Computer Methods in Biomechanics and Biomedical Engineering最新文献

{"title":"Machine learning prediction of human blood optical properties: a comparative study of optimized algorithms with SHAP-based interpretability analysis.","authors":"Faiza Omari, Achouak Madani, Mohamed Kouider Amar, Mohamed Hentabli, Samira Tared, Latifa Khaouane, Maamar Laidi, Otmane Benkortebi, Jie Zhang","doi":"10.1080/10255842.2026.2723068","DOIUrl":"https://doi.org/10.1080/10255842.2026.2723068","url":null,"abstract":"<p><p>Accurate characterization of the optical properties of blood is essential for biomedical optics, diagnostic imaging, and therapeutic applications. conventional measurement techniques are frequently constrained by complex setups and idealized assumptions, highlighting the need for robust predictive models. This study presents a comparative machine learning framework to predict three blood optical properties: the absorption coefficient (µ_a), the scattering coefficient (µ_s), and the refractive index (RI). We developed and systematically optimized support vector regression (SVR), random forest (RF), and extreme gradient boosting (XGBoost) models using the Optuna framework, training them on a comprehensive dataset utilizing wavelength, hematocrit (Hct%), and oxygen saturation (SO2%) as input features. On the test dataset, the Optuna-optimized RF model achieved the highest predictive accuracy, with an R² of 0.9981 and a root mean squared error (RMSE) of 1.3680. It significantly outperformed both SVR (R² = 0.9736) and XGBoost (R² = 0.9865), demonstrating superior generalization capability. SHAP analysis provided model interpretability, confirming that the predictions were based on a physically meaningful relationship. Wavelength was the dominant predictor, while hematocrit and oxygen saturation contributed with light-tissue interaction principles, reinforcing model validity. Additionally, the analysis demonstrated that tree-based models exhibit superior feature utilization with clearer decision boundaries compared to SVR, more effectively capturing the nonlinear, hierarchical relationships inherent in biological systems. Finally, the optimized models were deployed <i>via</i> a user-friendly web interface, providing the biomedical optics community with accessible, interpretable tools for rapid optical property prediction to advance fundamental research and clinical applications.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-15"},"PeriodicalIF":1.9,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148841668","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}

{"title":"Comprehensive analysis of senescence-associated secretory phenotype-related signature for predicting prognosis and immunotherapy response in cervical cancer.","authors":"Yao Fu, Li Du, Haiyang Zhang, Jifeng Wan, Wei Ren, Haixia Pang","doi":"10.1080/10255842.2026.2723072","DOIUrl":"https://doi.org/10.1080/10255842.2026.2723072","url":null,"abstract":"<p><p>Cervical cancer (CESC) is a common malignancy in women. The senescence-associated secretory phenotype (SASP) contributes to tumor progression. We developed and validated a 7-gene SASP-related prognostic signature (PTPRB, RBM38, WNT3A, TNF, SPP1, ROR1, and MEIS2) using TCGA and GEO datasets. Patients in the low-risk group exhibited a more favorable prognosis and distinct immune infiltration patterns. TIDE analysis indicated a more favorable predicted immunotherapy response in the low-risk group. Single-cell analysis demonstrated distinct expression patterns of prognostic genes across cell types. This signature may help predict prognosis and therapeutic response in CESC patients.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-19"},"PeriodicalIF":1.9,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148820002","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}

{"title":"Synthetic data generation from a stenosed carotid arteries using sensitivity analysis: an application to AI models.","authors":"Shamsul Haq, Raheem Gul, Nasir Siddiqui","doi":"10.1080/10255842.2026.2717628","DOIUrl":"https://doi.org/10.1080/10255842.2026.2717628","url":null,"abstract":"<p><p>In artificial intelligence (AI), data dramatically impacts AI models performance, accuracy, and reliability. High-quality data enables models to make better predictions and produce more reliable outcomes. Poor data quality or lack of data can lead to flawed results and cause poor performance and predictions. Sensitivity analysis could play a vital role to generate synthetic dataset from any validated model. Within this work, a sensitivity-based approach is used to generate synthetic data or measurements for healthy and stenosed carotid arteries. Pressure and flow time-series are collected for different levels of stenosis ranging from <math><mrow><mn>30</mn><mi>%</mi></mrow></math> to <math><mrow><mn>90</mn><mi>%</mi></mrow><mtext>,</mtext></math> which are created artificially from a validated model of the stenosed carotid arteries. Based on the generated dataset, a machine learning model could be developed for new data to detect the site and level of stenosis in the carotid arteries. In order to validate the applicability of the generated dataset for AI-driven analysis, a proof-of-concept Random Forest classifier was trained to classify different levels of stenoses (mild, moderate, and severe) using a <math><mrow><mn>70</mn><mi>%</mi><mi>n</mi><mn>30</mn><mi>%</mi></mrow></math> train-test split. The model achieved an overall accuracy of <math><mrow><mn>99.81</mn><mi>%</mi></mrow><mtext>,</mtext></math> demonstrating strong discriminative capability of the simulated pressure and flow time-series. Although this high performance is obtained under idealized synthetic conditions without measurement noise, the results confirm that sensitivity-based synthetic data generation can effectively support machine learning applications for carotid stenosis detection and severity assessment.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-12"},"PeriodicalIF":1.9,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801225","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}

