生物医学工程学杂志最新文献

{"title":"[A simulation study of photothermal effects in transcranial photobiomodulation].","authors":"Xintong Liu, Jie Xia, Jiadong Pan, Shipeng Chen, Shaomin Zhang, Minmin Wang, Shurong Dong","doi":"10.7507/1001-5515.202512019","DOIUrl":"10.7507/1001-5515.202512019","url":null,"abstract":"<p><p>Transcranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique utilizing infrared or near-infrared light. Clarifying the energy deposition patterns and safe dose thresholds within realistic anatomical head structures is crucial for advancing its clinical application. However, existing studies often rely on simplified models for numerical simulation, which may fail to accurately capture the influence of cortical sulci and gyri on light propagation and thermal diffusion. This study established a high-resolution (1 mm ³) anatomically realistic human head model using the finite element method, and developed an optical-thermal multiphysics coupling framework to systematically simulate and analyze key parameters, including power density and wavelength, to evaluate light penetration depth and tissue temperature elevation characteristics. The results demonstrated that approximately 0.05% of the incident optical power penetrated to the cortical gray matter. As the power density increased, scalp temperature elevation reached up to 5.22 °C, and brain temperature elevation reached up to 0.49 °C, with a distinct \"halo\" scattering effect observed within the cerebrospinal fluid layer. These simulation results systematically revealed the photothermal propagation characteristics and tissue thermal responses of tPBM in realistic head anatomy, providing an important theoretical basis for defining safe dose thresholds and optimizing individualized stimulation parameters.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"686-694"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148833466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Multi-view signal integration via manifold learning for sleep stage classification].","authors":"Wei Tong, Xi Lin, Xinying Wu, Tao Li, Qi Wu","doi":"10.7507/1001-5515.202512024","DOIUrl":"10.7507/1001-5515.202512024","url":null,"abstract":"<p><p>Sleep disorders and sleep disturbances are gaining increasing attention, and accurate sleep staging is key to assessing sleep quality. Existing studies utilize spatio-temporal features of multi-channel physiological signals such as EEG and spatial topological information of brain regions for sleep staging, but they suffer from insufficient mining of spatio-temporal correlations, neglect of the nonlinear geometric structure of signals, and feature redundancy, leading to low accuracy in sleep stage classification. To address these problems, this paper proposes a multi-view spatio-temporal convolutional integration network based on manifold learning. Firstly, three types of feature representations of multi-physiological signals are constructed via short-time Fourier transform, discrete wavelet transform, and raw signal processing. Secondly, an attention module that fuses Euclidean space and manifold geometry is designed to represent and enhance multi-modal physiological signals on the Riemannian symmetric positive definite manifold, mining their potential spatio-temporal representations. Finally, combining these three types of sleep features from adjacent time segments, long short-term memory (LSTM) is used to model temporal dependencies to accomplish sleep stage classification. Experimental results on public sleep stage classification datasets show that the proposed method outperforms existing mainstream methods in accuracy, F1-score, and Kappa coefficient, and ablation studies validate the effectiveness of the manifold attention mechanism and multi-view feature combination. This work provides a new method for nonlinear fusion of multi-modal physiological signals.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"729-740"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519829/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148832620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[A study on three-dimensional reconstruction of coronary arteries and numerical simulation of fractional flow reserve based on deep learning].","authors":"Jiangchao Wei, Lihua Wang, Wenpu Zhang","doi":"10.7507/1001-5515.202603042","DOIUrl":"10.7507/1001-5515.202603042","url":null,"abstract":"<p><p>To address the needs of geometric modeling and hemodynamic analysis in the noninvasive functional assessment of coronary heart disease, this study establishes a deep learning-based integrated framework for coronary artery segmentation, three-dimensional reconstruction, and hemodynamic analysis. The nnU-Net model was used to achieve automatic coronary artery segmentation, and point cloud modeling techniques based on the Point Cloud Library (PCL) were further applied to construct patient-specific coronary artery models. Based on the reconstructed models, coronary hemodynamic numerical simulations were performed to analyze the variation characteristics of key indicators, including the blood flow velocity field, fractional flow reserve derived from computed tomography (CT-FFR), and wall shear stress (WSS), under different degrees of coronary artery stenosis. The results showed that, with increasing stenosis severity, local flow acceleration and high-velocity jet flow in the stenotic segment were enhanced, while the pressure distal to the stenosis decreased, leading to a gradual reduction in CT-FFR. Meanwhile, WSS increased in the stenotic region and adjacent vessel walls, and the high-WSS region expanded. These results indicate that the combination of machine learning-based three-dimensional reconstruction and hemodynamic analysis can help compensate for the limitations of conventional CT imaging in functional assessment, providing a numerical simulation basis for the noninvasive functional evaluation of coronary artery stenosis.