BioengineeringPub Date : 2025-02-26DOI: 10.3390/bioengineering12030235
M J Aashik Rasool, Akmalbek Abdusalomov, Alpamis Kutlimuratov, M J Akeel Ahamed, Sanjar Mirzakhalilov, Abror Shavkatovich Buriboev, Heung Seok Jeon
{"title":"PixMed-Enhancer: An Efficient Approach for Medical Image Augmentation.","authors":"M J Aashik Rasool, Akmalbek Abdusalomov, Alpamis Kutlimuratov, M J Akeel Ahamed, Sanjar Mirzakhalilov, Abror Shavkatovich Buriboev, Heung Seok Jeon","doi":"10.3390/bioengineering12030235","DOIUrl":"10.3390/bioengineering12030235","url":null,"abstract":"<p><p>AI-powered medical imaging faces persistent challenges, such as limited datasets, class imbalances, and high computational costs. To overcome these barriers, we introduce PixMed-Enhancer, a novel conditional GAN that integrates the ghost module into its encoder-a pioneering approach that achieves efficient feature extraction while significantly reducing the computational complexity without compromising the performance. Our method features a hybrid loss function, uniquely combining binary cross-entropy (BCE) and a Structural Similarity Index Measure (SSIM), to ensure pixel-level precision while enhancing the perceptual realism. Additionally, the use of conditional input masks offers unparalleled control over the generation of tumor features, marking a breakthrough in fine-grained dataset augmentation for segmentation and diagnostic tasks. Rigorous testing on diverse datasets establishes PixMed-Enhancer as a state-of-the-art solution, excelling in its realism, structural fidelity, and computational efficiency. PixMed-Enhancer establishes a robust foundation for real-world clinical applications in AI-driven medical imaging.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143728010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-24DOI: 10.3390/bioengineering12030226
Sofia Pettenuzzo, Elisa Belluzzi, Assunta Pozzuoli, Veronica Macchi, Andrea Porzionato, Rafael Boscolo-Berto, Pietro Ruggieri, Alice Berardo, Emanuele Luigi Carniel, Chiara Giulia Fontanella
{"title":"Correction: Pettenuzzo et al. Mechanical Behaviour of Plantar Adipose Tissue: From Experimental Tests to Constitutive Analysis. <i>Bioengineering</i> 2024, <i>11</i>, 42.","authors":"Sofia Pettenuzzo, Elisa Belluzzi, Assunta Pozzuoli, Veronica Macchi, Andrea Porzionato, Rafael Boscolo-Berto, Pietro Ruggieri, Alice Berardo, Emanuele Luigi Carniel, Chiara Giulia Fontanella","doi":"10.3390/bioengineering12030226","DOIUrl":"10.3390/bioengineering12030226","url":null,"abstract":"<p><p>In the original publication [...].</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-24DOI: 10.3390/bioengineering12030228
Xuhui Hu, Fengkai Guo, Zhikai Wei, Dapeng Chen, Junfa Dai, Anran Li, Senhao Zhang, Mostafa Orban, Yao Tong, Cong Hu, Baoguo Xu, Hong Zeng, Aiguo Song, Kai Guo, Hongbo Yang
{"title":"HANDSON Hand: Strategies and Approaches for Competitive Success at CYBATHLON 2024.","authors":"Xuhui Hu, Fengkai Guo, Zhikai Wei, Dapeng Chen, Junfa Dai, Anran Li, Senhao Zhang, Mostafa Orban, Yao Tong, Cong Hu, Baoguo Xu, Hong Zeng, Aiguo Song, Kai Guo, Hongbo Yang","doi":"10.3390/bioengineering12030228","DOIUrl":"10.3390/bioengineering12030228","url":null,"abstract":"<p><p>A significant number of people with disabilities rely on assistive devices, yet these technologies often face limitations, including restricted functionality, inadequate user-centered design, and a lack of standardized evaluation metrics. While upper-limb prosthetics remain a key research focus, existing commercial solutions still fall short of meeting daily reliability and usability needs, leading to high abandonment rates. CYBATHLON integrates assistive technologies into daily living tasks, driving innovation and prioritizing user needs. In CYBATHLON 2024, the HANDSON hand secured first place in the arm prosthesis race, showcasing breakthroughs in human-robot integration. This paper presents the HANDSON hand's design, core technologies, training strategies, and competition performance, offering insights for advancing multifunctional prosthetic hands to tackle real-world challenges.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939478/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-24DOI: 10.3390/bioengineering12030230
Dorottya Kocsis, Dániel Sztankovics, Liza Józsa, Afrodité Németh, Tamás Garay, Márton Bese Naszlady, Miléna Lengyel, Miklós Vecsernyés, István Antal, Anna Sebestyén, Franciska Erdő
