Molecular & Cellular Biomechanics

The application of the SPOC teaching model in college elective basketball courses: integrating biomechanical principles for enhanced performance

Mingming Si — 2025-01-16

The SPOC (Small Private Online Course) model is a new teaching model derived from Massive Open Online Courses (MOOC) and is an important direction for the reform and innovation of future higher education. In the practical application of SPOC teaching, subjectivity issues may arise, namely the influence of individual opinions and judgment criteria. The evaluation may focus on certain aspects and neglect others, resulting in incomplete overall assessment results. This paper applies the SPOC teaching model in three time periods: before class, during class, and after class, with a focus on integrating biomechanical principles into the evaluation of student performance in basketball. The study employs various research methods such as literature review, Analytic Hierarchy Process (AHP) analysis, and fuzzy comprehensive evaluation to construct a comprehensive evaluation index system for student ability improvement in SPOC teaching in higher education. This system incorporates biomechanical factors such as movement efficiency, force production, and body mechanics, which are essential for enhancing basketball skills. Based on this, an evaluation method for student ability improvement in college SPOC elective basketball courses is proposed using the AHP-fuzzy evaluation model. This model not only assesses traditional skill metrics but also integrates biomechanical assessments, such as shooting mechanics, dribbling efficiency, and defensive posture. The application of the AHP-fuzzy evaluation model, enhanced with biomechanical insights, demonstrates that his method can effectively improve students basketball abilities. The incorporation of biomechanical principles allows for a more holistic evaluation of student performance, emphasizing the importance of physical mechanics in skill development. The integration of the SPOC teaching model with biomechanical principles in elective basketball courses provides a comprehensive framework for evaluating and improving student performance. By focusing on both skill acquisition and biomechanical efficiency, this approach not only enhances basketball abilities but also fosters a deeper understanding of the physical demands of the sport.

MiR-6747-5p suppresses angiogenesis in esophageal squamous cell carcinoma by targeting EGFL6

Jiawen Huang — 2025-01-16

Epidermal growth factor-like domain 6 (EGFL6) plays a crucial role in angiogenesis in various malignant tumors. This study aimed to screen microRNAs (miRNAs) targeting EGFL6 and explore their mechanisms in regulating angiogenesis in esophageal squamous cell carcinoma (ESCC) cells. After analyzing the miRNA expression profiles of ESCC and using the target prediction algorithm, we screened three miRNAs that could potentially target EGFL6. By dual luciferase reporter gene assay and western blot, we found that miR-6747-5p could directly target EGFL6 and down-regulate EGFL6 expression in ESCC cells. The results of clone formation, CCK-8, Transwell, wound healing, and endothelial cell tube formation assay showed that miR-6747-5p exerted a significant inhibitory effect on the proliferation, migration, invasion, and angiogenesis of ESCC cells. At the same time, we observed that the phosphorylation levels of AKT and MAPK were decreased, the epithelial-mesenchymal transition (EMT) related E-cadherin expression was downregulated while N-cadherin was upregulated, and the protein expression of the pro-angiogenic factors, including platelet-derived growth factor subunit B (PDGFB), fibroblast growth factor 2 (FGF2), and angiogenin (ANG) were inhibited transfected with miR-6747-5p mimics. Further studies showed that the overexpression vectors of EGFL6 transfected into ESCC cells could reverse the inhibitory effects induced by miR-6747-5p. These findings reveal that miR-6747-5p could target EGFL6 and inhibit tumor angiogenesis and ESCC progression. miR-6747-5p may be a promising biomarker for the anti-angiogenic treatment of ESCC.

Research on the application of sports biomechanics in optimizing the effect of physical training

Xiaofeng Gou — 2025-01-16

This paper discusses the application of sports biomechanics in optimizing the effect of sports training, finds out the existing problems through quantitative evaluation of athletes’ technical movements, and puts forward improvement suggestions to maximize the training effect. In this study, 12 professional long jumpers were taken as the object, and advanced equipment such as high-speed photography, computer analysis and photoelectric timer were used to record the long jump movements of athletes in all directions, and the biomechanical parameters were analyzed. The results show that after four weeks of personalized training, the key performance indexes of athletes such as take-off speed, horizontal displacement, vertical jump height, landing technique and muscle strength have been significantly improved, and the average long jump performance has been significantly improved. Principal component analysis (PCA) reveals the key biomechanical factors that affect the performance of long jump, including take-off speed, horizontal displacement and vertical jump height. In addition, hierarchical cluster analysis helps to identify the technical characteristics and training needs of different athletes, which provides a basis for making personalized training plans. The results show that the application of sports biomechanics not only improves athletes’ performance, but also helps to reduce sports injuries and prolong sports life, and provides scientific training guidance for coaches. This study has important theoretical and practical value for promoting the development of sports science and improving the level of competitive sports.

Biomechanical and biodegradation performance of CSA-CSF reinforced cementitious composites: A bio-inspired approach

Bo Peng — 2025-01-16

This study investigates the mechanical, biodegradation, and microstructural performance of cementitious composites reinforced with Corn Straw Ash (CSA) and Corn Straw Fiber (CSF) for applications in bio-inspired materials and sustainable engineering. CSA, a pozzolanic material, enhances matrix densification, while CSF provides crack-bridging and toughness improvement. Dynamic mechanical testing under cyclic loading demonstrated that CSA-CSF composites exhibit superior fatigue resistance, retaining 85% of their initial compressive strength after 1000 cycles. Biodegradation studies in simulated body fluid (SBF) and acidic environments revealed that the composites maintain 75% compressive strength in SBF over 28 days, highlighting their potential for bioactive scaffolds. Scanning electron microscopy (SEM) and quantitative porosity analysis showed that CSA-derived Calcium Silicate Hydrate (C-S-H) gel effectively filled voids, while CSF enhanced fiber-matrix bonding, mimicking the hierarchical structure of biological systems. The results emphasize the dual benefits of CSA-CSF composites in dynamic environments and their alignment with sustainable and bio-inspired design principles. This research provides insights into the development of materials for biomechanical applications, including tissue engineering scaffolds and earthquake-resistant structures.

The impact of fatigue on the jumping mechanics and injury risk of basketball players

Tianci Zhao — 2025-01-16

Fatigue can significantly alter an athlete’s biomechanics and performance, which can increase their risk of injury. Important basketball moves like jump shots (JS) and countermovement jumps (CMJ) primarily use the muscles in the lower back and lower limbs. Basketball players’ jumping mechanics, performance, and risk of injury during CMJ, JS, and ankle sprains were all examined. A total of 415 male collegiate basketball players participated in the league, this season representing varying levels of jumping mechanics. Surface electromyography, a force plate, and a 3D motion analysis system were used to gather data. Field-goal percentage, the center of mass’s (CM) lowest point, joint angles during takeoff and landing, and Electromyography data from the lower leg muscles, erector spinae limbal, and rectus femoris were among the parameters that were recorded. Lower back muscle tiredness was created, and performance was evaluated after the fatigue. Data was analyzed using SPSS, with paired-sample t-tests, logistic, and Multiple Regression tests employed to examine the impact of fatigue on performance and injury risk. These tests assessed how fatigue affects shooting accuracy and joint angles, and increases the chance of injuries in basketball players. Following a period of tiredness, athletes’ field-goal percentages significantly decreased, whereas their CM lowest point increased on jump shots. In both CMJ and JS, fatigue leads to reduced knee flexion angles and increased ankle plantar flexion during landing, changing the contribution ratio of both legs. Due to impaired mechanics, these biomechanical changes suggest an increased probability of ankle sprains and an elevated risk of damage, especially during landing. The risk of lower back, knee, and ankle injuries increased due to major athletic impairments and altered landing mechanics caused by lower back muscular fatigue. To reduce basketball players’ risk of injury, these data highlight how crucial it is to address fatigue in training and recovery plans.

Biometric recognition and analysis of sports teaching behavior based on wearable devices

Hui Ma — 2025-01-16

This study introduces a lightweight, multi-node IMU-based motion capture system optimized for biomechanical analysis, addressing limitations of traditional optical systems and challenges in sensor drift and noise. Multi-node IMU systems offer distinct advantages in biomechanical analysis, such as portability, affordability, and the ability to capture motion data in real-world environments, making them particularly suited for applications in gait analysis, sports performance, and rehabilitation. Enhanced calibration techniques correct biases in accelerometers, gyroscopes, and magnetometers, while an optimized Madgwick algorithm ensures accurate, real-time motion tracking. The system’s scalable design, supported by high-throughput USB 3.0 communication, enables precise capture of human motion. Experimental validation confirms the system’s affordability, robustness, and suitability for biomechanics, offering a practical and effective tool for advancing human movement research.