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"751-759"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519830/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148833461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Numerical simulation of coping strategies for the \"bird-beak\" phenomenon in thoracic endovascular aortic repair].","authors":"Dali He, Shiliang Chen, Hanbing Zhang, Aike Qiao","doi":"10.7507/1001-5515.202511037","DOIUrl":"https://doi.org/10.7507/1001-5515.202511037","url":null,"abstract":"<p><p>This study aims to explore the effects of different surgical strategies on the \"bird-beak\" phenomenon during thoracic endovascular aortic repair (TEVAR), so as to provide a theoretical basis for clinical intervention optimization. Three finite element aortic arch models with arch apex angles of 45°, 55°, and 65° were established via finite element simulation. Two stent implantation regions and three gradient stent oversizing ratios of 10%, 20%, and 30% were configured. The bird-beak angle, stent contact area, and vascular wall von Mises stress were quantitatively analyzed to compare the mechanical performance of stent implantation under different parameter combinations. Our results revealed a negative correlation between aortic arch angle and the threshold oversizing ratio required for bird-beak elimination. For 45° small angle aortic arches, 30% oversizing was necessary to resolve the bird-beak effect, whereas merely 20% oversizing sufficed for 55° and 65° larger angle arches. Nevertheless, excessive oversizing of 30% induced stent ring kinking and prolapse, reduced stent vessel apposition area, substantially elevated aortic wall stress, and raised the risk of vascular injury. Furthermore, landing zone 2 implantation was associated with a significantly higher risk of bird-beak formation compared with landing zone 3. In conclusion, stents with >20% oversizing are recommended for patients with 45° small angle aortic arches, with close attention paid to preventing stent deformation. For 55° and 65° aortic arches, 20% oversizing is sufficient to mitigate complications related to bird-beak. These findings offer theoretical support for operative planning and complication reduction in clinical TEVAR practice.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"760-768"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148832842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Analysis of the constraints of inherent limitations on the capability boundaries of brain-computer interfaces and corresponding strategies].","authors":"Yunfa Fu, Haoyu Yao, Tianwen Li, Lei Zhao, Xue Yang, Rongzhang Luo, Jiaping Xu","doi":"10.7507/1001-5515.202603080","DOIUrl":"10.7507/1001-5515.202603080","url":null,"abstract":"<p><p>Brain-computer interfaces (BCIs) has developed rapidly in recent years, yet a systematic understanding of its inherent limitations and capability boundaries remains insufficient. This paper analyzes the constraint mechanisms through which inherent limitations shape BCI capability boundaries and discusses corresponding strategies from the perspectives of neural information generation, representation, acquisition, and utilization. The analysis indicates that the inherent limitations of BCI mainly arise from the dynamic nature of neural coding, inter-individual variability, low signal-to-noise ratios, partial observability, and paradigm dependence. As the intrinsic basis for capability boundary formation, these limitations jointly constrain the capability boundaries at the neural information, human-factors, and system levels, which are manifested as the upper performance limits of decoding accuracy, information transfer rate, complex intention decoding, user experience, as well as system stability, reliability, and safety. To address these constraints, this paper summarizes representative strategies, including information enhancement, adaptive decoding, human-machine collaboration, and system optimization. The analysis suggests that improvements in BCI performance fundamentally rely on enhancing neural information utilization and progressively expanding achievable capability boundaries under existing constraints, rather than overcoming their underlying limitations. The proposed framework provides a theoretical basis for understanding the relationship between inherent limitations and capability boundaries, and provides a reference for BCI research, technological innovation, practical applications, and scientific communication.