{"title":"In Vitro Functional and Structural Evaluation of Low-Complexity Artificial Human Epidermis for 3D Tissue Engineering.","authors":"Dorottya Kocsis, Dániel Sztankovics, Liza Józsa, Afrodité Németh, Tamás Garay, Márton Bese Naszlady, Miléna Lengyel, Miklós Vecsernyés, István Antal, Anna Sebestyén, Franciska Erdő","doi":"10.3390/bioengineering12030230","DOIUrl":"10.3390/bioengineering12030230","url":null,"abstract":"<p><p>In recent times, with the need for a reduction, refinement, and replacement of in vivo animal testing, there has been an increasing demand for the use of relevant in vitro human cell systems in drug development. There is also a great demand for the replacement of skin tissue in various wounds and burns. Furthermore, human skin cell-based in vitro systems can be used to investigate the side effects (toxicity and irritation) and tissue penetration of topical preparations. In this study, exploratory experiments were performed to produce artificial epidermis using two hydrogel scaffolds, alginate and GelMA C. The amount of keratinocytes added to the matrix (10-50-100 × 10<sup>6</sup>/mL) and the duration of tissue maturation (fresh, 1-3-4 weeks) were optimized in an extensive study. The behavior and structure of the two hydrogels were functionally and morphologically assessed. The permeability order for caffeine in the tested barriers was the following: alginate > GelMA C > cellulose acetate membrane > rat skin. It was concluded that GelMA C matrix provides a more favorable environment for cell survival and tissue differentiation (as demonstrated by histology and immunohistochemistry) than alginate. The 3-week incubation and 50 × 10<sup>6</sup>/mL cell number proved to be the most beneficial in the given system. This study provides data for the first time on the multifactorial optimization of two potential skin substitutes for tissue manufacturing. In order to use these results in tissue engineering, the fabricated artificial epidermis preparations must also be optimized for biocompatibility and from physical and mechanical point of views.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939566/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-24DOI: 10.3390/bioengineering12030227
Quincy A Hathaway, Naveena Yanamala, TaraChandra Narumanchi, Janani Narumanchi
{"title":"Bringing Precision to Pediatric Care: Explainable AI in Predicting No-Show Trends Before and During the COVID-19 Pandemic.","authors":"Quincy A Hathaway, Naveena Yanamala, TaraChandra Narumanchi, Janani Narumanchi","doi":"10.3390/bioengineering12030227","DOIUrl":"10.3390/bioengineering12030227","url":null,"abstract":"<p><p>Patient no-shows significantly disrupt pediatric healthcare delivery, highlighting the necessity for precise predictive models, especially during the dynamic shifts caused by the SARS-CoV-2 pandemic. In outpatient settings, these no-shows result in medical resource underutilization, increased healthcare costs, reduced access to care, and decreased clinic efficiency and increased provider workload. The objective is to develop a predictive model for patient no-shows using data-driven techniques. We analyzed five years of historical data retrieved from both a scheduling system and electronic health records from a general pediatrics clinic within the WVU Health systems. This dataset includes 209,408 visits from 2015 to 2018, 82,925 visits in 2019, and 58,820 visits in 2020, spanning both the pre-pandemic and pandemic periods. The data include variables such as patient demographics, appointment details, timing, hospital characteristics, appointment types, and environmental factors. Our XGBoost model demonstrated robust predictive capabilities, notably outperforming traditional \"no-show rate\" metrics. Precision and recall metrics for all features were 0.82 and 0.88, respectively. Receiver Operator Characteristic (ROC) analysis yielded AUCs of 0.90 for all features and 0.88 for the top five predictors when evaluated on the 2019 cohort. Furthermore, model generalization across racial/ethnic groups was also observed. Evaluation on 2020 telehealth data reaffirmed model efficacy (AUC: 0.90), with consistent top predictive features. Our study presents a sophisticated predictive model for pediatric no-show rates, offering insights into nuanced factors influencing attendance behavior. The model's adaptability to evolving healthcare delivery models, including telehealth, underscores its potential for enhancing clinical practice and resource allocation.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939553/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-24DOI: 10.3390/bioengineering12030233
Penglei Fan, Youngsuk Kim, Dong-Wook Han, Sukwon Kim, Ting Wang