Biosensing technology based on biomechanics in psycho analysis: Improving the efficiency of ideological and political education

Donghong Lei — 2025-01-17

In recent years, advancements in technology have significantly transformed educational paradigms, particularly through the integration of biomechanics in teaching methodologies. The incorporation of biomechanical analysis in educational settings provides valuable insights into students' physical engagement and motor skills development. This study aims to leverage biomechanical data to enhance the effectiveness of physical education and sports training. Biomechanical sensors, such as motion capture systems and wearable devices, collect critical data on parameters like gait, balance, and muscle activity. By analyzing this data, educators can gain a deeper understanding of students' physical performance and identify areas for improvement. We propose a novel biomechanical optimization framework utilizing a multi-kernel support vector machine (MK-SVM) to assess students' physical strain levels during activities. In the preprocessing stage, a median filter is employed to eliminate noise from the motion data. Features are extracted using power spectral density (PSD) analysis to evaluate students' physical responses during instructional activities. The proposed method utilizes algorithms to create personalized training environments, identifying physical responses and facilitating real-time feedback for enhanced engagement in sports and physical education. The MK-SVM algorithm is applied for feature selection, effectively categorizing student strain levels to refine personalized learning strategies. Results indicate that our approach outperforms traditional methods, achieving high accuracy (92%), Recall (98%), precision (80%), and F1-Score (88%) in assessing students' physical strain. This study demonstrates how biomechanics and technology can revolutionize physical education, fostering more adaptive and responsive learning environments.

The biomechanical influence of Qianlong health maintenance movement on the mental health of the elderly people

Li-Jun Wang — 2025-01-17

Purpose: As mental health issues among the aging population become increasingly prevalent, effective interventions that incorporate physical movement are essential. To explore the influence of Qianlong health exercise on the mental health of the elderly people, emphasizing the biomechanical aspects of physical activity. Methods: A general situation questionnaire and the SCL-90 were used to measure the psychological status of 627 elderly people. Results: There were significant differences in the dimensions of somatization, obsessive symptoms, interpersonal sensitivity, depression, anxiety, hostility, terror, paranoia, psychosis, sleep diet and total score, especially in the dimensions of interpersonal sensitivity, depression, anxiety, paranoia and psychosis. Furthermore, the study identified significant variations in the length, frequency, and forms of Qianlong health exercise practiced by participants, indicating that these factors may play a critical role in influencing mental health outcomes. The biomechanical properties of Qianlong health exercise, characterized by controlled movements that enhance balance, coordination, and flexibility, may contribute to improved psychological well-being by reducing stress and promoting relaxation. Conclusion: Qianlong health exercise represents an effective intervention for enhancing mental health among the elderly, integrating physical activity with psychological benefits. Future research should focus on the specific biomechanical mechanisms that mediate these effects and explore how such exercises can be incorporated into comprehensive health promotion strategies for the aging population. This approach not only addresses physical fitness but also fosters mental resilience, making it a valuable addition to geriatric health programs.

Kinetic elements and brushstroke dynamics in painting through the lens of biomechanics

Zhenpeng Zhao — 2025-01-17

This study explores the biomechanics of brushstroke dynamics in painting, focusing on the physical demands of different brushstroke types and their underlying kinetic elements. Through an experimental method combining motion capture, force sensors, and electromyography, we analyzed the joint angles, Muscle Activation (MA) patterns, and force application across four brushstroke types: broad strokes, fine detail, stippling, and circular motions. Key findings revealed that broad strokes required the most extensive range of motion, with shoulder and elbow joint angles averaging 45°–60° and 30°–40°, respectively, reflecting the involvement of larger muscle groups in creating expansive movements. Fine detail strokes, in contrast, relied predominantly on wrist flexion and extension (15°–20°), necessitating greater precision and stability from distal muscles. Force analysis showed that stippling generated the highest mean force (10.2 N) due to repetitive dabbing motions, whereas fine detail strokes exhibited minimal force variability, indicating controlled, delicate muscle engagement. Electromyography data indicated peak MA in the extensor carpi radialis and flexor carpi radialis during fine and circular strokes, highlighting the unique demands of rotational and fine motor control in painting. These findings underscore the complex interplay of movement, force, and MA required for different painting techniques, contributing valuable insights for optimizing technique and preventing repetitive strain in artists. This research provides a foundational biomechanical understanding of brushstroke execution, with implications for art education, rehabilitation, and ergonomic interventions in the arts.

The diagnostic value of carotid ultrasound in stroke prevention: Cellular molecular biomechanics-anchored exploration of current applications and future trails

Min Zhang — 2025-01-17

Stroke continues to be a major public health concern involving high morbidity and mortality in most parts of the world with far reaching economic impact. About two thirds of these cases are caused by ischemic strokes that are linked to carotid artery disease. Identifying high-risk stroke patients is crucial for initiating appropriate management. At the cellular molecular biomechanics level, the carotid artery’s endothelial cells experience shear stress. Changes in blood flow patterns can disrupt the mechanotransduction pathways within these cells. Ideally, high risk stroke patients should first be identified for proper management to be begins. Carotid artery disease or carotid stenosis and plaque formation is one of the major and modifiable risk factors for ischemic stroke, thereby the importance of accurate diagnostic assessment cannot be overstressed. The current uses, accuracy, and future developments of carotid ultrasound as a diagnostic tool for stroke prevention are discussed in this paper. Carotid ultrasound that is noninvasive and relatively inexpensive is a central tool in evaluating the degree of stenosis and plaque features that are vital in risk of stroke. It can detect alterations in the intima-media thickness, which reflects changes in the cellular and extracellular matrix composition of the artery wall. The biomechanical properties of plaques, such as their stiffness and vulnerability, can also be inferred. In the review, difficulties in stroke risk detection and features of carotid ultrasound that were outlined include its effectiveness in identifying stroke risk, in comparison with other imaging techniques, the incorporation of carotid ultrasound into clinical practice for early strokes detection. New developments such as carotid elastography and imaging with the help of artificial intelligence algorithms are also presented to exemplify the increasing possibilities of enhancing diagnostic accuracy. The primary value of carotid ultrasound is in stroke prevention because it offers a preliminary and precise means of diagnosing carotid artery disease. However, further studies are needed to explore additional applications, enhance diagnostic precision, and develop more effective preventive healthcare strategies, taking into account the cellular molecular biomechanics of the carotid artery and its associated pathologies.

Enhancing college students physical education using artificial intelligence-optimized teaching system based on biomechanics

Zixuan Gao — 2025-01-17

Physical Education Teaching concerns the process of leading students to perform different tasks, games, and workouts that improve physical fitness, body control, and health. In the realm of cell and molecular biomechanics, physical education teaching can be regarded as a means to induce specific physiological responses at the microscopic level. The various physical activities in which students partake, like diverse tasks and workouts, exert mechanical forces that permeate throughout the body and impinge upon cells and tissues. During physical exertion, cells within muscles, bones, and connective tissues are subject to biomechanical stress. This stress triggers a cascade of molecular events. Teachers focus on enhancing spatial and manual skills, promoting cooperation, and setting up priorities. In this research, it is proposed to learn about the teaching system of physical education in colleges and universities using artificial intelligence (AI) optimization algorithm. Thus, for predicting the achievements of college students in physical education, we propose the Blue Monkey optimization-driven Weight-Tuned AdaBoost (BM-WTAdaBoost) algorithm. The observations and variables were derived from typical physical education programs of college students during their training sessions. A data pre-processing technique known as min–max normalization is applied to the obtained raw data to enhance its quality. For nonlinear data, Kernel Principal Component Analysis (kernel-PCA) is employed as it helps in extracting the nonlinear information, which in turn helps in making accurate predictions. The following is our proposed model: BM opt with WTAdaBoost to improve selecting features and model accuracy in predicting college students’ physical education outcomes. Python program uses our suggested technique. The finding assessment phase assesses the suggested model’s prediction efficacy using several measures, including the accuracy ratio (99.8%), F1-score (95.56%), prediction ratio (98.24%), interaction ratio (97.2%), efficiency ratio (98.24%), performance ratio (97.2%), and error rate (5.62%). We also performed a comparative analysis with different traditional approaches to assess the efficacy of the suggested strategy. Comparative analysis with traditional methods shows the superiority of this approach in predicting physical education outcomes considering cell and molecular biomechanics, providing a novel perspective for understanding and optimizing physical education in relation to the microscopic biological world.

