Yang Song
57206814107
Publications - 7
Running-Induced Fatigue Exacerbates Anteromedial ACL Bundle Stress in Females with Genu Valgum: A Biomechanical Comparison with Healthy Controls
Publication Name: Sensors
Publication Date: 2025-08-01
Volume: 25
Issue: 15
Page Range: Unknown
Description:
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.
Open Access: Yes
DOI: 10.3390/s25154814
Parametric cushioning lattice insole based on finite element method and machine learning: A preliminary computational analysis
Publication Name: Journal of Biomechanics
Publication Date: 2025-05-01
Volume: 184
Issue: Unknown
Page Range: Unknown
Description:
The cushioning performance of insole has always been a critical consideration in its design. While the development of intelligent methods and the emergence of additive manufacturing (AM) technology have enhanced design freedom and convenience, a standardized approach to guide designers in selecting optimal materials and structures for specific scenarios is still lacking. This study aims to propose a controllable parameterized lattice cushioning insole (PLI) by integrating finite element (FE) and machine learning (ML) methods. The insole performance can be adjusted by modifying the structural parameters (a, b) and the internal strut thickness (t). The findings indicate that PLI, under the optimal parameter combination (a = 2.54, b = 3.56, t = 3.15), can reduce plantar pressure by up to 44.45 %, which may be achieved by increasing the contact between the footwear and the foot. The data-driven PLI optimization design method proposed in this study significantly enhances the cushioning performance of insole structures, simplifies the optimization process for selecting insole structures or materials, and provides a systematic and efficient solution for insole design. Although the initial preparation of material data is time-intensive, the trained model eliminates the need for repeated laboratory gait analysis or plantar pressure measurements, offering a foundational reference for clinical applications in insole structure design.
Open Access: Yes
The Effects of Skill Level on Lower-Limb Injury Risk During the Serve Landing Phase in Male Tennis Players
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-03-01
Volume: 15
Issue: 5
Page Range: Unknown
Description:
The kinematic and kinetic performance of tennis players differs across skill levels, with joint range of motion (ROM), moments, and stiffness being strongly linked to injury risk. Focusing on the biomechanical characteristics of lower-limb joints throughout the landing stage, especially among athletes of different skill levels, aids in understanding the link between injury risk and performance level. This study recruited 15 male campus tennis enthusiasts and 15 male professional tennis players. The kinematic and kinetic differences between amateur and professional players during the landing phase of the tennis serve were analyzed using SPM1D 0.4.11 and SPSS 27.0.1, with independent-sample t-tests applied in both cases. Throughout the tennis serve’s landing stage, the professional group exhibited significantly greater sagittal plane hip-joint stiffness (p < 0.001), horizontal plane moment (59~91%; p = 0.036), and a significantly higher peak moment (p = 0.029) in comparison with the amateur group. For the knee joint, the professional group exhibited significantly larger ROM in flexion–extension (0~82%; p = 0.003); along with greater ROM (0~29%; p = 0.042), moment (12~100%; p < 0.001), peak moment (p < 0.001) in adduction-abduction; and internal–external rotational moments (19~100%; p < 0.001) were markedly higher. The professional group showed significantly higher ankle joint ROM (p < 0.001) and moments (6~74%; p = 0.004) in the sagittal plane, as well as greater horizontal-plane ROM (27~67%; p = 0.041) and peak moments (p < 0.001). Compared with amateur tennis players, professional tennis players exhibit greater ROM, joint moments, and stiffness in specific planes, potentially increasing their risk of injury during the landing phase.
Open Access: Yes
DOI: 10.3390/app15052681
Will this be the next step? A systematic review of 3D printing in footwear biomechanics
Publication Name: Footwear Science
Publication Date: 2025-01-01
Volume: 17
Issue: 2
Page Range: 127-142
Description:
Three-dimensional (3D) printing technology enables designers to push the limits of their creativity, creating new possibilities for high-performance footwear. With advancements in engineering and a deeper understanding of biomechanics, researchers have designed footwear with complex structures comprising various materials. These materials and structures exhibit diverse physical properties and are used in physical activity, sports rehabilitation and competitive athletics. This article offers a systematic review of the biomechanical responses to advancements in 3D-printed footwear research from the past decade, focusing on three key domains: injury prevention, comfort, and athletic performance. Current research suggests that adjusting material stiffness or incorporating specific design elements in 3D-printed footwear can modulate plantar pressure distribution, which plays a crucial role in injury prevention, while also enhancing comfort. However, a consensus has yet to be reached regarding the impact of such footwear on athletic performance. Owing to the heterogeneity of research methodologies, the effectiveness of these designs may be significantly influenced by the design specifics, materials used, and individual user differences. Further systematic research and long-term clinical trials are crucial to advancing this field.
