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Symmetrical structure design of PLGA Biodegradable sinus stents and structure optimization based on surrogate models. 基于代用模型的 PLGA 可生物降解鼻窦支架的对称结构设计与结构优化。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-10-01 Epub Date: 2024-05-22 DOI: 10.1080/10255842.2024.2355491
Lingyan Li, Peng Zhu, Qiao Li, Yuanming Gao, Yubo Fan
{"title":"Symmetrical structure design of PLGA Biodegradable sinus stents and structure optimization based on surrogate models.","authors":"Lingyan Li, Peng Zhu, Qiao Li, Yuanming Gao, Yubo Fan","doi":"10.1080/10255842.2024.2355491","DOIUrl":"10.1080/10255842.2024.2355491","url":null,"abstract":"<p><p>This study aims to enhance the degradation uniformity of PLGA sinus stents to minimize fracture risk caused by stress corrosion. Symmetric stent structures were introduced and compared to sinusoidal structure in terms of stress and degradation uniformity during implantation and degradation processes. Three surrogate models were employed to optimize the honeycomb-like structure. Results showed honeycomb-like structures exhibited the superior stress distribution and highest degradation uniformity. The kriging model achieved the smallest error and degradation uniformity of 83.24%. In conclusion, enhancing the symmetry of stent structures improves degradation uniformity, and the kriging model has potential for the optimization of stent structures.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1981-1990"},"PeriodicalIF":1.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141082874","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
Seizure detection using nonlinear measures over EEG frequency bands and deep learning classifiers. 使用脑电图频带非线性测量和深度学习分类器进行癫痫发作检测。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-10-01 Epub Date: 2024-05-27 DOI: 10.1080/10255842.2024.2356634
Amel Benzaid, Rafik Djemili, Khaled Arbateni
{"title":"Seizure detection using nonlinear measures over EEG frequency bands and deep learning classifiers.","authors":"Amel Benzaid, Rafik Djemili, Khaled Arbateni","doi":"10.1080/10255842.2024.2356634","DOIUrl":"10.1080/10255842.2024.2356634","url":null,"abstract":"<p><p>Epilepsy is a brain disorder that causes patients to suffer from convulsions, which affects their behavior and way of life. Epilepsy can be detected with electroencephalograms (EEGs), which record brain neural activity. Traditional approaches for detecting epileptic seizures from an EEG signal are time-consuming and annoying. To supersede these traditional methods, a myriad of automated seizure detection frameworks based on machine learning techniques have recently been developed. Feature extraction and classification are the two essential phases for seizure detection. The classifier assigns the proper class label after feature extraction lowers the input pattern space while maintaining useful features. This paper proposes a new feature extraction method based on calculating nonlinear features from the most relevant EEG frequency bands. The EEG signal is first decomposed into smaller time segments from which a vector of nonlinear features is computed and supplied to machine learning (ML) and deep learning (DL) classifiers. Experiments on the Bonn dataset reveals an accuracy of 99.7% reached in classifying normal and ictal EEG signals; and an accuracy of 98.8% in the discrimination of ictal and interictal EEG signals. Furthermore, a performance of 100% is achieved on the Hauz Khas dataset. The classification results of the proposed approach were compared to those from published state of the art techniques. Our results are equivalent to or better than some recent studies appeared in the literature.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"2032-2048"},"PeriodicalIF":1.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141159194","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
EEG-based motor execution classification of upper and lower extremities using machine learning. 基于脑电图的上肢和下肢运动执行分类的机器学习。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-09-30 DOI: 10.1080/10255842.2025.2566260
Ismail Korkmaz, Cengiz Tepe
{"title":"EEG-based motor execution classification of upper and lower extremities using machine learning.","authors":"Ismail Korkmaz, Cengiz Tepe","doi":"10.1080/10255842.2025.2566260","DOIUrl":"https://doi.org/10.1080/10255842.2025.2566260","url":null,"abstract":"<p><p>This study classifies upper- and lower-extremity motor execution from electroencephalography (EEG). We compared two feature extractors, statistical features and Common Spatial Patterns (CSP), and four classifiers: K-Nearest Neighbors, Linear Discriminant Analysis (LDA), Multilayer Perceptron, and Support Vector Machine. Metrics were accuracy, F1, precision, and recall. CSP with LDA achieved the best, most consistent performance (72.5% accuracy); statistical features underperformed. We report real-time feasibility benchmarks, post-cue time-window analysis, and significance tests for classifiers. Findings support BCI and neuroprosthesis development, while noting subject variability and dataset specificity. Future work is real-time use, cross-dataset generalization, and hybrid deep learning.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-17"},"PeriodicalIF":1.6,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202014","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
Computational fluid-structure interaction analysis of arterial hemodynamics for cardiovascular risk assessment. 用于心血管风险评估的动脉血流动力学计算流固耦合分析。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-09-30 DOI: 10.1080/10255842.2025.2564341