Research on biomechanics-informed rural planning strategies for enhancing biodiversity and health

Xiuli Yang — 2025-01-17

Rapid urbanization has resulted in decreased biodiversity, adversely impacting ecosystem functions and human health, especially in rural regions. Biomechanics-informed rural planning integrates principles of biological mechanics with biodiversity enhancement and public health objectives to establish sustainable communities. Purpose: This study aims to foster resilient ecosystems and healthier rural populations by introducing biomechanics-informed approaches to rural planning that synergize biodiversity enhancement with health promotion. Methods: This study bridges the knowledge gap by examining the relationship among biomechanically efficient behaviors, personal health, and ecosystem-based disaster risk reduction (EDRR) through the lens of the Health Belief Model (HBM). Structural equation modeling (SEM) was employed to investigate the correlations between the study's key variables. The research focused on a rural community impacted by disaster to test the hypotheses, exploring biomechanics-informed rural planning strategies that facilitate sustainable development and biodiversity enhancement. Results: The findings indicate that health perceptions and EDRR attributes indirectly influence biomechanically efficient behaviors. Specifically, participation in activities that support biodiversity is positively associated with perceptions of social integration benefits, EDRR awareness, and health promotion. Conclusion: This study underscores the potential to integrate biomechanics into Emergency Disaster Risk Reduction (EDRR) initiatives and community planning to encourage healthy lifestyles and enhance the environmental sustainability of resilient communities.

The integration of biomechanics and the application of green materials in the construction of sports facilities under environmental sustainability

Xian Liu — 2025-01-17

With the in-depth implementation of the Scientific Outlook on Development, in order to implement the national basic energy-saving policies and various emission reduction mechanisms, as well as the demonstration and promotion role of universities in energy conservation and emission reduction, the state has put forward the idea of further supporting the construction of energy-saving campuses in higher education and universities. This paper delves into the application of green and environmentally friendly materials in the construction of sports facilities, not only from the perspective of ecological sustainable development but also in close connection with the field of biomechanics. Biomechanics plays a crucial role in the design and use of sports facilities. When applying green materials, it is essential to consider how these materials interact with the human body's mechanics during sports activities. For example, different sports demand specific mechanical properties from the facilities, such as the right amount of elasticity, friction, and shock absorption. Green materials, when selected and designed with biomechanics in mind, can enhance the performance and safety of athletes while maintaining environmental friendliness. To assess the feasibility of green materials in this context, this paper presents an evaluation method that integrates the Analytic Hierarchy Process (AHP) and information entropy. This approach incorporates biomechanical factors into the index system. By doing so, the combined weight value of each component in the system can more accurately reflect the real-world situation. Compared to traditional evaluation methods, this integrated approach effectively mitigates the subjectivity in determining weight coefficients. It also ensures that the significance of each evaluation index, especially those related to biomechanical performance, is fully considered. The experimental results in this paper show that the use of AHP to evaluate the advantages of green environmental protection materials, the average weight reaches 0.8275. This finding strongly suggests that the application of green materials in sports facilities construction is highly viable. These materials not only contribute to environmental protection but also offer biomechanical advantages, ensuring the long - term sustainability and functionality of the facilities for athletes.

Biomechanical research on the construction and optimization of youth basketball training system based on the integration of sports and education

Zechun Hu — 2025-01-17

The development and improvement of a youth basketball training program founded on the fusion of education and sports is investigated in this study. Athlete performance and academic advancement must be balanced in light of the growing need for comprehensive youth development. Biomechanical factors play a significant role in both sports performance and injury prevention, making it essential to integrate them into the training program design. To increase the effectiveness and design of training programs, the suggested model makes use of the Tabu Search Optimized Intelligent Random Forest (TSO-IRF) algorithm. The TSO-IRF identifies important physical, technical, and cognitive elements affecting basketball play by combining search-based optimization with machine learning (ML) approaches from a biomechanical perspective. It focuses on elements such as joint forces, muscle activation patterns, and movement kinematics, which are fundamental in determining an athlete's performance and injury risk. The research gathers information on youth basketball training programs, with a specific emphasis on biomechanical aspects. This includes information on players' body mechanics during different basketball movements, like jumps, shots, and passes. By integrating this data, the study ensures that the goals of educational development and sports training are aligned, while also considering the biomechanical requirements of the athletes. TSO-IRF is used to evaluate these multidimensional features and provides individualized training suggestions in line with the performance and educational objectives of both sports. Experimental results indicate that the TSO-ERF model can perform better than traditional methods, providing higher prediction recall (94.26%), accuracy (97.81%) and precision (97.21%) in development metrics for players. Additionally, the model shows improved adaptability across various skill levels as it can adjust training recommendations based on an athlete's unique biomechanical characteristics. The proposed youth basketball training system optimizes loads in training, reduces risks of injury, and develops young athletes over the long term. It facilitates athletic success but fosters cognitive and emotional development so that the fields of sport and education may converge. Future work involves the application of this model in other sports disciplines and algorithm refinement to take care of larger datasets that would help deliver real-time performance feedback.

Optimization of alpine skiing turning techniques based on biomechanics

Changfeng Li — 2025-01-17

Alpine skiing turning technique requires high coordination of movements, but the existing training methods lack in-depth analysis of biomechanical characteristics. Athletes are prone to injuries during training. Technical optimization mainly relies on summarizing experience and lacks a precise quantitative basis. This paper aims to systematically analyze and optimize alpine skiing turning techniques from a biomechanical perspective, build a scientific action model and data analysis system, realize quantitative evaluation of technical movements, improve training safety and technical level, and provide scientific guidance for athletes. The study uses motion capture equipment to record three-dimensional motion trajectories and pressure sensors to collect mechanical data. By building an analysis model based on biomechanics, key features such as joint angles and torque changes are extracted, and an optimization scheme is designed in combination with a nonlinear multi-objective optimization algorithm. Based on these models and algorithms, a real-time feedback system is developed to provide personalized training suggestions to support athletes in adjusting movements and improving their technical level. The experimental results show that compared with the traditional training method, the coordination and balance of the optimized training model are improved by about 23.6% and 13.6% respectively, the action efficiency is improved by about 26.9%, and the risk of injury is reduced by more than 20%. In addition, the results of the model generalization ability test also show that the optimized training method has the characteristics of adapting to different groups. This shows that the optimized training method can significantly improve movement coordination and efficiency while reducing the risk of sports injuries, providing a new path for the scientific training of alpine skiing.

Study on dexterous structure and control of bio-inspired musculoskeletal robots in artificial intelligence environment

Qiyuan Wang — 2025-01-17

The design and development process of bio-inspired musculoskeletal robots in the artificial intelligence environment integrates mechanical design, control algorithms, real-time computing, variable sensing, and other fields of technology, which can provide effective mechanical support for the user’s actions in the process of use, and has a broader application prospect in a number of fields. In the process of exoskeleton robots moving from experimental research and development to practical applications, the comfort of the use process is an important evaluation criterion. Therefore, from the perspective of user comfort, this paper takes the waist exoskeleton robot as the research object, and conducts a design study on the structure and control of the exoskeleton robot.

Application of virtual reality in e-commerce: Taking the experience of trying on sports equipment as an example

Lin Gan — 2025-01-17

Traditional e-commerce platforms have the problem that users cannot try on sports equipment in person, and it is difficult for consumers to perceive its size, comfort and dynamic performance before purchasing. This limitation leads to high return rates and difficult purchasing decisions. This paper introduces a virtual try-on solution with higher accuracy and more immersion. After using 3D scanning technology to obtain the user’s body data and combining it with SMPL (Skinned Multi-Person Linear Model) to generate the user’s body model, a posture optimization algorithm is used to adjust the dynamic posture of the user model and the PoseNet optimization model is used to adapt it to the user’s dynamic motion scenes. Next, Unity Physics is used to achieve the dynamic performance of sports equipment materials, high-definition texture mapping technology is used to reproduce the visual effects of equipment materials to ensure that the appearance is consistent with reality, and sports scenes are constructed to simulate the actual performance of equipment in different environments. Users can use motion capture devices to simulate running, jumping and other movements to feel the suitability of sports equipment. Then, based on the user’s body shape data and sports scene preferences, Deep Q-Learning is used to recommend sports equipment options suitable for the user. Finally, the system adjusts the virtual try-on experience in real time, showing a variety of combination effects, helping users quickly find their favorite products. Experiments show that the performance error between virtual equipment and real equipment is only 1.35%, the virtual try-on pass rate exceeds 90%, and the return rate is less than 10%, which verifies the feasibility of virtual reality technology in e-commerce and improves users’ online shopping experience.