{"title":"Stage-dependent muscle force patterns during femoral fracture reduction: a patient-specific modeling study.","authors":"Dongru Xie, Hongjian Yu, Zhijiang Du, Xin Hua, Xiangyu Shen, Zhen Wang, Canhua Ye, Huiren Tao","doi":"10.1080/10255842.2026.2718489","DOIUrl":"https://doi.org/10.1080/10255842.2026.2718489","url":null,"abstract":"<p><p>During fracture reduction, bone segment pose changes induce complex muscle force responses, but their patterns and association with fracture geometry remain unclear. Using CT data from 16 femoral shaft fracture cases, patient-specific musculoskeletal models were developed in AnyBody. A staged fracture reduction simulation framework comprising traction, derotation, translational alignment, and length restoration was established. Muscle force distribution exhibited heterogeneity and stage-dependent characteristics. Additionally, muscle force showed a multivariate association with fracture geometric parameters. The multivariate model achieved an <math><mrow><mrow><msup><mrow><mi>R</mi></mrow><mn>2</mn></msup></mrow></mrow></math> of 0.551, outperforming the univariate model. These findings provide quantitative biomechanical evidence for understanding muscle responses during fracture reduction.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-11"},"PeriodicalIF":1.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801198","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}

{"title":"A fractional-order impedance and momentum observer-based compliant interaction strategy for upper-limb exoskeletons.","authors":"Chun Liu, Xinrong Liu, Yuhang Xue","doi":"10.1080/10255842.2026.2719651","DOIUrl":"https://doi.org/10.1080/10255842.2026.2719651","url":null,"abstract":"<p><p>This study proposes a composite control framework for upper-limb rehabilitation exoskeletons integrating fractional-order impedance control, computed-torque compensation, and a momentum-based nonlinear disturbance observer. By combining Jacobian-transpose force mapping, fractional-order impedance shaping, and observer-based compensation, the framework enhances compliant yielding and tracking robustness under non-ideal dynamics. Simulation results show that, under severe spasticity-like impact, interaction force remains within 45 N. Under 30% mass mismatch and strong friction, tracking accuracy improves without reaching the 60 N·m torque limit. Under tremor-like disturbance, 4-8 Hz oscillations are attenuated while low-frequency voluntary motion is preserved, improving compliance, disturbance rejection, and torque smoothness.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-18"},"PeriodicalIF":1.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801048","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}

{"title":"A nonlinear coupled model of capillary blood flow under external pressure considering vascular elasticity and collapse.","authors":"Xinyi Cai, Hanyue Mo, Yuyao Chang, Zhe Li, Kun Cheng","doi":"10.1080/10255842.2026.2714842","DOIUrl":"https://doi.org/10.1080/10255842.2026.2714842","url":null,"abstract":"<p><p>External pressure alters microcirculatory blood flow, yet quantitative pressure-flow models remain limited. We develop a nonlinear three-stage coupling model unifying vascular elasticity and progressive collapse. A smooth transition function bridges the elastic, transitional, and collapse-dominant regimes, eliminating discontinuities in conventional piecewise models. The model reveals stage-specific control: stiffness dominates low-pressure flow, collapse pressure scale governs the transition, and attenuation coefficient controls high-pressure flow. Sensitivity analysis identifies nonlinear coupling between vessel radius and stiffness, together with synergistic geometric and collapse effects. These findings provide a quantitative framework for pressure-induced microvascular flow regulation and pressure-based therapeutic optimization.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-13"},"PeriodicalIF":1.9,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801084","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}

