function in PFP patients. Trial registration: Trial Registration Number: ChiCTR2300067598, Date of trial registration: 1/13/2023.

Single-leg landing (SL) imposes substantial mechanical demand on the patellar tendon, with peak patellar tendon force (PPTF) serving as a key metric for characterizing the internal mechanical environment of the tendon. This study integrates 3D modeling with high-resolution in vivo kinematics to quantify the patellar tendon moment arm (PTMA) and the PPTF, examining their biomechanical correlations and neuromuscular features. Minimal sex-related PTMA differences suggest comparable anatomical leverage during knee flexion across both sexes. In both sexes, PPTF was significantly positively correlated with the knee flexion angle at initial contact (IC) and significantly negatively correlated with the knee range of motion (ROM). Muscle network analysis showed lower clustering coefficients in high-frequency versus low-frequency bands. Reduced IC knee flexion and increased ROM attenuate patellar tendon mechanical demand. By incorporating individualized moment-arm analysis, this study provides a biomechanical basis for understanding patellar tendon loading during landing.

Purpose: To test whether ultrasound-triggered pre-landing quadriceps focal vibration acutely improves knee mechanics and coordination during single-leg drop landings under fresh vs combined cognitive-physical fatigue. Methods: Twenty-four healthy males (25.4 ± 2.1 years; 175.0 ± 3.1 cm; 73.2 ± 4.9 kg) performed randomized-crossover single-leg forward drop landings. Quadriceps vibration was off or ultrasonically triggered. Landings were tested pre- and post-combined fatigue (15 min dual-task cognitive +90 s burpees). Results: In the pre-fatigued state, vibration increased peak knee flexion angle by 2.67% (P = 0.001) and knee flexion range of motion by 1.36% (P = 0.008), reduced knee flexion work by 1.69% (P = 0.024), peak vertical ground reaction forces loading rate by 6.67% (P < 0.001), peak patellar tendon force by 5.92% (P < 0.05), time to stabilization by 3.88% (P = 0.003), and maximal diagonal line length by 2.32% (P = 0.008). Post-fatigue, vibration increased determinism (P = 0.023), Shannon entropy (P = 0.041), and dynamic time warping distance (P = 0.045) without significant kinematic or energetic changes. Conclusions: Pre-landing quadriceps vibration acutely enhances sagittal-plane landing biomechanics, increasing knee flexion, reducing eccentric work and impact loading, and improving adaptive coordination in fresh conditions, with no significant effects under combined fatigue.

This study aimed to explore the independent and interactive effects of varying squat depths and movement speeds on dynamic postural stability during the Part the Wild Horse's Mane (PWHM) movement. Thirteen male participants (age: 25.86 +/- 1.35 years; height: 174.26 +/- 6.09 cm; body mass: 68.64 +/- 8.15 kg) performed the PWHM movement at three different squat heights, high squat (HS), middle squat (MS), low squat (LS), and two different speeds, fast and slow. Dynamic postural stability (DPSI) was assessed through the center-of-mass (CoM) trajectory and the center-of-pressure (CoP) trajectory. The analyses used two-factor repeated-measures ANOVA and statistical nonparametric mapping, with key metrics including anteroposterior stability (APSI), mediolateral stability (MLSI), vertical stability (VSI), DPSI indices, and the path lengths of the CoP and CoM. LS exhibited significantly greater CoP and CoM path lengths compared with MS and HS (p < 0.01). Furthermore, fast movements demonstrated higher VSI and DPSI than slow movements (p < 0.05). Tai Chi with different squat depths and speeds can affect postural stability. To reduce the fall risk, older adults and individuals with balance impairments should prioritize slower Tai Chi movements, particularly when using high squat postures.