New paths to promote athletic injury prevention by integrating statistics and sports biomechanics

Yiming Zhao — 2025-01-17

Athletic injuries are a common problem in sports. Due to the insufficient processing of multimodal biomechanical data by traditional prevention strategies, personalized risk prediction cannot be achieved. To this end, this paper adopts an athletic injury prevention method based on sparse principal component analysis (SPCA) and spatio-temporal graph convolutional network (ST-GCN). The Vicon Vantage V5 3D motion capture system and the Noraxon Ultium EMG electromyography acquisition device are used to obtain the athlete’s joint angle change rate, ground reaction force (GRF) and electromyographic activity data, and the SPCA method is used to extract key biomechanical features, thereby reducing data redundancy and improving the representativeness of features. Subsequently, ST-GCN is used to construct a dynamic risk prediction model to capture the temporal changes and spatial dependencies in the motion sequence to achieve precise and efficient risk assessment. In the experimental verification, the prediction accuracy of the model reaches 95.3% when the number of features was 20, and the ability to provide risk feedback in real-time is realized to generate personalized injury prevention strategies. Studies have shown that the integration of statistics and sports biomechanics has effectively improved the efficiency of athletic injury prevention and provided new ideas for scientific and precise sports management.

A study on the application of machine learning algorithms incorporating biomechanical principles in optimising the health status assessment of electric vehicle power batteries

Jiyuan Zhang — 2025-01-17

This study addresses the problem of power battery health state assessment for electric vehicles, integrating biomechanical principles and machine learning algorithms to investigate the health state assessment accuracy of different types of power batteries under different working conditions. The study adopts a variety of data-driven methods to deeply analyse the performance degradation law of power batteries. The results show that the machine learning algorithm incorporating biomechanical principles can effectively improve the accuracy of power battery health state assessment, especially under complex working conditions, and exhibits better robustness. The current status of power battery health state assessment technology is reported, and it provides a useful reference for future power battery health management in electric vehicles.

Algorithms for digital cultural tourism ecological model with biomechanical considerations in VR scene interactions

Jing Peng — 2025-01-17

Digital cultural tourism is an emerging form of tourism that presents cultural heritage and tourism resources digitally to users, providing immersive travel experiences. However, traditional methods of constructing virtual scenes often rely on manual modeling, leading to low efficiency and high costs. The existing digital cultural tourism platforms mostly provide static and pre-set content, lacking interaction with users, making it difficult to achieve personalized recommendations and interactive experiences. In response to these issues, this article is based on VR (Virtual Reality) scene intelligent generation and interactive algorithms, and aims to optimize the overall synergy between the presentation of cultural resources and user experience by constructing a digital cultural tourism ecological model. Drawing on biomechanical principles, the study emphasizes the importance of natural user interactions and physical engagement in enhancing the immersive experience. Firstly, the Lindenmayer system (L-system) and parameterized generation rules are used to generate complex natural landscapes and architectural structures. Natural and textured scene details are added using the Perlin noise algorithm. Using GANs (Generative Adversarial Networks) technology, generative and discriminative networks are trained to generate more realistic VR scenes, further enhancing the realism and detail representation of the scenes. At the same time, a gesture recognition technology combining CNN (Convolutional Neural Network) and LSTM (Long Short-Term Memory) models, along with a speech recognition algorithm based on DNN (Deep Neural Networks), is adopted to enhance the natural interaction between users and virtual scenes. By combining collaborative filtering algorithms with user behavior data, personalized content recommendations are realized, enhancing user engagement and satisfaction. The efficiency test of scene modeling, the total time required to generate scenes using the model in this article is only 84 hours, which is much lower than manual modeling. In the interactive test, the highest success rate of the model in this article in gesture recognition reaches 94%. The experimental results have verified the advantages of the model in this article in improving scene modeling efficiency and enhancing immersive experiences through biomechanically informed interactions.

Applications and challenges of artificial intelligence-driven 3D vision in biomedical engineering: A biomechanics perspective

Lei Wang — 2025-01-20

This paper explores the applications and challenges of artificial intelligence (AI)-driven 3D vision technology in biomedical engineering, with a specific focus on its integration with biomechanics. 3D vision technology offers richer spatial information compared to traditional 2D imaging and is increasingly applied in fields like medical image analysis, surgical navigation, lesion detection, and biomechanics. In biomechanics, AI-driven 3D vision is used for analyzing human movement, modeling musculoskeletal systems, and assessing joint biomechanics. However, challenges persist, including image quality, computational resource demands, data privacy, and algorithmic bias. This paper reviews the development of 3D vision technology and AI, discusses its applications in biomedicine and biomechanics, and addresses the key technical obstacles, offering insights into the future development of these technologies in the context of biomedical and biomechanical research.

A biomechanics-oriented study on the impact of AIGC on user interaction and ergonomics in visual communication design

Yiwen Chen — 2025-01-20

This study investigates the biomechanical implications and ergonomic impacts of AI-generated content (AIGC) integration in visual communication design workflows. Through a comprehensive analysis of 23 professional designers in Chengdu, China, we examined the physical stress patterns, user interaction dynamics, and overall ergonomic outcomes when transitioning from traditional to AIGC-assisted design processes. The research employed a mixed-method approach combining quantitative biomechanical measurements with qualitative user experience assessments over 12 weeks. Results revealed significant reductions in muscle activity across key muscle groups, with the upper trapezius showing the most significant decrease (−3.6% MVC, p < 0.001) during AIGC-assisted tasks. This change in muscle activity can be further linked to alterations in the body's postural stability and load distribution, which are core considerations in biomechanics. Movement efficiency metrics, which are inherently related to biomechanical performance, demonstrated a 27.9% reduction in task completion time (p < 0.001) and a 33.3% decrease in design iterations. Quality assessment scores improved across all dimensions, with Creative Innovation showing the highest enhancement (+1.8 points, p < 0.001). User satisfaction metrics indicated significant improvements, with consistent gains of 1.1 points (on a 5-point scale) across all measured dimensions (p < 0.001). Notably, the study identified distinct adaptation patterns between novice and experienced users in terms of their biomechanical responses. Experienced users demonstrated significantly faster response times in AIGC prompt input (8.94 ± 1.87 s vs 18.62 ± 3.15 s, p < 0.001), which can be associated with differences in their neuromuscular coordination and motor learning abilities. While AIGC integration initially increased certain types of errors (+51.2% in input errors), it led to substantial reductions in tool misuse (−40.4%) and design revisions (−39.9%). These findings suggest that AIGC integration can significantly reduce physical stress while improving design efficiency and quality outcomes, all of which are intertwined with the biomechanical functioning of the body during the design process. The research provides evidence-based recommendations for optimizing AIGC implementation in professional design workflows, taking into account the biomechanical and ergonomic factors that contribute to the overall well-being and creative productivity. This study has important implications for software development, workplace health policies, and the future direction of AI-assisted creative work, as it highlights the significance of considering biomechanics in the integration of advanced technologies within creative domains.

Innovative design and implementation path of biomechanical elements in intelligent landscapes

Delin Zeng — 2025-01-20

With the acceleration of urbanization and rapid development of intelligent technologies, incorporating biomechanical elements into intelligent landscape design has become a crucial approach to enhancing urban landscape quality. This research conducts a systematic study on the innovative design and implementation approaches of biomechanical elements in intelligent landscapes, proposing a “Bio-Intelligence-Environment” trinity design principle system and developing new intelligent composite materials and biomimetic multi-level structural design methods. Experimental testing demonstrates that the developed intelligent composite materials achieve a tensile strength of 576 MPa, a 32.5% improvement over traditional materials, with intelligent response sensitivity increased by 45.3%. Through biomimetic multi-level structural design, component weight is reduced by 18.5% while bearing capacity increases by 22.3%, achieving a static load capacity of 2850 N/m². The intelligent control system reaches a recognition accuracy of 98.7%, an improvement of 15.4 percentage points over traditional systems, with control precision reaching ± 0.08 mm. Environmental adaptability tests show that the system maintains stable operation within a temperature range of −25 ℃ to 65 ℃, with performance degradation not exceeding 5.8%, and relative humidity adaptation ranging from 20% to 95%. Field application data indicates a system stability rate of 99.3%, with an average fault-free operation time of 8500 h and annual operation and maintenance costs accounting for 3.2% of initial investment, a 45% reduction compared to traditional systems. User experience evaluation shows an overall satisfaction score of 92.3, with intelligent interaction satisfaction reaching 95.2%. Economic benefit analysis reveals that mass production reduces single system cost to 325,000 yuan, with a 2.8-year investment recovery period and an internal rate of return of 24.5%.