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"669-677"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519809/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148833513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Personalized lower-limb gait assessment method based on musculoskeletal modeling and machine learning].","authors":"Daxing Zeng, Xiangyang Luo, Hongyu Xu, Huizhi Chen, Ya Liu, Wenjuan Lu","doi":"10.7507/1001-5515.202512061","DOIUrl":"10.7507/1001-5515.202512061","url":null,"abstract":"<p><p>To address the issues of insufficient objectivity and difficulty in locating muscle dysfunction in current lower-limb gait assessment methods, this paper proposes a personalized lower-limb gait assessment method that integrates a musculoskeletal model with machine learning. First, a personalized musculoskeletal model is constructed using human biomechanical simulation software through model scaling and optimized calibration of key muscle parameters, and the validity of the proposed model is verified by comparing simulation results with experimental data. Second, the peak coefficient of variation (PCV) is introduced to quantify the stability of muscle control, and differences in neuromuscular control patterns of the lower limbs between healthy individuals and stroke patients are analyzed. Finally, a gait assessment model is developed using machine learning to recognize gait abnormalities and identify abnormal muscles, combined with rule-based reasoning to generate personalized rehabilitation training plans. Experimental results show that the output of the proposed gait assessment model is highly consistent with clinical grading results, achieving an accuracy of 92.3% and a Kappa coefficient of 0.87. The findings confirm that the proposed lower-limb gait assessment method can effectively quantify the gait and muscle characteristics of stroke patients, enabling both quantitative and qualitative evaluation of gait, thus providing an objective basis for personalized rehabilitation of stroke patients.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"808-817"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519820/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148832863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Synergistic learnable frequency and multi-scale spatial network for lightweight skin cancer classification].","authors":"Jianjun Zhuang, Zhenglong Lyu, Xiang Li","doi":"10.7507/1001-5515.202604067","DOIUrl":"10.7507/1001-5515.202604067","url":null,"abstract":"<p><p>Early screening of skin cancer is crucial to the survival rate of patients. Although deep learning has made significant progress in dermoscopic image analysis, the blurred edge of the lesion, the vulnerability to noise interference, and the limited computing resources at the time of model deployment are still the main bottlenecks. To this end, this paper proposes a frequency-space collaborative enhancement network (FSC-Net) based on lightweight classification. Aiming at the problem of blurred lesion edge and noise interference, the network first constructs a learning frequency enhancement module. Through the dynamic selective enhancement of frequency domain features, the lesion edge is finely characterized while suppressing high-frequency artifacts. Secondly, aiming at the scale heterogeneity of lesion morphology, this paper proposes a multi-scale aggregation module, which uses multi-branch pooling to reduce the loss of deep semantic features in the lightweight network. Finally, in order to solve the problem of difficult localization of complex lesion areas, this paper introduces a directional spatial calibration mechanism, which realizes accurate localization of lesion features through orthogonal decoupling coding and asymmetry factors. The experimental results on the 2019 international skin image collaboration challenge (ISIC2019) and the human against machine with 10000 training images (HAM10000) dataset show that FSC-Net achieves 93.41% eight-classification accuracy and 95.84% seven-classification accuracy with a lower number of parameters. Compared with the existing advanced models, the proposed method achieves a better balance between computational overhead and diagnostic performance, and provides a robust and efficient solution for auxiliary diagnosis in resource-constrained environments.