Open Access: Yes
The effects of different carbon-fiber plate shapes in shoes on lower limb biomechanics following running-induced fatigue
Publication Name: Frontiers in Bioengineering and Biotechnology
Publication Date: 2025-01-01
Volume: 13
Issue: Unknown
Page Range: Unknown
Description:
Different shapes of carbon-fiber plates (CFPs) are likely to affect lower limb biomechanics, particularly under conditions of running-induced fatigue, and potentially impact runners’ performance and risk of injury. However, no studies have yet elucidated the precise effects of CFP shapes on the lower limb biomechanical characteristics subsequent to running-induced fatigue. The purpose of this study was to investigate the effects of different CFP shapes in running shoes on the lower limb biomechanics of runners following running-induced fatigue. 12 male runners (aged 21.8 ± 1.3 years, mass 59.1 ± 4.1 kg, height 168.9 ± 2.2 cm, weekly running distance 68.8 ± 5.5 km/week) were recruited for this study. Two-way repeated measures ANOVA was used to compare kinematic and kinetic data, while SPM (Statistical Parametric Mapping) was used to assess the activation levels of lower limb muscles. Compared to wearing flat CFP shoes (“Flat”), wearing curved CFP shoes (“Curve”) resulted in a significant reduction in the hip (p = 0.034) and knee contact angle (p < 0.000), as well as a significant decrease in the hip flexion moment (p = 0.008). The activation level of the tibialis anterior (TA) was significantly higher when wearing “Curve” in pre-fatigue compared to “Flat”, whereas the opposite was observed post-fatigue. The curved CFP altered the bending angle of the forefoot, thereby significantly reducing the joint angles and joint moments of the hip and knee.
Open Access: Yes
Integrating footwear features into fatigue prediction models for marathon runners: A hybrid CNN-LSTM approach
Publication Name: Proceedings of the Institution of Mechanical Engineers Part P Journal of Sports Engineering and Technology
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Footwear design, especially the curvature of carbon plates, may influence fatigue perception, but few studies have integrated footwear features into fatigue prediction models. This study aimed to develop a hybrid CNN-LSTM model to predict runners’ fatigue states and evaluate the impact of footwear characteristics on fatigue perception. Twelve male marathon runners (age = 21.8 ± 1.3 years; body mass = 59.1 ± 4.1 kg; height = 168.9 ± 2.2 cm; and weekly mileage = 68.8 ± 5.5 km) participated. They wore two types of carbon-plated shoes (flat plate, FP, and curved plate (CP)) and ran at a steady pace (Borg score 13) until a Borg score of 16 or 85% of maximum heart rate was reached for 2 min. EMG signals and physiological data were collected during treadmill running. A hybrid CNN-LSTM model was trained with and without footwear features to predict fatigue states. The model with footwear features achieved 85% accuracy, compared to 69% without. Curved carbon plate (CP) shoes delayed semi-fatigue onset, indicating better initial support, but the time to full fatigue was similar for both shoe types. The CNN-LSTM model effectively predicted fatigue states, with significant improvement when footwear features were included. Footwear design, particularly carbon plate curvature, influenced fatigue perception.
Open Access: Yes
Pregnancy-induced gait alterations: meta-regression evidence of spatiotemporal adjustments
Publication Name: Frontiers in Bioengineering and Biotechnology
Publication Date: 2024-01-01
Volume: 12
Issue: Unknown
Page Range: Unknown
Description:
During pregnancy, women undergo significant physiological, hormonal, and biomechanical changes that influence their gait. The forward shift of the center of mass and increased joint loads often result in a “waddling gait,” elevating the risk of falls. While gait changes during pregnancy have been documented, findings across studies remain inconsistent, particularly regarding variations at different pregnancy stages. This systematic review and meta-analysis aimed to quantify the impact of pregnancy stages on spatiotemporal gait parameters. A comprehensive literature search across six databases (PubMed, Web of Science, Scopus, EBSCO, Embase, and Cochrane Library) was conducted to identify studies on pregnancy and gait, and data on publication details, methodology, participant characteristics, gait outcomes, and study limitations were extracted. Out of 4,581 initial records, 21 studies met the inclusion criteria. The meta-analysis revealed significant changes in gait parameters during pregnancy, with decreases in stride length (effect size = −0.29) and gait speed (effect size = −0.55), and increases in stride width (effect size = 0.45), cycle time (effect size = 0.38), and double support time (effect size = 0.41). Meta-regression analyses indicated that gestational weeks significantly impacted stride length (β = −0.03 [95% CI, −0.055 to −0.002], p < 0.05) and stride width (β = 0.02 [95% CI, 0.003 to 0.039], p < 0.05), while no significant effects were found for cycle time, double support time, or gait speed. In conclusion, pregnancy leads to significant changes in gait patterns, with a notable increase in stride width and a decrease in stride length as gestation progresses, suggesting these adjustments are strategies for maintaining balance and stability in response to physiological changes. The analysis also emphasizes that while gestational age influences gait adaptations, other factors such as pelvic girdle pain, footwear, and psychological influences play crucial roles. Understanding these complex gait changes can inform interventions and guidelines to support mobility and safety for pregnant women throughout their pregnancy.
Open Access: Yes