Research on the structural design of exoskeleton assisted transport robot combined with reinforcement learning algorithm under the background of artificial intelligence

Zhongnan Liu — 2025-01-21

With the comprehensive interface between “Made in China 2025” and Industry 4.0, the handling mode of the handling system is constantly updated and developed, and a new type of handling mode, which is assisted by exoskeleton and other equipments to complete the handling work of workers, has been gradually applied. However, most of the existing exoskeleton-assisted robots are expensive and complicated in structure, which are not applicable to the actual needs of ordinary workers. Therefore, it is of great significance to design an exoskeleton-assisted handling robot that is applicable to the needs of ordinary workers. Based on this, this paper designs a relatively simple structure and low cost exoskeleton-assisted handling robot, and introduces the BN-Q-learning algorithm to give the control strategy of the robot, and finally simulates and analyzes the reliability of the handling robot, and the results show that the exoskeleton-assisted handling robot designed in this paper has a high reliability, and the force situation and the human body’s joints are relatively well matched when handling heavy objects. The results show that the exoskeleton assisted handling robot designed in this paper is highly reliable, and the force situation when handling heavy objects matches the human body joints.

Analyzing biomechanical force characteristics in sports performance monitoring using biochemical sensors and internet of things devices

Jing Liang — 2025-01-21

This study explores the application of Internet of Things (IoT) devices and biochemical sensors in sports performance monitoring, focusing on the biomechanical force characteristics of athletes to address limitations in traditional methods, such as limited data types, poor real-time accuracy, and insufficient visualization. Emphasizing mechanobiological principles, the analysis targets key force-producing regions of the body—such as the feet, legs, and torso—to optimize energy efficiency, motion precision, and overall athletic performance. Biochemical sensors were employed to monitor real-time biomechanical and physiological data, while IoT devices ensured accurate data transmission, visualization, and feedback. Data accuracy was enhanced through methods such as zero correction, timestamp synchronization, and Kalman filtering, while data transmission efficiency was optimized using a lossless compression algorithm, hierarchical structuring, the MQTT protocol, and encryption via the AES algorithm. Data organization utilized a star-structured MySQL database with composite indexing for swift access. Analytical tools such as the Apriori algorithm for data correlation, linear discriminant analysis for feature extraction, and multi-source data fusion enabled detailed visualization of performance metrics. Experimental applications in football and sprinting demonstrated the effectiveness of IoT-based monitoring. Football experiments captured multi-dimensional data on technical characteristics, while sprint tests recorded precise performance metrics, including real-time speed profiling and timing accuracy. For instance, in a 100-meter sprint test, an IoT system measured an athlete's performance at 12.54 seconds with 100% accuracy, surpassing manual timing methods. These findings highlight the transformative potential of IoT devices and biochemical sensors in sports analytics, offering enhanced accuracy, real-time tracking, and actionable insights to refine athletic performance and decision-making.

The relationship between the quality of sports facilities and people’s satisfaction with exercise—The chain mediating effect of active participation and self-efficacy in the context of biomechanics

Liping Wang — 2025-01-21

In order to explore the relationship between active participation and self-efficacy in the quality of sports facilities and exercise satisfaction, this study takes into account the perspective of biomechanics. A survey was conducted among 361 urban residents aged 16 and above in Yongzhou City. The “Sports Facilities Quality Scale”, “Active Participation Scale”, “Self-Efficacy Scale”, and “Exercise Satisfaction Scale” were utilized, with an added consideration of biomechanical factors. Biomechanics, which examines the mechanical aspects of human movement during exercise, provides a crucial framework for understanding how sports facilities interact with the human body. High - quality sports facilities, designed in accordance with biomechanical principles, can significantly influence the physical experience of exercise. For example, the surface material and structure of a running track can affect the impact forces on joints during running, and the ergonomic design of fitness equipment can enhance the efficiency and comfort of movements. These biomechanical factors directly impact a person’s active participation in exercise. When facilities are biomechanically optimized, individuals are more likely to engage actively in physical activities, as they experience less discomfort and reduced risk of injury. The results showed that: 1) The quality of sports facilities, active participation, self-efficacy and exercise satisfaction were significantly correlated with each other. 2) Active participation played a single intermediary role between the quality of sports facilities and exercise satisfaction, accounting for 26.81% of the total effect, and self-efficacy played a single intermediary role between the quality of sports facilities and exercise satisfaction; Active participation and self-efficacy play a chain intermediary role between the quality of sports facilities and exercise satisfaction, accounting for 26.34% of the total effect. Conclusion: Considering biomechanics, the quality of sports facilities indirectly affects the exercise satisfaction of urban residents in Yongzhou City through the chain mediation of active participation and self - efficacy. In the context of national fitness, high - quality sports facilities, designed with biomechanical principles in mind, play a positive and crucial role in promoting residents’ physical exercise, as they can enhance the overall exercise experience from a biomechanical perspective.

Effects of low-level laser therapy (LLLT) on skeletal muscle fatigue and damage

Qingkun Feng — 2025-01-21

The present study aimed to evaluate the effects of low-level laser therapy (LLLT) on exercise performance and skeletal muscle damage. A randomized, double-blind, placebo-controlled study involved 24 male college swimming athletes. LLLT was administered prior to exercise using a He-Ne laser at 632.8 nm, with a power output of 5 mW, a total irradiation duration of 300 s, and an energy density of 0.3 J/cm² per diode or placebo, applied to two points on the rectus femoris muscles bilaterally. The performance in a 200-m breaststroke swim, as well as thigh and leg girth, blood lactate levels, creatine kinase (CK), and lactate dehydrogenase (LDH) levels were assessed before and immediately after the swimming protocol. The LLLT group demonstrated a significant improvement in 200-m breaststroke performance (p < 0.05) and a significant reduction in thigh circumference, blood lactate, CK, and LDH levels (p < 0.05) when compared to the placebo group. Pre-exercise photobiomodulation by LLLT improved the 200-m breaststroke swimming performance, and reduced muscle fatigue and damage.

Research on the mechanism of promoting precise poverty alleviation through educational informatization based on biomechanical mechanism

Heng Jiang — 2025-01-21

Drawing on the theory of biomechanics, this study explores the mechanism of promoting precision poverty alleviation through education informatization. Precision poverty alleviation is at the core of China’s poverty reduction strategy, addressing the root causes of poverty through targeted interventions. Under this framework, education informatization has become a key tool for bridging systemic inequalities by enhancing the quality and equity of education through information technology. From basic digital construction to the deep integration of big data, cloud computing and artificial intelligence, education informatization has made remarkable progress. Analogous to how biomechanical systems optimize force transmission and movement efficiency, it showcases great potential for the optimal distribution of educational resources, enhancing access to education in impoverished regions, and fueling long-term socio-economic progress. However, its role in rural and underdeveloped areas still faces many challenges. Viewing education informatization as a dynamic “biomechanical structure” and borrowing concepts like structural adaptation, load optimization, and connectivity from biomechanics, we posit that big data technology, acting as a “biomechanical signal”, can precisely pinpoint needy students and allocate educational resources adeptly, much like how forces are coordinated in a mechanical system. Based on the fuzzy breakpoint regression model and fixed-effects analysis of CFPS (China Family Panel Studies) data, the study finds that education informatization significantly improves the subjective well-being, health care, and employment outcomes of rural families. This study highlights the innovative role of education informatization in enhancing resilience, equity, and resource efficiency through the synergy of technological evolution and policy adaptation, providing a new perspective on precision poverty alleviation.