{"title":"Alterations in the Neuromuscular Control Mechanism of the Legs During a Post-Fatigue Landing Make the Lower Limbs More Susceptible to Injury.","authors":"Penglei Fan, Youngsuk Kim, Dong-Wook Han, Sukwon Kim, Ting Wang","doi":"10.3390/bioengineering12030233","DOIUrl":"10.3390/bioengineering12030233","url":null,"abstract":"<p><p>Fatigue causes the lower limb to land in an injury-prone state, but the underlying neuromuscular control changes remain unclear. This study aims to investigate lower limb muscle synergies during landing in basketball players, both before and after fatigue, to examine alterations in neuromuscular control strategies induced by fatigue. Eighteen male recreational basketball players performed landing tasks pre- and post-fatigue induced by 10 × 10 countermovement jumps. Electromyographic (EMG) data from eight muscles, including the erector spinae (ES), rectus abdominus (RA), gluteus maximus (GM), rectus femoris (RF), biceps femoris (BF), lateral gastrocnemius (LG), soleus (SM), and tibialis anterior (TA) muscles, were analyzed using non-negative matrix factorization to extract muscle synergies. Post-fatigue results revealed significant changes: synergy primitive 1 decreased before landing (18-30% phase) and synergy primitive 2 decreased after landing (60-100% phase). Muscle weights of the LG and SM in synergy module 2 increased. Fatigue reduced synergistic muscle activation levels, compromising joint stability and increasing knee joint loading due to greater reliance on calf muscles. These changes heighten the risk of lower limb injuries. To mitigate fatigue-induced injury risks, athletes should improve thigh muscle endurance and enhance neuromuscular control, fostering better synergy between thigh and calf muscles during fatigued conditions.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-24DOI: 10.3390/bioengineering12030232
Linda Blahová, Jozef Kostolný, Ivan Cimrák
{"title":"Neural Network-Based Mammography Analysis: Augmentation Techniques for Enhanced Cancer Diagnosis-A Review.","authors":"Linda Blahová, Jozef Kostolný, Ivan Cimrák","doi":"10.3390/bioengineering12030232","DOIUrl":"10.3390/bioengineering12030232","url":null,"abstract":"<p><p>Application of machine learning techniques in breast cancer detection has significantly advanced due to the availability of annotated mammography datasets. This paper provides a review of mammography studies using key datasets such as CBIS-DDSM, VinDr-Mammo, and CSAW-CC, which play a critical role in training classification and detection models. The analysis of the studies produces a set of data augmentation techniques in mammography, and their impact and performance improvements in detecting abnormalities in breast tissue are studied. The study discusses the challenges of dataset imbalances and presents methods to address this issue, like synthetic data generation and GAN augmentation as potential solutions. The work underscores the importance of dataset design dedicated for experiments, detailed annotations, and the usage of machine learning models and architectures in improving breast cancer screening models, with a focus on BI-RADS classification. Future directions include refining augmentation methods, addressing class imbalance, and enhancing model interpretability through tools like Grad-CAM.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939436/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-24DOI: 10.3390/bioengineering12030229
Steven M Kurtz, Steven A Rundell, Hannah Spece, Ronald V Yarbrough
{"title":"Sensitivity of Lumbar Total Joint Replacement Contact Stresses Under Misalignment Conditions-Finite Element Analysis of a Spine Wear Simulator.","authors":"Steven M Kurtz, Steven A Rundell, Hannah Spece, Ronald V Yarbrough","doi":"10.3390/bioengineering12030229","DOIUrl":"10.3390/bioengineering12030229","url":null,"abstract":"<p><p>A novel total joint replacement (TJR) that treats lumbar spine degeneration was previously assessed under Mode I and Mode IV conditions. In this study, we relied on these previous wear tests to establish a relationship between finite element model (FEM)-based bearing stresses and in vitro wear penetration maps. Our modeling effort addressed the following question of interest: Under reasonably worst-case misaligned conditions, do the lumbar total joint replacement (L-TJR) polyethylene stresses and strains remain below values associated with Mode IV impingement wear tests? The FEM was first formally verified and validated using the risk-informed credibility assessment framework established by ASME V&V 40 and FDA guidance. Then, based on criteria for unreasonable misuse outlined in the surgical technique guide, a parametric analysis of reasonably worst-case misalignment using the validated L-TJR FEM was performed. Reasonable misalignment was created by altering device positioning from the baseline condition in three scenarios: Axial Plane Convergence (20-40°), Axial Plane A-P Offset (0-4 mm), and Coronal Plane Tilt (±20°). We found that, for the scenarios considered, the contact pressures, von Mises stresses, and effective strains of the L-TJR-bearing surfaces remained consistent with Mode I (clean) conditions. Specifically, the mechanical response values fell below those determined under Mode IV (worst-case) boundary conditions, which provided the upper-bound benchmarks for the study (peak contact pressure 83.3 MPa, peak von Mises stress 32.2 MPa, and peak effective strain 42%). The L-TJR was judged to be insensitive to axial and coronal misalignment under the in vitro boundary conditions imposed by the study.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939812/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-24DOI: 10.3390/bioengineering12030231
