Xin Li
57225159776
Publications - 9
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
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 Impact of Shoe Heel-Toe Drop on Plantar Pressure During the Third Trimester of Pregnancy
Publication Name: Advances in Transdisciplinary Engineering
Publication Date: 2024-01-01
Volume: 59
Issue: Unknown
Page Range: 509-514
Description:
Pregnancy induces various physiological adaptations to accommodate the growing fetus. Pregnant women commonly experience changes in gait, balance, and center of gravity, which may increase the risk of falls. This study investigates the effects of negative heel shoes on plantar pressure distribution during walking in third-trimester pregnant women. Twelve healthy primigravidas participated, wearing both flat shoes and negative heel shoes while walking. Plantar pressure data were collected using the Pedar-X® insole system. Results revealed that negative heel shoes significantly reduced maximum force in the medial forefoot regions compared to flat shoes, and the force-time integral only significantly decreased in the medial forefoot region. Wearing negative-heeled shoes resulted in an increase in peak force in the hallux region. The study suggests that modifying heel-toe drop in shoes can effectively mitigate plantar pressure during third-trimester pregnancy, reducing the risk of forefoot discomfort and potential injuries. Negative heel shoes could be beneficial for pregnant women, offering a solution to alleviate forefoot pressure and promote foot blood circulation during walking. However, further optimization is needed in the hallux region for negative heel shoes.
Open Access: Yes
DOI: 10.3233/ATDE240587
Biomechanical Analysis of Gymnastics Movements Using Wearable Motion Capture Systems and Linear Sensors: A Case Study of the Kipping Bar Muscle-Up
Publication Name: Advances in Transdisciplinary Engineering
Publication Date: 2024-01-01
Volume: 59
Issue: Unknown
Page Range: 523-529
Description:
Gymnastics moves are complex and varied, needing precise technique and body coordination, which traditional biomechanics methods struggle to capture in detail. This study aims to look at and judge how well new motion capture and analysis technology works in gymnastics biomechanics. This study picks the kipping bar muscle up move and uses the IMU-based Xsens system and the GymAware RS unit power test system to finely look at how athletes do the move in terms of body position, power, work done by the body, and main upper limb joint movements. The study tested 8 male elite collegiate gymnasts, collecting movement data with Xsens and power data with GymAware RS unit. Results show the kipping bar muscle up takes 1.42 seconds, with a 1.13-meter shift of the body's center and a peak speed of 3.40m/s. In terms of power, the peak output was 2772.96J/s, showing the need for explosive power and fast strength. Also, the total work done was 889.70J, showing the move's efficiency and energy level. This study shows that new motion capture and analysis tech is effective in capturing complex gymnastics moves. The use of these techs not only expands the ways biomechanics can be studied but also helps in making training better and improving how efficiently moves are done.
Open Access: Yes
DOI: 10.3233/ATDE240589
Customized 3D-Printed Insoles for Diabetic Foot Care: Finite Element analysis and Machine Learning Approach
Publication Name: Advances in Transdisciplinary Engineering
Publication Date: 2024-01-01
Volume: 59
Issue: Unknown
Page Range: 515-522
Description:
Diabetic foot is a common complication in patients with diabetes, which can lead to plantar ulcers and even necessitate amputation. This study aims to utilize finite element analysis to simulate the offloading effects of 3D-printed insoles with various structures on plantar pressure and to explore the use of machine learning in providing optimal plantar pressure offloading solutions for patients with diabetic foot. The results demonstrated that negative Poisson's ratio structured insoles were more effective in reducing plantar pressure (reducing pressure by an average of 39.2%) than barefoot and conventional structures. This was achieved through a unique lateral contraction deformation, which increased the contact area with the foot. The pressure-reducing effect of insoles may be weight-related, suggesting that heavier patients may require stiffer insoles. However, the machine learning algorithm demonstrated a poor fit (only 60.75%) in the task of recommending suitable insoles. In conclusion, this study demonstrated the significant effect of negative Poisson's ratio structured insoles in reducing plantar pressure in diabetic patients, providing new ideas for diabetic foot protection. With the development of data analysis technology in the future, the feasibility and application of personalised insole design will be more promising.
Open Access: Yes
DOI: 10.3233/ATDE240588
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
Advances and future directions of foetal finite element modelling in childbirth: from biomechanical interactions to clinical implications
Publication Name: International Journal of Biomedical Engineering and Technology
Publication Date: 2025-01-01
Volume: 49
Issue: 2
Page Range: 139-168
Description:
This review aims to summarise the applications of finite element modelling used in labour mechanics and explore their clinical relevance in optimising labour management and intervention strategies. A systematic literature search was performed in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines across the PubMed, IEEE Xplore, Web of Science and Elsevier ScienceDirect databases. Selected 13 studies were evaluated based on the methodological quality assessment of single-subject finite element analysis (MQSSFE). The review highlights the widespread use of whole-body foetal finite element models in childbirth simulations. Key factors in childbirth biomechanics include uterine contraction intensity, abdominal muscle forces, pelvic floor function, foetal head flexion, tissue properties, and descent trajectory. Finite element modelling offers key insights but faces challenges in accuracy, personalised anatomy, and clinical application. Advances in computational biomechanics, imaging validation, and patient-specific simulations will improve childbirth understanding, risk assessment and labour management.
Open Access: Yes
Foot Progression Angle Modulates Three-Dimensional Lower-Limb Biomechanics in Flexible Flatfoot: Kinematic–Kinetic Patterns and Clinical Implications
Publication Name: Journal of Foot and Ankle Research
Publication Date: 2026-03-01
Volume: 19
Issue: 1
Page Range: Unknown
Description:
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.
Open Access: Yes
DOI: 10.1002/jfa2.70126
Foot Progression Angle Modulates Knee Loading During Walking in Individuals with Flexible Flatfoot
Publication Name: Annals of Biomedical Engineering
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Purpose: This study evaluated tibiofemoral loading and medial meniscal stress distribution in individuals with flexible flatfoot (FFF) during walking under different foot progression angle (FPA) conditions. Methods: This study analyzed the gait of 28 FFF patients (16 males, 12 females) under three FPA conditions (neutral, toe-in, toe-out). Kinematic (Vicon) and kinetic (Kistler) data were used to estimate tibiofemoral forces in OpenSim. Subsequently, joint angles and muscle forces at peak tibiofemoral forces were used to drive a finite element (FE) model of the knee, enabling the comparison of meniscal von Mises stress, maximum shear stress, and contact pressure across FPA conditions. Results: Tibiofemoral force increased during early stance (9–11%) in the toe-in condition with this increase reaching statistical significance in males (p = 0.008, mean partial η2=0.70 within the SPM-identified cluster). FE analysis showed that peak stresses and contact pressure were primarily localized in the anterior region of the medial meniscus. A consistent directional response to FPA was observed with the lowest peak values occurring in the toe-in condition and the highest values in the toe-out condition. Conclusion: Adjusting FPA modulates intra-articular knee loading via the kinetic chain. For FFF patients, neutral FPA provides stable loading. The toe-in condition presents a complex mechanism: despite increasing tibiofemoral force (notably in males), it reduces peak stress by altering contact mechanics and stress distribution. Therefore, FFF gait interventions must be individualized based on factors like foot morphology, sex, and functional goals.
Open Access: Yes