Exploration of the clinical significance of rapid intraoperative measurement of lymph node thyroglobulin concentration in determining lymph node metastasis of papillary thyroid carcinoma

Shiyi Zhao — 2025-01-21

Objective: This study aims to evaluate the diagnostic accuracy of thyroid globulin (Tg) detection in elution fluid for intraoperative judgment of lymph node metastasis, and to explore the potential role of biomolecular mechanical behavior in influencing the detection results. By rapidly quantifying Tg levels, the optimal cutoff value was determined, and its potential value in clinical applications was further assessed. Methods: This is a prospective study that included 65 patients with papillary thyroid carcinoma who underwent surgery at Xiangyang Central Hospital's thyroid surgery department from November 2022 to May 2023. A total of 150 cervical lymph node samples were collected. Tg levels were detected intraoperatively using colloidal gold immunochromatographic assay (FNA-TG-GICA), and results were compared with routine paraffin pathology findings. Particular attention was given to the reactivity of Tg molecules in the elution fluid. The optimal cutoff value for Tg test to judge the benign or malignant nature of lymph nodes was determined by plotting the ROC curve and calculating the AUC, to evaluate the diagnostic performance of the intraoperative Tg detection in identifying lymph node metastasis. Results: A total of 150 lymph node samples were included in this study, of which paraffin pathology verification showed 50 metastatic and 100 non-metastatic lymph nodes. The optimal cutoff value for Tg test was 77 ng/mL, with sensitivity of 94.00%, specificity of 96%, and accuracy of 95%. The AUC from the ROC curve analysis was 0.97, indicating high diagnostic accuracy. Further analysis revealed that most of the positive samples were metastatic lymph nodes, and all negative samples were non-metastatic, suggesting that the Tg test performs excellently in determining lymph node metastasis. Conclusion: Elution fluid Tg test demonstrates high accuracy in intraoperatively determining lymph node metastasis. With an optimal cutoff value of 77 ng/mL, it shows excellent sensitivity and specificity. This detection method serves as a rapid and reliable diagnostic tool, providing effective decision support for clinical practice.

Application of quantitative analysis of biomechanical data in predicting healthcare investment trends

Zhe Jiao — 2025-01-21

Traditional methods for predicting investment trends often rely on macroeconomic data, overlooking the influence of individual biomechanical characteristics on decision-making, particularly in the health and medical fields. This paper seeks to enhance the accuracy of healthcare investment trend predictions by integrating high-precision biomechanical data acquisition technology with advanced quantitative analysis methods. High-precision sensors and smart wearable devices are employed to collect individual biomechanical data, encompassing dynamic features such as sports performance, joint angles, and gait. To ensure data quality, a rigorous preprocessing procedure is implemented. Principal component analysis (PCA) is utilized for feature extraction, minimizing redundant information and isolating the most representative biomechanical features. During the data analysis phase, a hybrid model combining random forests and support vector machines (SVM) is employed to predict healthcare investment trends. Random forests are applied for feature selection and regression analysis, while SVMs address classification tasks for trend prediction. The results indicate that the proposed model achieves an accuracy and precision exceeding 0.9, with healthcare investment returns on investment (ROI) ranging from 20% to 50%. The findings underscore the potential of biomechanical data in providing valuable insights for healthcare investment trend predictions, ultimately driving innovation and progress in the industry.

Exploring the therapeutic mechanism of the Qing Palace Summer-avoiding Pearl based on network pharmacology and molecular dynamics simulation

Haotian Li — 2025-01-21

Heatstroke is a thermal injury disease resulting from excessive water and electrolyte loss, as well as impaired heat dissipation, in hot and humid conditions. Modern medicine typically focuses on physical measures for early heatstroke intervention and prevention, with drug-related research being somewhat limited in scale and scope. In Chinese contexts, heatstroke is often referred to as “Zhongshu”, encompassing symptoms like nausea, vomiting, loss of appetite, emotional fluctuations and agitation, and headaches due to elevated body temperature. Traditional Chinese medicine boasts a long history and extensive literature on treating heatstroke. The Qing Palace Summer-avoiding Pearl, a treasured medicine used by ancient Chinese royalty for “Zhongshu” treatment and prevention, is of particular interest. This study aims to explore a new approach for early heatstroke prevention and intervention using the Qing Palace Summer-avoiding Pearl. We identified the disease types associated with this medicine through disease enrichment analysis and pinpointed the most likely therapeutic targets and effective substances via network pharmacology and molecular docking techniques. Furthermore, we conducted molecular thermodynamic analyses on six target Plant Extracts (PEs) using molecular dynamics simulations, examining parameters such as Root Mean Square Displacement (RMSD), Radius of gyration (Rg), and hydrogen bonds. The results indicated that the complexes exhibited favorable binding performance, which may facilitate further research on the Qing Palace Summer-avoiding Pearl.

A multimedia fugacity model for assessing the environmental fate of typical antibiotics in Lake Taihu with emphasis on the biomechanical characteristics of drug delivery systems

Runwu Zhou — 2025-01-21

The extensive use of antibiotics in the Taihu Lake Basin has led to a significant threat to human and environmental health. In this context, the QWASI model is developed to simulate the fate of typical antibiotics in Lake Taihu. Through this model, real-time tracking of the dynamic changes in antibiotic content is possible. The study primarily focuses on evaluating the fate and transfer of antibiotics in the water and sediment phases of the lake. The model results indicate that most of the simulated concentrations and mass fluxes are within the same order of magnitude as the measured values, demonstrating a good simulation effect. However, an underestimation of the simulated output value occurs in some cases. The sediment layer serves as the main accumulation site for antibiotics, and the mass balance equation is a crucial tool for simulating the environmental distribution of antibiotics. Sulfamethoxazole (SMX) exhibits a relatively high concentration in water due to its large model input. The sensitivity analysis reveals that for ATM, SMX, and OFX, the five input parameters with the most significant impact are the half-life in water, sediment-water partition coefficient, sediment solids concentration, sediment particle density, and sediment-water diffusion MTC. For OTC, the impact of lake water depth is more prominent than the sediment-water mass transfer rate. The uncertainty analysis effectively showcases the model’s stability, with the water phase concentration showing better stability. In this process, each factor is assigned a correlation coefficient to represent its influence on the original content. The sediment phase antibiotic concentration has a relatively high uncertainty. The source intensity assessment in this study utilizes direct monitoring data of the Taihu Lake water body, ensuring higher accuracy. The major factor contributing to prediction errors is the ambiguity of the sediment phase, which is affected by numerous environmental factors. Importantly, when considering the fate of antibiotics in the lake, the biomechanical characteristics of potential drug delivery systems play a vital role. The movement and dispersion of antibiotics within the water and sediment are influenced by biomechanical forces. In the sediment, the porosity and permeability, which are related to biomechanical properties, can determine the rate at which antibiotics penetrate and accumulate. Understanding these biomechanical aspects of drug delivery systems can help in devising more effective strategies for antibiotic remediation. It can also provide insights into how the physical environment interacts with the chemical behavior of antibiotics, ultimately contributing to a more comprehensive understanding of the environmental fate of antibiotics in Lake Taihu. This is the first study to explore the fate of antibiotics in Lake Taihu and offers valuable recommendations for the restoration of antibiotic-contaminated lakes. It enriches the research perspectives on water management, especially in relation to addressing water pollution caused by antibiotic abuse.

Postural mechanics and artistic control in painting: Investigating the role of movement in artistic creation

Chunlan Shen — 2025-01-21

Postural mechanics and movement control play fundamental roles in artistic creation, particularly in painting, where precision and fluidity of motion directly influence artistic outcomes. This study investigated the biomechanical relationships between posture, movement, and artistic control in painting practice through a comprehensive analysis of 38 artists (22 Female, 16 Male) ranging from novice to expert-level practitioners in traditional Chinese and contemporary painting techniques. Using an integrated measurement approach combining Motion Capture System (MCS) (Vicon Motion System), electromyography (EMG), and force plate analysis, we examined postural dynamics, movement patterns, and their effects on artistic precision across varied painting conditions. Results revealed significant correlations between postural stability and painting precision (r = 0.82, p < 0.001), with experienced artists demonstrating superior postural control strategies compared to novices. Analysis of seated versus standing positions showed distinct advantages in stability metrics (88.5 ± 4.2 vs. 82.3 ± 5.6 stability index, p < 0.01), though standing positions offered a more excellent range of motion (58.7 cm ± 7.2 cm vs. 42.3 cm ± 5.6 cm brush reach, p < 0.001). Environmental factors, particularly easel configuration and lighting conditions, significantly impacted performance, with optimal easel height (90%–105% of eye level) correlating with enhanced precision scores (improvement of 18.4 ± 4.2%, p < 0.001). Tool selection analysis demonstrated that medium-length brushes (20 cm–30 cm) provided optimal comfort (8.7 ± 0.9 out of 10) and precision (88.6 ± 3.8 out of 100) scores. Extended painting sessions revealed progressive changes in muscle activation patterns, with expert artists maintaining more consistent movement patterns despite fatigue (8.4 ± 1.2% vs. 18.7 ± 3.2% movement variability, p < 0.001). These findings provide quantitative evidence for the importance of proper postural mechanics in artistic creation and offer practical insights for optimizing painting performance through improved biomechanical awareness and environmental setup.

