Computer Methods in Biomechanics and Biomedical Engineering最新文献_第9页

Fatigue strength analysis of a new left atrial appendage occluder at different release scales. 新型左心房阑尾封堵器在不同释放尺度下的疲劳强度分析

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-17 DOI: 10.1080/10255842.2024.2405084

Yanlong Chen,Haiquan Feng,Juan Su

{"title":"Fatigue strength analysis of a new left atrial appendage occluder at different release scales.","authors":"Yanlong Chen,Haiquan Feng,Juan Su","doi":"10.1080/10255842.2024.2405084","DOIUrl":"https://doi.org/10.1080/10255842.2024.2405084","url":null,"abstract":"Owing to its low incidence, small trauma, fast recovery, and high efficiency, left atrial appendage occlusion has become a new strategy for preventing stroke caused by atrial fibrillation. Due to a lack of relevant research information on this emerging technology, the effectiveness, stability, or related complications of occluders are mostly observed from a clinical perspective. However, there are fewer studies on the mechanical properties and safety of these occluders. In this study, a new left atrial appendage occluder is proposed, and a complete numerical simulation analysis framework is established through the finite element method to simulate the actual implantation and service process of the left atrial appendage occluder. Besides, the influence of the structural size and release scale of the occluder on its support performance, occluding effect, and safety is also explored. The results demonstrate that the structural size and release scale exert a significant impact on the support performance, occluding effect, and safety of the occluder. The structural optimization of the occluder contributes to enhancing its mechanical performance, thus ensuring its stability and effectiveness after implantation. Overall, these efforts may lay a scientific foundation for the structural optimization, safety evaluation, and effectiveness prediction of the occluder. Furthermore, these findings also provide effective reference for the application of numerical simulation technology in the research on the left atrial appendage occlusion.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142267153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint multi-feature extraction and transfer learning in motor imagery brain computer interface 运动图像脑机接口中的联合多特征提取和迁移学习

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-17 DOI: 10.1080/10255842.2024.2404541

Miao Cai, Jie Hong

引用次数: 0

The impact of toe spring and foot strike angle on forefoot running biomechanics: a finite element analysis. 脚趾弹力和脚掌击球角度对前脚掌跑步生物力学的影响：有限元分析。

IF 1.7 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-16 DOI: 10.1080/10255842.2024.2402860

Fengping Li, Dong Sun, Chengyuan Zhu, Qiaolin Zhang, Yang Song, Xuanzhen Cen, Yining Xu, Zhiyi Zheng, Yaodong Gu

{"title":"The impact of toe spring and foot strike angle on forefoot running biomechanics: a finite element analysis.","authors":"Fengping Li, Dong Sun, Chengyuan Zhu, Qiaolin Zhang, Yang Song, Xuanzhen Cen, Yining Xu, Zhiyi Zheng, Yaodong Gu","doi":"10.1080/10255842.2024.2402860","DOIUrl":"https://doi.org/10.1080/10255842.2024.2402860","url":null,"abstract":"<p><p>The surge in popularity of running has led to a multitude of designs in running shoe technology, notably, there is an increasing trend in toe spring elevation. However, the impact of this design on foot structures during running remains an essential exploration. To investigate the effects of toe spring on the foot during forefoot running, we employed finite element simulation to create two sole models with different toe spring heights (6.5 cm and 8 cm) and ground contact angles (5°, 10°, and 15°). We established and validated two foot-shoe coupling models and compared stress variations in metatarsal bones and the big toe under identical loading and environmental conditions. Higher toe spring resulted in lower peak stress and reduced stress concentration in metatarsal bones. The fourth and fifth metatarsals exhibited increasing stress trends with ground contact angle, with the fifth metatarsal experiencing the most significant stress concentration. In the case of low toe spring, stress on the fifth metatarsal increased from 15.917 MPa (5°) to 27.791 MPa (15°), indicating a rise of 11.874 MPa. Conversely, the first metatarsal showed lower stress, indicating relative safety but reduced functional significance. Moreover, higher toe spring running shoes exerted less pressure on the big toe, with an increasing trend in stress on the big toe with an increase in ground contact angle. Shoes with a higher toe spring design result in reduced pressure on the big toe. Therefore, it is advisable to avoid landing angles greater than 15° to prevent stress fractures resulting from repetitive loading.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142300059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Finite element analysis of three internal fixations for the posteromedial split fracture fragment in tibial plateau fractures 胫骨平台骨折后内侧劈裂骨折片三种内固定的有限元分析

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-16 DOI: 10.1080/10255842.2024.2399036

Wupeng Zhang, Cheng Xu, Zhengfeng Jia, Daofeng Wang, Weilu Gao, Jiantao Li, Licheng Zhang, Peifu Tang

引用次数: 0

Comment on permeability conditions in finite element simulation of bone fracture healing 关于骨骨折愈合有限元模拟中的渗透性条件的评论

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-14 DOI: 10.1080/10255842.2024.2402878