Junjie Ma, Xucheng Zhu, Suryanarayanan Kaushik, Eman Ali, Liangliang Li, Kavitha Manickam, Ke Li, Martin A Janich
{"title":"Qualitative and Quantitative Evaluation of a Deep Learning-Based Reconstruction for Accelerated Cardiac Cine Imaging.","authors":"Junjie Ma, Xucheng Zhu, Suryanarayanan Kaushik, Eman Ali, Liangliang Li, Kavitha Manickam, Ke Li, Martin A Janich","doi":"10.3390/bioengineering12030231","DOIUrl":"10.3390/bioengineering12030231","url":null,"abstract":"<p><p>Two-dimensional (2D) cine imaging is essential in routine clinical cardiac MR (CMR) exams for assessing cardiac structure and function. Traditional cine imaging requires patients to hold their breath for extended periods and maintain consistent heartbeats for optimal image quality, which can be challenging for those with impaired breath-holding capacity or irregular heart rhythms. This study aims to systematically assess the performance of a deep learning-based reconstruction (Sonic DL Cine, GE HealthCare, Waukesha, WI, USA) for accelerated cardiac cine acquisition. Multiple retrospective experiments were designed and conducted to comprehensively evaluate the technique using data from an MR-dedicated extended cardiac torso anatomical phantom (digital phantom) and healthy volunteers on different cardiac planes. Image quality, spatiotemporal sharpness, and biventricular cardiac function were qualitatively and quantitatively compared between Sonic DL Cine-reconstructed images with various accelerations (4-fold to 12-fold) and fully sampled reference images. Both digital phantom and in vivo experiments demonstrate that Sonic DL Cine can accelerate cine acquisitions by up to 12-fold while preserving comparable SNR, contrast, and spatiotemporal sharpness to fully sampled reference images. Measurements of cardiac function metrics indicate that function measurements from Sonic DL Cine-reconstructed images align well with those from fully sampled reference images. In conclusion, this study demonstrates that Sonic DL Cine is able to reconstruct highly under-sampled (up to 12-fold acceleration) cine datasets while preserving SNR, contrast, spatiotemporal sharpness, and quantification accuracy for cardiac function measurements. It also provides a feasible approach for thoroughly evaluating the deep learning-based method.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BioengineeringPub Date : 2025-02-22DOI: 10.3390/bioengineering12030225
Liangsen Wang, Wenyue Ma, Wenfei Zhu, Lin Zhai, Yuliang Sun
{"title":"Effects of Experimentally Induced Lower Limb Muscle Fatigue on Healthy Adults' Gait: A Systematic Review.","authors":"Liangsen Wang, Wenyue Ma, Wenfei Zhu, Lin Zhai, Yuliang Sun","doi":"10.3390/bioengineering12030225","DOIUrl":"10.3390/bioengineering12030225","url":null,"abstract":"<p><p>Lower limb fatigue reduces muscle strength, alters joint biomechanics, affects gait, and increases injury risk. In addition, it is of great clinical significance to explore local muscle fatigue or weakness caused by fatigue to understand its compensatory effect on the ipsilateral or contralateral joints. We systematically searched multiple databases, including five databases, using key terms such as \"Muscle Fatigue\" and \"Gait\". Only studies that experimentally induced fatigue through sustained muscle activities in healthy adults were included. This review examined 11 studies exploring the effects of lower limb muscle fatigue on gait and lower limb biomechanics. The findings indicated that muscle fatigue significantly influenced spatiotemporal parameters, joint angles, and moments. Most studies that were reviewed reported an increase in step width and a decrease in knee joint moments following fatigue. Additionally, muscle activation levels tended to decline. In summary, compensatory mechanisms can lead to new walking strategies, such as increasing step width or enhancing the strength of muscles in adjacent joints. These adjustments impact dynamic balance differently: wider steps may enhance medial-lateral stability, while reduced muscle strength could lead to higher heel contact velocity and longer slip distances. Although these changes might influence dynamic balance, compensatory strategies may help mitigate the overall effect of fall risk. Future studies should use appropriate protocols, such as moderate or severe fatigue interventions with isokinetic dynamometry.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 3","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939146/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}