Application of biomechanics in graphic design and ergonomic optimization

Wei Wei — 2025-01-21

For patients recovering from spinal diseases, ordinary seats often lack support and correction functions, which can easily lead to problems such as spinal curvature and lumbar disc herniation. The study uses MediaPipe to recognize postures and perform 3D graphics modeling, combined with finite element analysis to simulate the coordinated work of the patient’s muscles, bones, and joints, and optimize the design of ergonomic orthosis. First, MediaPipe Pose is used for posture recognition to capture the key point coordinates of the spine and joint positions and obtain dynamic data of the patient’s sitting posture. Next, a 3D model of the patient’s skeleton and spine is built, and the bone structure is generated based on the posture data and refined with ZBrush. Then, a finite element analysis is performed using ANSYS Workbench, and the stress distribution of the spine under the patient’s weight and different sitting pressures is simulated. The orthopedic seat’s geometry and support area distribution are optimized, and adjustment functions are added to improve adaptability. The data results show that the MSE (Mean Square Error) of the optimized spinal curve deviation is only 0.0009; the maximum stress of the intervertebral disc is reduced from 56.1 MPa to 42.4 MPa; the area of the high-stress area is reduced to 12.4cm²; the stress uniformity is improved by 28.1%; the local pressure is reduced by 24.6%. The designed method can significantly reduce the patient’s spinal deviation rate, relieve seat pressure, and have a good rehabilitation auxiliary effect.

Development of personalized physical education teaching plan: Research on evaluating students’ physical fitness and sports adaptability using biosensors

Le Wang — 2025-01-21

Physical education plays an essential role in the growth of students’ overall health, fitness, and well-being. Wearable biosensors revolutionize physical performance monitoring by providing real-time data on physiological parameters, providing valuable insights into students’ fitness and flexibility during physical activities. The research aims to develop an approach for assessing students’ athletic adaptation and physical fitness using biosensors. Traditional monitoring systems have complexity in managing the huge volumes of data collected from several sensors because of noise and ambiguity. These research difficulties are addressed with the help of a deep learning (DL) based assessment model, which monitors students’ fitness using biosensor data. This research proposed a novel dynamic Bumblebee mating refined deep neural networks (DBBM-RDNN) to forecast student physical fitness and sports adaptability levels using biosensors. The biosensor dataset provides different data types that capture various aspects of physical activity and fitness. The data was preprocessed using low-pass filters to remove noise from the achieved data. Principal Component Analysis (PCA) is developed to extract the features from preprocessed data. DBBM is utilized to optimize the features in sensor data and RDNN to classify or predict fitness and adaptability levels in students based on data from sensors in real time. In a comparative analysis, the research assessed various performance metrics, such as accuracy (98.05%), precision (90.9%), recall (90.1%), F1-score (88.55%), MAE (1.915) and RMSE (2.505). Experimental results indicate the proposed model achieved superior performance in predicting student physical fitness compared to other conventional algorithms. The research highlights the integration of biosensor technology with DL, which provides an accurate and dependable system for tracking students’ physical performance.

Effect analysis of functional physical fitness training based on improved genetic algorithm under functional analysis

Danxu Lu — 2025-01-21

In addition to helping athletes enhance their athletic abilities and spark their interest in sports, youth athletics amateur training can also set the groundwork for athletes’ future athletic growth. Physical training still has less than optimal results for Chinese youth, nevertheless. The physical training effect of athletes can be maximized with the aid of amateur training. We can direct the creation of the most sensible physical training plan and choose the best physical training technique in order to achieve the ideal physical training goal and realize the steady improvement of athletes’ physical fitness by focusing more on and analyzing the fundamental and unique physical training strategies. Therefore, in order to improve the scientific and state-of-the-art analysis of training effect and to provide more scientific guidance for youth physical training, this paper introduces scientific quantitative indexes and personalized customized indexes into physical training from the perspective of genetic algorithms.

Application research on mechanical assessment and training based on intelligent physical training system in the rehabilitation of athletes’ ankle injuries

Lu Zhang — 2025-01-21

As the only hinge connection between human body and the ground, ankle joint plays an important role in sports. Based on the theory of rehabilitation medicine, this paper puts forward an intelligent physical training system integrating mechanical evaluation and training functions, and applies it to the rehabilitation of athletes’ ankle injuries. The system adopts virtual reality (VR) technology, realizes active ankle rehabilitation training through high-precision sensors and advanced computer simulation technology, and provides accurate evaluation, monitoring and personalized training scheme for ankle rehabilitation. The system creates an immersive training environment for athletes by simulating real sports scenes and processes. The experimental results show that the system is excellent in training convergence speed and performance, and the error is small. Compared with the traditional algorithm, the accuracy is improved by 19.27%. The main contribution of this paper is that the intelligent physical training system integrating mechanical evaluation and training is applied to the rehabilitation of athletes’ ankle injuries, and good rehabilitation results have been achieved.

Exploring heart failure treatment via calf & inner thigh electroacupuncture from cell molecular biomechanics perspective within “Three Yin Theories” framework

Hua Yi — 2025-01-21

Object: To guide meridian external treatment based on the “Three Yin Theories” of Water Warmth, Earth Harmony, and Wood Reaching, and to observe from a cell molecular biomechanics perspective the clinical efficacy of electroacupuncture at the calf (Chuai) and inner thigh in the treatment of heart failure. This involves analyzing how the electroacupuncture might influence cellular and molecular events within cardiomyocytes and related cardiovascular tissues. Methods: Chronic heart failure patients hospitalized in general wards were selected, and the efficacy indices before and after treatment in patients, as well as the differences between groups, were comparatively observed and studied. To explore the mechanism, not only the correlation between the reduction of neuro-endocrine hormone levels and symptom improvement was analyzed through correlation studies, but also the impact on cell molecular biomechanics was investigated. This includes examining changes in the biomechanical properties of the extracellular matrix surrounding cardiomyocytes, as well as alterations in the molecular forces and interactions that govern cell adhesion and communication within the heart tissue. Results: There was a significant difference between the treatment and control groups before and after the treatment (Sig. (two-tailed) < 0.05), and the intergroup difference was not statistically significant (Sig. (two-tailed) > 0.05), failing the significance test. There was a significant positive correlation between the decrease in aldosterone and the decrease in NYHA classification scores and BNP levels; Conclusion: Electroacupuncture at the calf and inner thigh has a better therapeutic effect on heart failure and has certain clinical promotion and application value. From a cell molecular biomechanics standpoint, the treatment appears to modulate key cellular and molecular processes within the heart, potentially providing a new avenue for understanding and enhancing the treatment of heart failure.

Impact of biomechanical properties of tongue muscles on accuracy of English vowel pronunciation

Ping Zhang — 2025-01-21

Pronunciation is a complex physiological process. Traditional research usually uses static pronunciation tests and fails to observe the dynamic changes of tongue muscles during pronunciation. This paper aims to comprehensively analyze the structure and function of tongue muscles and their role in English vowel pronunciation from the perspective of tongue muscle biomechanics, and provide a systematic framework for understanding. This paper designs multiple pronunciation tasks to evaluate participants’ pronunciation accuracy and dynamic changes of tongue muscles. Through multi-modal technology, dynamic images and electromyographic signals of the tongue are synchronously acquired to analyze the precise relationship between tongue movement and muscle activity in the pronunciation of English vowels. A tongue biomechanical model is constructed based on finite element analysis and Hill model to precisely simulate the mechanical response of tongue muscle activity and tongue position changes during pronunciation. The experimental results show that there is a significant negative correlation between electromyographic activity and pronunciation quality. The closer the correlation coefficient is to −1, the higher the consistency. The tongue is positioned higher and forward during pronunciation, making it easier to control, so that the pronunciation can be more accurate with less deviation. The greater the movement and flexibility of the tongue, the better it is able to form clear vowel pronunciations. In short, the tongue muscles achieve precise control of tongue position through the coordinated action of internal and external muscles during vowel pronunciation, which is beneficial to improving pronunciation accuracy.

Study on the influence of sports participation on happiness from the perspective of biological sports resource allocation in the Yellow River Basin perspective

Haifeng Guo — 2025-01-21

The relationship between physical activity and human well-being is based on biological mechanisms, and regular exercise positively affects physiological, psychological and social health dimensions. This study explores the impact of physical activity resource allocation on residents’ well-being in the Yellow River Basin from a biological basis. Using data from CGSS2015, CGSS2017, and SSY2017, the study combines OLS multiple linear regression modeling and spatial econometrics techniques to reveal how the accessibility of fitness infrastructure, sports services, and resource distribution can enhance well-being by facilitating increased sports participation. Findings reveal significant spatial agglomeration effects, suggesting that a balanced distribution of sport resources can optimize regional health outcomes. However, differences in resource distribution prevent physical activity from yielding physiological and psychological benefits across provinces.

