Xin Li

57225159776

Publications - 6

Parametric cushioning lattice insole based on finite element method and machine learning: A preliminary computational analysis

Yaodong Gu Gusztáv Fekete Dong Sun András Kovács Yang Song Zhenghui Lu Xin Li Kámán András

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

DOI: 10.1016/j.jbiomech.2025.112674

Will this be the next step? A systematic review of 3D printing in footwear biomechanics

Yaodong Gu Gusztáv Fekete Dong Sun András Kovács Yang Song Zhenghui Lu Xin Li

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

DOI: 10.1080/19424280.2025.2472251

The Impact of Shoe Heel-Toe Drop on Plantar Pressure During the Third Trimester of Pregnancy

Yaodong Gu Gusztáv Fekete András Kovács Siqin Shen Zixiang Gao Yuqi He Zhenghui Lu Xin Li

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

Yaodong Gu Gusztáv Fekete Qichang Mei Zixiang Gao Yining Xu Zhenghui Lu Wei Liu Xin Li

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

Yaodong Gu Gusztáv Fekete Zixiang Gao Yining Xu Zhenghui Lu Xin Li Qiaolin Zhang Hairong Chen

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

Yaodong Gu Gusztáv Fekete Minjun Liang Dong Sun András Kovács Yang Song Zhenghui Lu Xin Li Yi Yuan

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

DOI: 10.3389/fbioe.2024.1506002