Agnieszka Sabik

引用次数: 0

A zero precision loss framework for EEG channel selection: enhancing efficiency and maintaining interpretability 用于脑电图信道选择的零精度损失框架：提高效率并保持可解释性

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-13 DOI: 10.1080/10255842.2024.2401918

Lu Wang, Junkongshuai Wang, Haolong Su, Xueze Zhang, Lihua Zhang, Xiaoyang Kang

引用次数: 0

A quasilinear hyperbolic one-dimensional model of the lymph flow through a lymphangion with valve dynamics and a contractile wall 带有瓣膜动力学和收缩壁的淋巴管淋巴流的准线性双曲一维模型

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-11 DOI: 10.1080/10255842.2024.2399769

Alberto Girelli

引用次数: 0

Fracture risk prediction in diabetes patients based on Lasso feature selection and Machine Learning. 基于拉索特征选择和机器学习的糖尿病患者骨折风险预测

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-11 DOI: 10.1080/10255842.2024.2400325

Yu Shi,Junhua Fang,Jiayi Li,Kaiwen Yu,Jingbo Zhu,Yan Lu

{"title":"Fracture risk prediction in diabetes patients based on Lasso feature selection and Machine Learning.","authors":"Yu Shi,Junhua Fang,Jiayi Li,Kaiwen Yu,Jingbo Zhu,Yan Lu","doi":"10.1080/10255842.2024.2400325","DOIUrl":"https://doi.org/10.1080/10255842.2024.2400325","url":null,"abstract":"Fracture risk among individuals with diabetes poses significant clinical challenges due to the multifaceted relationship between diabetes and bone health. Diabetes not only affects bone density but also alters bone quality and structure, thereby increases the susceptibility to fractures. Given the rising prevalence of diabetes worldwide and its associated complications, accurate prediction of fracture risk in diabetic individuals has emerged as a pressing clinical need. This study aims to investigate the factors influencing fracture risk among diabetic patients. We propose a framework that combines Lasso feature selection with eight classification algorithms. Initially, Lasso regression is employed to select 24 significant features. Subsequently, we utilize grid search and 5-fold cross-validation to train and tune the selected classification algorithms, including KNN, Naive Bayes, Decision Tree, Random Forest, AdaBoost, XGBoost, Multi-layer Perceptron (MLP), and Support Vector Machine (SVM). Among models trained using these important features, Random Forest exhibits the highest performance with a predictive accuracy of 93.87%. Comparative analysis across all features, important features, and remaining features demonstrate the crucial role of features selected by Lasso regression in predicting fracture risk among diabetic patients. Besides, by using a feature importance ranking algorithm, we find several features that hold significant reference values for predicting early bone fracture risk in diabetic individuals.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biomechanical model of minimally invasive hallux valgus surgery 微创外翻手术的生物力学模型

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-10 DOI: 10.1080/10255842.2024.2400321

Yueyang Zhang, Yibo Ren, Jiateng Pan, Zihe Liu, Wanan Xiao, Yu Zhan

引用次数: 0

Finite element analysis and surrogate-optimized design of a nature-inspired auxetic stent. 受自然启发的辅助支架的有限元分析和代用优化设计。

IF 1.6 4区医学

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2024-09-10 DOI: 10.1080/10255842.2024.2399018

Y W Teong,K B Mustapha,Morufu Olusola Ibitoye

{"title":"Finite element analysis and surrogate-optimized design of a nature-inspired auxetic stent.","authors":"Y W Teong,K B Mustapha,Morufu Olusola Ibitoye","doi":"10.1080/10255842.2024.2399018","DOIUrl":"https://doi.org/10.1080/10255842.2024.2399018","url":null,"abstract":"Prior studies have revealed that the structural design of stents is critical to reducing some of the alarming post-operative complications associated with stent-related intervention. However, the technical search for stents that guarantee robustness against stent-induced post-intervention complications remains an open problem. Along this objective, this study investigates a re-entrant auxetic stent's structural response and performance optimizations. In pursuit of the goal, a nonlinear finite element analysis (FEA) is employed to uncover metrics characterizing the auxetic stent's mechanical behavior. Subsequently, the non-dominated sorting genetic algorithm (NSGA-II) is implemented to simultaneously minimize the stent's von Mises stress and the elastic radial recoil (ERR). Results from the FEA revealed a tight connection between the stent's response and the features of the base auxetic building block (the rib length, strut width, and the re-entrant angle). It is observed that the auxetic stent exhibits a much lower ERR. Besides, larger values of its rib length and re-entrant angle are noticed to favor smaller von Mises stress. The Pareto-optimal front from the NSGA-II-based optimization scheme revealed a sharp trade-off in the simultaneous minimization of the von Mises stress and the ERR. Moreover, an optimal combination of the auxetic unit cell's geometric parameters is found to yield a much lower maximum von Mises stress of ≈403 MPa and ERR of ≈0.4%.","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0