Research on the effect of biosensing technology on the dissemination of health information in ideological and political education

Ruirui Zhao — 2025-01-21

Biosensing technologies, which monitor physiological responses such as Heart Rate Variability (HRL), Skin Conductance Level (SCL), and Electroencephalogram (EEG) activity, offer a novel approach to enhancing the dissemination of health information in ideological and political education (IPE). In this context, health information encompasses topics such as mental health, stress management, and healthy lifestyle practices, all crucial to students’ overall well-being. Traditional health education methods cannot often capture real-time physiological and emotional responses, which can improve engagement and learning outcomes. This research explores the effectiveness of biosensing technology in enhancing the dissemination of health information within IPE. It examines how physiological data can be utilized to assess student engagement, emotional responses, and learning outcomes related to health. A mixed-methods approach was adopted, combining quantitative data from wearable biosensors (heart rate monitors, Galvanic Skin Response (GSR) sensors, EEG headsets) with qualitative feedback from students. Physiological data were preprocessed using signal filtering techniques, such as the Savitzky-Golay Filter, and features such as heart rate variability, skin conductance, and EEG alpha waves were extracted using the Kalman Filter (KF). A Modified Runge-Kutta Optimizer Integrated with Deep Belief Networks (MRKO-DBN) classifier was employed to predict student engagement based on these features. The research revealed that physiological responses, particularly heart rate variability and skin conductance, were strongly correlated with student engagement. The MRKO-DBN model achieved accuracy in predicting engagement. Qualitative feedback further confirmed that Biosensing technology significantly improved students’ engagement. Integrating Biosensing technology into health education within ideological and political contexts offers significant potential for enhancing student engagement and learning outcomes. By providing real-time, personalized feedback, it fosters a more interactive and responsive learning environment.

Integrating ecological philosophy into ideological and political education in universities: Bridging with biomechanics for sustainable development and human health considerations

Qin Zhang — 2025-01-22

The ideological and political education (IPE) ecosystem in universities is not only an essential component of the broader educational ecosystem but also a microcosm of it. In an era that emphasizes ecology and sustainability, integrating the concepts of the biomechanics field into the ecological environment of IPE in universities holds significant practical implications. Biomechanics, a discipline dedicated to studying the mechanical behavior of organisms, has a profound impact on aspects such as the ecological environment and human health. From the perspective of ecological philosophy, the ecological environment of IPE in universities should fully consider the sustainable development of biomechanical technologies and their influence on human health. This paper presents a dynamic early warning system for IPE in universities based on an improved Support Vector Machine (SVM) algorithm. This system aims to optimize the IPE model and enhance educational effectiveness while incorporating concepts related to biomechanics. We have constructed an evaluation index system for the quality of IPE in universities across five dimensions: basic quality, teaching attitude, teaching method, teaching ability, and teaching effect. These indicators are evaluated through expert scoring to generate a comprehensive assessment of the teaching quality of IPE. Taking into account the close connection between human mechanical responses and the ecological environment in the field of biomechanics, during the evaluation process, we incorporate the impact of the ecological environment on the human biomechanical state (such as bone development and muscle function) into consideration. This approach guides students to establish a correct ecological view and understanding of biomechanical technologies. Model simulations and performance verifications show that the fuzzy neural network undergoes 779 training iterations, with a training target set at 0.05 and a learning rate of 0.09. This model demonstrates a strong ability to provide comprehensive dynamic early warnings for IPE in universities. It has obvious advantages in adaptability, model fitting accuracy, and processing efficiency in the face of information overload, contributing to the continuous development of IPE in universities from the integrated perspective of ecological philosophy and biomechanics.

College sports offline and online mixed teaching evaluation enhanced by biomechanics and GA-BP neural network

Xu Han — 2025-01-22

In the process of higher education reform, physical education plays a vital role in improving students’ comprehensive quality. The online hybrid teaching mode integrates the advantages of online and traditional teaching, which has been gradually applied to various teaching scenarios. However, establishing a comprehensive and effective evaluation model for hybrid teaching remains a challenge due to its complexity. This study introduces a teaching evaluation model based on the Genetic Algorithm Optimized Back Propagation (GA-BP) neural network, incorporating the principles of biomechanics to enhance the evaluation of motor skills, movement efficiency, and physical performance. By comparing the BP and GA-BP models using sample data, results demonstrate that the GA-BP model provides higher precision, offering a feasible framework for hybrid teaching quality evaluation. This integration of computational methods and biomechanical insights not only enriches the model’s applicability but also advances the evaluation of physical education quality and athletic performance.

Understanding the biomechanics of smartphone addiction: The physical and cognitive impacts of prolonged device use on college students

Qiufang Sheng — 2025-01-22

The widespread use of smartphones, particularly among college students, has raised concerns about the negative impacts of prolonged device use on physical and cognitive health. While smartphones offer many conveniences, excessive usage can lead to a range of biomechanical and psychological issues, including posture-related strain, repetitive strain injuries (RSIs), eye strain, impaired cognitive function, and elevated levels of anxiety and stress. This study aims to examine the physical and cognitive impacts of prolonged smartphone use among college students, focusing on biomechanical strain, cognitive impairments, and psychological effects. It explores the relationship between smartphone addiction and its effects on posture, musculoskeletal health, eye fatigue, focus, memory retention, and mental health. The study was conducted with a sample of 37 college students in China. Data collection involved physical assessments, including posture analysis, musculoskeletal screening, and cognitive assessments, such as focus and memory tests. Mental health was evaluated using standardized surveys for anxiety, stress, and depression. Statistical analyses were used to interpret the data, including descriptive statistics, paired t-tests, correlation analysis, and multiple regression. The results indicated a significant increase in neck tilt angle, posture discomfort, and wrist strain over the study period, with higher smartphone usage correlating with worse physical outcomes. Cognitive performance, mainly focuses and memory retention, significantly declined with increased smartphone usage. In addition, elevated levels of anxiety and stress were observed among heavy smartphone users, with a strong correlation between high smartphone usage and negative psychological effects.

Integrating sports industry development with national health promotion: A biomechanics-informed study of the healthy China strategy

Gaoyang Zhang — 2025-01-17

China’s strategic objective of promoting national health is in line with the integration of the sports business with sports promotion programs. Biomechanics, which delves into the mechanical aspects of human movement and its interaction with the surrounding environment, is a linchpin in this integration. When it comes to the construction of sports venues and sports equipment development, biomechanical principles are fundamental. For example, the selection of surface materials for tracks, courts, and fields must consider factors such as ground reaction forces, coefficient of friction, and energy dissipation. These biomechanical parameters not only influence an athlete’s performance but also play a crucial role in injury prevention. Policies promoting the development of sports venues, increasing public access to recreational facilities, and investing in community health programs remain essential for expanding sports participation and promoting fitness. Through an examination of policy frameworks, economic benefits, and social impacts, this study identifies key factors facilitating this integration. Technological advancements, such as the use of inertial measurement units (IMUs) and force-sensitive sensors in sports equipment and training facilities, enable real-time monitoring of biomechanical variables like joint angles, muscle activation, and movement velocities. Public-private collaborations can then leverage these technologies to develop innovative biomechanics-based sports products and services, making them more accessible to the general public. The findings of this study emphasize the necessity of a comprehensive strategy for sports promotion and sector expansion. This strategy should not only focus on economic gains but also aim to achieve superior health outcomes. Biomechanics-informed sports promotion allows for a more in-depth understanding of how different physical activities impact the human body’s biomechanics. This knowledge can be used to customize exercise programs according to an individual’s anthropometric and biomechanical characteristics, ensuring maximum effectiveness and safety. From a social perspective, a health-conscious society with widespread access to sports resources can significantly enhance the quality of life. By minimizing the risk of injuries through biomechanics-optimized sports facilities and equipment, individuals can engage in a more active lifestyle, leading to a reduction in healthcare costs. Moreover, as people participate in sports events, fitness challenges, and wellness campaigns, the shift in public attitudes towards fitness can strengthen social cohesion and community engagement. In conclusion, this study offers recommendations for future legislation and programs to enhance the integration of the sports sector with public health promotion. By fully integrating biomechanics into the development of the sports industry, we can ensure a substantial contribution to the “Healthy China” goals, fostering a more robust sports economy and a healthier society.