The scissor jump (SKJ) is vital in badminton, particularly for backcourt shots, but fatigue increases lower limb load and injury risk. This study investigates how quadriceps fatigue affects biomechanical characteristics and load during SKJ landing, aiming to understand its impact on injury risk. This study involved 27 amateur male badminton players from Ningbo University. Quadriceps fatigue was induced via knee exercises and footwork drills. Biomechanical data before (prior fatigue-PRF) and after fatigue (post fatigue-POF) were recorded using a force platform and motion capture system. Muscle activation was measured with EMG and analyzed through musculoskeletal modeling, with paired t-tests and SPM 1D (Statistical Parametric Mapping 1D) for statistical analysis. Under the POF condition, knee flexion angle increased, and power decreased (p < 0.001, p < 0.001, respectively); ankle plantarflexion angle increased, and power decreased (p < 0.001, p < 0.001, respectively). As fatigue progressed, joint reaction forces initially decreased but later increased. Joint energy dissipation decreased, with differences more pronounced in the coronal than sagittal plane. Achilles tendon force and anterior-posterior tibial shear force decreased, while coronal plane center-of-mass displacement increased. Findings show quadriceps fatigue harms limb stability, upping knee and ankle loads, disrupting the movement pattern, and risking coronal plane injuries. It is recommended that athletes enhance quadriceps endurance, improve neuromuscular control, and refine landing techniques to maintain stability and prevent injuries when fatigued.

The purpose of this study is to restore the before fracture kinematic state by using the observed foot bone displacements as boundary conditions for finite element (FE) analysis. Secondly, this study aims to compare the biomechanical changes of the foot before and after a metatarsal (MT) fracture using this method. A total of 21 subjects had previously experienced a shaft stress fracture of the MT5 in the six months before the collection of experimental data. All patients received treatment through the use of cast immobilization for duration of 4-6 weeks. After the subject's recovery, we obtained gait biomechanical data. At the same time, we also obtained gait data from 21 healthy subjects as the control group. This study found that when a fracture of the MT5 occurs, even after rehabilitation, there is a significant impact on the metatarsal.

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.

Machine learning (ML) has emerged as a powerful tool to analyze gait data, yet the “black-box” nature of many ML models hinders their clinical application. Explainable artificial intelligence (XAI) promises to enhance the interpretability and transparency of ML models, making them more suitable for clinical decision-making. This systematic review, registered on PROSPERO (CRD42024622752), assessed the application of XAI in gait analysis by examining its methods, performance, and potential for clinical utility. A comprehensive search across four electronic databases yielded 3676 unique records, of which 31 studies met inclusion criteria. These studies were categorized into model-agnostic (n = 16), model-specific (n = 12), and hybrid (n = 3) interpretability approaches. Most applied local interpretation methods such as SHAP and LIME, while others used Grad-CAM, attention mechanisms, and Layer-wise Relevance Propagation. Clinical populations studied included Parkinson’s disease, stroke, sarcopenia, cerebral palsy, and musculoskeletal disorders. Reported outcomes highlighted biomechanically relevant features such as stride length and joint angles as key discriminators of pathological gait. Overall, the findings demonstrate that XAI can bridge the gap between predictive performance and interpretability, but significant challenges remain in standardization, validation, and balancing accuracy with transparency. Future research should refine XAI frameworks and assess their real-world clinical applicability across diverse gait disorders.

Background: Running is a widely practiced physical activity but carries a high risk of injury, with foot structure, particularly the medial arch, playing a vital role in biomechanical performance and injury prevention. As the core of foot support, the arch is essential for absorbing impact, transmitting force, and maintaining dynamic stability. This study aims to compare the dynamic stability of runners with moderate flatfoot and those with normal arches in the initial, steady, and fatigue stages in order to elucidate how fatigue differently affects their dynamic postural control. Methods: Twelve male runners were recruited. Using inertial measurement units (IMUs) and a Zebris treadmill system, data on Maximum Lyapunov Exponent(MLE) and plantar center of pressure (COP) trajectories were collected during the initial, steady-state, and fatigued phases. Results: In the fatigue phase, runners with flatfoot showed an increase of 0.05 s⁻¹ in short-term MLE compared to those with normal arches (p < 0.05), indicating significantly lower stability under fatigue. Conclusions: The deterioration of lower-limb dynamic stability in flatfoot runners is dependent on fatigue. Specifically, their overall lower dynamic stability stems primarily from a marked increase in MLE when entering the fatigued phase. Concurrently, fatigue induces alterations in COP trajectory and temporal gait parameters in flatfoot runners; they signify reduced efficiency in gait control.