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"836-844"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519823/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148832904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Noninvasive nanosecond transcranial pulsed electric fields: deep-penetrating, high-field stimulation for suppressing hippocampal amyloid-β and improving cognitive function in an Alzheimer's disease model].","authors":"Yue Chen, Chenguo Yao, Fanping Yan, Pangxin Xiao, Xiaoyu Lu","doi":"10.7507/1001-5515.202602022","DOIUrl":"10.7507/1001-5515.202602022","url":null,"abstract":"<p><p>Abnormal deposition of amyloid-β (Aβ) in the deep-brain hippocampus can impair synaptic transmission and disrupt neural network activity, thereby inducing learning and memory deficits and accelerating cognitive decline in Alzheimer's disease (AD). Therefore, reducing hippocampal Aβ deposition is an important strategy for delaying AD progression. Existing transcranial electrical stimulation methods are limited by safety thresholds and are difficult to achieve effective field strength in deep brain regions under noninvasive conditions, thus failing to effectively intervene in hippocampal Aβ deposition. Nanosecond pulsed electric fields, which contain abundant high-frequency components and exhibit stronger transcranial penetration capability, may overcome this limitation. In this study, nanosecond transcranial pulsed electric field stimulation (ns-tPFS) was applied with parameters of 500 ns band width, 500 V amplitude, and 5 Hz frequency in a five familial AD mutations (5xFAD) mouse model. First, finite element simulation was performed to determine that the electric field strength generated by ns-tPFS in the hippocampal region could reach 3 × 10 ⁴ V/m. Then, molecular dynamics simulation was used to evaluate the disruptive effect of this field strength on the structural stability of Aβ multimers. Subsequently, Morris water maze and Y-maze behavioral tests, together with immunofluorescence detection, were conducted to assess the intervention effects of ns-tPFS on animal cognitive function and hippocampal Aβ deposition. The results showed that, under the above stimulation parameters, ns-tPFS could disrupt the structure of Aβ multimers, markedly reduce hippocampal Aβ deposition in 5xFAD mice, and effectively improve their cognitive function. In summary, this study demonstrates, from animal simulations and experiments, the feasibility of ns-tPFS for improving AD symptoms and provides a new research perspective and experimental basis for the noninvasive intervention of hippocampal Aβ pathology.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"718-728"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519821/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148832812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Study on the effect of superficial layer damage on cartilage retention performance].","authors":"Zhaoyang Han, Lilan Gao, Fan Yang, Ruiqi Chen, Wangxuan Li, Chunqiu Zhang","doi":"10.7507/1001-5515.202601054","DOIUrl":"10.7507/1001-5515.202601054","url":null,"abstract":"<p><p>The superficial layer of articular cartilage acts as a critical physical barrier for joint homeostasis, and its damage is a hallmark of early osteoarthritis. To investigate the effect of superficial layer injury on solute permeation and retention in cartilage, two injury models were established using isolated porcine cartilage: chymotrypsin digestion (mucus layer injury) and physical abrasion (10% removal of the superficial layer). Rhodamine B (479 Da) and rhodamine-labeled dextrans (40 kDa, 150 kDa) were used as tracers. Combined with a custom-built permeation device and laser scanning confocal microscopy, solute transport behaviors under different injury degrees were analyzed. The results showed that superficial layer injury significantly impaired the barrier function, with retention concentrations increasing as injury severity rose. Solutes with lower molecular weights migrated more rapidly and exhibited higher retention levels. The peak solute concentration was localized in the superficial layer of normal cartilage but shifted toward the middle layer after injury. This study demonstrates that superficial layer integrity is essential for regulating cartilage solute transport, providing experimental evidence for understanding substance transport disorders in early cartilage degeneration of osteoarthritis.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"800-807"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519838/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148832947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Advances in stem cell and exosome-based therapies for dry eye disease].","authors":"Huateng Zhang, Leiqing Wang, Chao Lin, Nuannuan Li, Renyu Jiang, Lili Liang, Bo Li","doi":"10.7507/1001-5515.202602027","DOIUrl":"10.7507/1001-5515.202602027","url":null,"abstract":"<p><p>Conventional treatments for dry eye disease, such as artificial tears and anti-inflammatory drugs, can only alleviate symptoms, and it is difficult to achieve etiological repair with these treatments. In recent years, stem cell and exosome-based therapies have emerged as promising research hotspots for dry eye disease treatment, owing to their immunomodulatory, tissue-regenerative, and anti-inflammatory properties. Multiple basic and clinical studies have preliminarily confirmed the therapeutic potential of stem cells and exosomes in treating dry eye disease. This review summarizes recent advances in stem cell and exosome-based treatments for dry eye disease and analyzes their current regulatory landscapes, intending to serve as a reference for investigators within the field.</p>","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 4","pages":"886-892"},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148833482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}