Zhenghui Lu
57222247894
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 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
Mixed comparison of intervention with eccentric, isometric, and heavy slow resistance for Victorian Institute of Sport Assessment Patella Questionnaire in adults with patellar tendinopathy: A systematic review and network meta-analysis
Publication Name: Heliyon
Publication Date: 2024-11-15
Volume: 10
Issue: 21
Page Range: Unknown
Description:
Background: PT (Patellar Tendinopathy) is a degenerative disorder of the tendons induced via extended overstretching or overuse of the tendons instead than usual inflammation. In the past, humans have centered on a number of strategies of treating PT such as ultrasound and surgical treatment. However, they did no longer genuinely consider the effectiveness of eccentric, isometric, or HSR (Heavy Slow Resistance Training) education for PT; They did now not really outline the stage of PT to beautify the uniformity of the find out about participants; They did no longer immediately examine the affects of isometric, eccentric, and HSR training. This systematic assessment chosen eccentric, isometric, and heavy gradual resistance coaching for the remedy of patellar tendinopathy and their respective prognostic effects will supply valuable, top notch evidence-based insights as properly as vital facts and advice for future scientific administration of patellar tendinopathy. Methods: A thorough and comprehensive search was conducted across the Web of Science, PubMed, and Scopus databases, encompassing a wide range of relevant journals and sources, in order to perform a rigorous systematic review and network meta-analysis, ensuring the inclusion of all pertinent and high-quality studies. The selected studies satisfied predetermined eligibility requirements, which included: (1) PT patients included in the studies; (2) use of eccentric, isometric, and heavy slow resistance training as interventions; and (3) evaluation of VISA-P (Victorian Institute of Sport Assessment Patella Questionnaire) outcome measures. The effect magnitude was measured using the standard mean difference. The risk of bias inherent in each of the studies that were meticulously selected and included in the comprehensive analysis was rigorously evaluated and assessed using the well-established Cochrane Collaboration Risk of Bias Assessment Tool, ensuring the robustness and reliability of the research findings. Results: Three scientific databases yielded a total of 1460 studies, of which 7 were included in the final analysis. The findings indicated that eccentric training (0.01 in Rank 1 and 0.06 in Rank 8) is the worst method for increasing VISA-P level in patients with patellar tendinopathy, while moderate resistance slow training (0.25) and Rank 1 and Rank 8 are the best options. Conclusions: While heavy slow resistance is more suited for attaining long-term improvements in knee function, progressive tendon-loading exercises combined with isometric training or moderate slow resistance training are more beneficial than eccentric training alone. Eccentric training gives a greater range of exercise venues and doesn't require any additional training equipment. The inability to directly compare the effects of heavy slow, eccentric, and isometric resistance training constitutes a significant drawback of this review. This limitation stems from the scarcity of research that compares the outcomes of these various therapeutic approaches. To address this constraint, future research endeavors should strive to conduct comparative studies of these strategies. By doing so, they can aim to bridge this evaluation gap and facilitate a more effective and comprehensive assessment of their respective efficacies.
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