{"title":"A generalized multilayer reaction-diffusion model for tumor dynamics under hyperthermic therapy with spatial heterogeneity.","authors":"Saqib Mubarak","doi":"10.1080/10255842.2026.2717311","DOIUrl":"https://doi.org/10.1080/10255842.2026.2717311","url":null,"abstract":"<p><p>Local hyperthermia is an effective treatment for advanced malignant tumors, whose multilayer structure and physiological heterogeneity strongly influence their response to therapy. In this work, a generalized multilayer reaction-diffusion model is developed to study tumor-volume dynamics under localized hyperthermic treatment. The tumor is represented as a set of interacting biological layers, allowing spatial variation in key parameters such as diffusion and proliferation. The model is formulated with appropriate initial, interface and boundary conditions and solved using the finite element method. Simulations are carried out for planar, cylindrical and spherical tumor geometries to examine the effects of heterogeneity, geometry and hyperthermia. The results show a clear reduction in tumor volume under thermal therapy, with stronger effects observed in spherical tumors due to enhanced diffusion. Sensitivity analysis and comparison with published data further support the reliability of the model. Overall, the proposed work provides a simple and flexible approach for analyzing tumor behavior under hyperthermic treatment. This work can support future treatment planning studies.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-17"},"PeriodicalIF":1.9,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801051","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}

{"title":"Enhance motor imagery EEG classification using DWT and chirplet transform.","authors":"Swati Patil, Deepali Sultane, Prashant K Shah","doi":"10.1080/10255842.2026.2704678","DOIUrl":"https://doi.org/10.1080/10255842.2026.2704678","url":null,"abstract":"<p><p>Brain Computer Interfaces promote seamless interaction between individuals with movement limitations and their surrounding environment by transforming electroencephalography signals derived using Motor Imagery. The procedure relies on accurately classifying various MI activities, which requires dependable approaches for EEG signal classification to be continuously improved. In this paper, discrete wavelet transform, and chriplet transform are proposed to enhance the performance of test system with demonstrating critical importance of time-related data and is implemented in visual studio code python. The proposed method holds 91% efficiency, accuracy 94.8% for CBCIC and 93.72% for BCI Competition IV Dataset with response time of 1.03 sec.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-12"},"PeriodicalIF":1.9,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148708294","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}

{"title":"<i>In silico</i> biomechanical evaluation of personalized A-shaped titanium plates for mandibular condylar base fractures.","authors":"Jie Li, Chong-Tao Xu, Ting Luo, Guo-Ning Xiao, Yuan Liang","doi":"10.1080/10255842.2026.2716410","DOIUrl":"https://doi.org/10.1080/10255842.2026.2716410","url":null,"abstract":"<p><p>The anatomical complexity of the mandibular condylar base renders open reduction and internal fixation challenging for fractures in this region. Although the double-straight-plate fixation remains the most widely adopted clinical strategy, its implementation is frequently hindered by technical limitations inherent to conventional operative routes. The biomechanical adequacy of single-geometric-plate fixation has not been conclusively established and warrants rigorous experimental validation. This study developed personalized A-shaped plates with 5-, 6-, and 7-hole configurations, geometrically optimized to adjust the curvature of the anterior arm to accommodate the anatomical contour of the sigmoid notch. Subsequently, the biomechanical efficacy of these personalized plates in stabilizing condylar base fractures was systematically evaluated. Finally, a multi-dimensional quantitative comparison was conducted to assess biomechanical differences between the proposed single-geometric-plate fixation and conventional fixation protocols. The 7-hole-A-shaped-plate configuration demonstrated biomechanical performance equivalent to the double-straight-plate configuration across all parameters. The 6- and 5-hole-A-shaped-plate configuration achieved comparable global stability but exhibited significantly elevated stress concentration in either fixation hardware or adjacent cortical bone. The <i>in silico</i> study furnishes robust biomechanical evidence to support individualized selection of A-shaped geometric fixation for condylar base fractures.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-18"},"PeriodicalIF":1.9,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148714504","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}

{"title":"Contrastive Learning Network based on Multi-Scale Transformer (CLMT-net): EEG decoding for fine-grained motor imagery of movements within the same limb.","authors":"Lei Zhu, Qifeng Yue, Aiai Huang, Jianhai Zhang, Peng Yuan","doi":"10.1080/10255842.2026.2714841","DOIUrl":"https://doi.org/10.1080/10255842.2026.2714841","url":null,"abstract":"<p><p>Motor imagery (MI)-based brain-computer interfaces (BCIs) decode EEG signals into control commands. However, fine-grained MI decoding within the same limb remains challenging due to highly similar neural patterns. This paper proposes a Contrastive Learning Network based on a Multi-Scale Transformer (CLMT-Net) for fine-grained MI decoding. CLMT-Net integrates multi-scale temporal convolution, FFT-based frequency fusion, spatial convolution, and dual-path Transformer to learn complementary EEG representations. Supervised contrastive learning further improves feature discrimination. On the MI-2 dataset, CLMT-Net achieves an accuracy of 76.13 ± 6.77% with a 95% confidence interval of [73.33, 78.92], demonstrating competitive performance for same-limb MI decoding.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-17"},"PeriodicalIF":1.9,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148702731","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}