Hedyeh Mahjoub, Kamran Hassani, Ali Sheikhani, Mehdi Razeghi
{"title":"Computational fluid-structure interaction analysis of arterial hemodynamics for cardiovascular risk assessment.","authors":"Hedyeh Mahjoub, Kamran Hassani, Ali Sheikhani, Mehdi Razeghi","doi":"10.1080/10255842.2025.2564341","DOIUrl":"https://doi.org/10.1080/10255842.2025.2564341","url":null,"abstract":"<p><p>Cardiovascular diseases (CVDs) continue to be a major cause of death worldwide; thus, improving diagnostic and treatment methods requires advanced computer modeling techniques. This study aimed to investigate the hemodynamic and structural behavior of arterial walls using a fluid-structure interaction (FSI) model. Modeling the walls as hyper-elastic materials and assuming Newtonian blood flow, COMSOL multiphysics was used to create a three-dimensional (3D) computational model of the aorta and its main branches. Our new model enhances one-way and two-way coupling comparisons to evaluate the effects on wall stress, velocity profiles, and flow and pressure distributions. According to the simulation results, two-way coupling efficiently captured the bidirectional interplay between blood flow and arterial mechanics, improving wall stress estimates by 30% compared with one-way coupling. Under high-viscosity conditions (0.1 Pa·s), the proximal aorta exhibited a peak velocity of approximately 0.13 m/s, which gradually decreased downstream owing to branching and arterial compliance. Systolic pressures were highest near the aortic entrance and decreased downstream, according to pressure distribution studies. Furthermore, under extreme hypertension conditions (160 mmHg), the experiments revealed a maximal displacement of 4.10 μm, where the mechanical stress was highest in disease-prone areas. Nevertheless, although intensive computations are required, our results highlight the potential of sophisticated FSI modeling to improve personalized risk prediction for cardiovascular disorders.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-12"},"PeriodicalIF":1.6,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202047","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
Comparison of lumbar fusion and artificial disc replacement: a finite element analysis. 腰椎融合术与人工椎间盘置换术的比较：有限元分析。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-09-29 DOI: 10.1080/10255842.2025.2566253
Jingang Zhao, Ke Wei, Junling Chen, Daming Feng, Jingsong Xue, Liping Liu, Jianwei Chen
{"title":"Comparison of lumbar fusion and artificial disc replacement: a finite element analysis.","authors":"Jingang Zhao, Ke Wei, Junling Chen, Daming Feng, Jingsong Xue, Liping Liu, Jianwei Chen","doi":"10.1080/10255842.2025.2566253","DOIUrl":"https://doi.org/10.1080/10255842.2025.2566253","url":null,"abstract":"<p><p>This study quantitatively evaluates biomechanical effects on L2-L5 of lumbar fusion versus two artificial disc prostheses. Finite element models of normal/operated spines were built; Physiological motions were simulated, with range of motion (RoM) and adjacent discs' peak von Mises stress recorded. Out results showed that fusion increased adjacent stress; mechanical prosthesis enhanced specific RoM, viscoelastic one preserved near-normal RoM/stress. Disc replacement has better biomechanics; viscoelastic prosthesis aids physiological preservation, informing prosthesis design and clinical practice for lumbar degenerative disease.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-12"},"PeriodicalIF":1.6,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187518","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
Identification and validation of centrosome-related features predicting prognosis in hepatocellular carcinoma. 肝细胞癌中心体相关特征预测预后的鉴定和验证。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-09-29 DOI: 10.1080/10255842.2025.2566280
Qingqing Wang, Yifan Lu, Songhai Chen, Xuanzeng Pei, Jie Zhang
{"title":"Identification and validation of centrosome-related features predicting prognosis in hepatocellular carcinoma.","authors":"Qingqing Wang, Yifan Lu, Songhai Chen, Xuanzeng Pei, Jie Zhang","doi":"10.1080/10255842.2025.2566280","DOIUrl":"https://doi.org/10.1080/10255842.2025.2566280","url":null,"abstract":"<p><p>Hepatocellular carcinoma (HCC) is commonly linked with centrosome abnormalities that contribute to chromosomal instability and tumor progression. Four prognostic centrosome-related genes (CRGs): DYNLL1, CEP85, C10orf90, and CETN1 were utilized to develop a risk model for HCC. The model demonstrated strong prognostic reliability. Both risk score and risk group served as independent prognostic predictors for HCC. Further analyses revealed that the low-risk group was associated with metabolism and detoxification pathways and exhibited a lower abundance of M2 macrophages. Additionally, high expression levels of DYNLL1 and CETN1 were significantly correlated with poorer prognosis, with upregulation of DYNLL1 confirmed in HCC patients.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-14"},"PeriodicalIF":1.6,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187514","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
Transformed wavelets for motor imagery EEG classification using hybrid CNN-modified vision transformer: an exploratory study of MI EEG. 基于混合cnn -改进视觉变换的变换小波运动图像脑电分类：一种MI脑电的探索性研究。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-09-26 DOI: 10.1080/10255842.2025.2563351
Balendra, Neeraj Sharma, Shiru Sharma
{"title":"Transformed wavelets for motor imagery EEG classification using hybrid CNN-modified vision transformer: an exploratory study of MI EEG.","authors":"Balendra, Neeraj Sharma, Shiru Sharma","doi":"10.1080/10255842.2025.2563351","DOIUrl":"https://doi.org/10.1080/10255842.2025.2563351","url":null,"abstract":"<p><p>Wavelets capture signal characteristics across time and frequency, but traditional wavelets suffer from high time-bandwidth products (TBP), limiting feature discrimination in EEG classification. We propose transformed wavelets with improved TBP and frequency bandwidth, outperforming Morlet by 0.04 and 0.20, respectively. Using datasets BCI Competition IV 2a, 2b, and CLA, we evaluated both fundamental and transformed wavelets with a modified vision transformer (MViT). Enhanced scalograms generated through local mean and principal component analysis (PCA) consistently outperformed raw scalograms. A hybrid convolutional neural network (CNN)-MViT achieved 82.35% inter-subject and 89.02% intra-subject accuracy, with 3-4% average gains in motor imagery EEG decoding.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-18"},"PeriodicalIF":1.6,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151724","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: study of better osteotomy angle of the first metacarpal for thumb carpometacarpal osteoarthritis. 有限元分析：第一掌骨最佳截骨角度治疗拇指腕掌骨关节炎的研究。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-09-25 DOI: 10.1080/10255842.2025.2566247
Akitoshi Sakuma, Yusuke Matsuura, Seiji Ohtori
{"title":"Finite element analysis: study of better osteotomy angle of the first metacarpal for thumb carpometacarpal osteoarthritis.","authors":"Akitoshi Sakuma, Yusuke Matsuura, Seiji Ohtori","doi":"10.1080/10255842.2025.2566247","DOIUrl":"https://doi.org/10.1080/10255842.2025.2566247","url":null,"abstract":"<p><p>This study examines the impact of metacarpal osteotomy at varying directions and angles. Using hand CT-DICOM data from fresh frozen cadavers, 3D models were created and analyzed with finite element analysis. Stress changes across various osteotomy directions and angles were compared. The findings indicate that a 30° extension and 30° abduction-opposition osteotomy significantly shift pressure distribution toward the volar side, which may reduce stress and enhance joint congruity.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-9"},"PeriodicalIF":1.6,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151650","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
Accuracy of machine learning techniques for real-time prediction of implanted lower limb mechanics with comprehensive and reduced input parameters. 机器学习技术在全面和减少输入参数的植入下肢力学实时预测中的准确性。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-09-23 DOI: 10.1080/10255842.2025.2554259
Chase Maag, Clare K Fitzpatrick, Paul J Rullkoetter
{"title":"Accuracy of machine learning techniques for real-time prediction of implanted lower limb mechanics with comprehensive and reduced input parameters.","authors":"Chase Maag, Clare K Fitzpatrick, Paul J Rullkoetter","doi":"10.1080/10255842.2025.2554259","DOIUrl":"https://doi.org/10.1080/10255842.2025.2554259","url":null,"abstract":"<p><p>This study evaluates the accuracy of machine learning techniques for real-time prediction of implanted knee mechanics. A musculoskeletal lower limb model was used to generate joint mechanics for a training dataset of 1500 simulations with varying surgical alignments, loading, and ligament properties. The objective was to determine the minimum input dataset required to estimate implanted biomechanics using three predictive methods: linear-regression, bi-directional long short-term memory (biLSTM), and transformer-based models. Results indicate that the biLSTM model had ∼45% lower nRMSE than the other models with reduced inputs. In the longer-term, this may aid in optimizing implant positioning pre- or intra-operatively.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-11"},"PeriodicalIF":1.6,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145126409","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
EMG intention perception approach in multimodal human computer interaction of wheelchairs. 轮椅多模态人机交互中的肌电图意图感知方法。
IF 1.6 4区 医学
Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-09-22 DOI: 10.1080/10255842.2025.2560524
Jie Hong, Miao Cai, Xiansheng Qin
{"title":"EMG intention perception approach in multimodal human computer interaction of wheelchairs.","authors":"Jie Hong, Miao Cai, Xiansheng Qin","doi":"10.1080/10255842.2025.2560524","DOIUrl":"https://doi.org/10.1080/10255842.2025.2560524","url":null,"abstract":"<p><p>At present, the limited mobility of the rehabilitation robots hampers stroke recovery. To address this issue, this paper presents multimodal human computer interaction (HCI) of wheelchairs, concentrating on electromyography (EMG) intention perception approach utilized in wheelchair control. In our study, five healthy subjects recorded EMG signals from four gestures. Through mean absolute value (MAV), root mean square (RMS), and probabilistic neural network (PNN) for classification, the EMG intention perception approach successfully facilitated multi-command control of wheelchairs. Although preliminary, this validation shows great promise for revolutionizing assistive mobility, enhancing independence, and significantly improving the quality of life for stroke patients.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-15"},"PeriodicalIF":1.6,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114911","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
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