Biomedical Physics & Engineering Express最新文献_第2页

Recent advances in applying machine learning to proton radiotherapy. 机器学习在质子放射治疗中的应用进展。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-23 DOI: 10.1088/2057-1976/adeb90

Vanessa L Wildman, Jacob F Wynne, Shadab Momin, Aparna H Kesarwala, Xiaofeng Yang

{"title":"Recent advances in applying machine learning to proton radiotherapy.","authors":"Vanessa L Wildman, Jacob F Wynne, Shadab Momin, Aparna H Kesarwala, Xiaofeng Yang","doi":"10.1088/2057-1976/adeb90","DOIUrl":"10.1088/2057-1976/adeb90","url":null,"abstract":"Background.Objectives: In radiation oncology, precision and timeliness of both planning and treatment are paramount values of patient care. Machine learning has increasingly been applied to various aspects of photon radiotherapy to reduce manual error and improve the efficiency of clinical decision making; however, applications to proton therapy remain an emerging field in comparison. This systematic review aims to comprehensively cover all current and potential applications of machine learning to the proton therapy clinical workflow, an area that has not been extensively explored in literature.Methods: PubMed and Embase were utilized to identify studies pertinent to machine learning in proton therapy between 2019 to 2024. An initial search on PubMed was made with the search strategy ''proton therapy', 'machine learning', 'deep learning''. A subsequent search on Embase was made with '('proton therapy') AND ('machine learning' OR 'deep learning')'. In total, 38 relevant studies have been summarized and incorporated.Results: It is observed that U-Net architectures are prevalent in the patient pre-screening process, while convolutional neural networks play an important role in dose and range prediction. Both image quality improvement and transformation between modalities to decrease extraneous radiation are popular targets of various models. To adaptively improve treatments, advanced architectures such as general deep inception or deep cascaded convolution neural networks improve online dose verification and range monitoring.Conclusions: With the rising clinical usage of proton therapy, machine learning models have been increasingly proposed to facilitate both treatment and discovery. Significantly improving patient screening, planning, image quality, and dose and range calculation, machine learning is advancing the precision and personalization of proton therapy.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12284894/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144558928","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}

引用次数: 0

Polydopamine-modified collagen membrane loading with platelet-rich plasma for enhancing diabetic wound healing. 多多巴胺修饰的胶原膜加载富血小板血浆促进糖尿病伤口愈合。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-21 DOI: 10.1088/2057-1976/adebf6

Hao-Jie Gao, Xiao-Wan Fang, Hao Chen, Zhen-Zhen Yan, Fei Xu, Chao Ji, Zi-Xuan Zhou, Yu-Xiang Wang, Jing-Nan Xun, Yi-Xin Wu, Fu-Ting Shu, Yong-Jun Zheng, Shi-Chu Xiao

{"title":"Polydopamine-modified collagen membrane loading with platelet-rich plasma for enhancing diabetic wound healing.","authors":"Hao-Jie Gao, Xiao-Wan Fang, Hao Chen, Zhen-Zhen Yan, Fei Xu, Chao Ji, Zi-Xuan Zhou, Yu-Xiang Wang, Jing-Nan Xun, Yi-Xin Wu, Fu-Ting Shu, Yong-Jun Zheng, Shi-Chu Xiao","doi":"10.1088/2057-1976/adebf6","DOIUrl":"10.1088/2057-1976/adebf6","url":null,"abstract":"Platelet-rich plasma (PRP), a reservoir of growth factors, is instrumental in the repair and regeneration of damaged tissues, orchestrating wound healing at all stages. However, PRP's rapid degradation and instability at the wound site, prone to displacement and degradation, limit its efficacy. Collagen, the most abundant protein in the human body, boasts exceptional biocompatibility, biological activity, and minimal immunogenicity. Polydopamine (PDA)-coated materials have been employed for sustained drug release, leveraging the catechol, amine, and imine functional groups on their surface for covalent bonding with other molecules. This study presents the fabrication of a PDA-modified collagen membrane (PDA-CM) loaded with PRP (PDA-CM@PRP) to achieve a sustained release of PRP. Our results showed that PDA-CM@PRP significantly improved proliferation, migration, delayed cellular senescence and reduced oxidative stress in human dermal fibroblasts (HDFs)in vitro.In vivoexperiments demonstrated accelerated diabetic wound healing with enhanced granulation tissue formation, cell proliferation, and neovascularization. Transcriptome sequencing analysis revealed that PDA-CM@PRP activated HDFs proliferation through upregulation of the cell cycle and DNA replication pathways. This study presents a novel strategy for sustained PRP release, offering a promising therapeutic approach for diabetic wounds and other chronic wound types.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144564325","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}

引用次数: 0

ViT-GCN: a novel hybrid model for accurate pneumonia diagnosis from x-ray images. ViT-GCN：一种基于x线影像的肺炎准确诊断的新型混合模型。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-21 DOI: 10.1088/2057-1976/adebf4

Nuo Xu, Jinran Wu, Fengjing Cai, Xi'an Li, Hong-Bo Xie

{"title":"ViT-GCN: a novel hybrid model for accurate pneumonia diagnosis from x-ray images.","authors":"Nuo Xu, Jinran Wu, Fengjing Cai, Xi'an Li, Hong-Bo Xie","doi":"10.1088/2057-1976/adebf4","DOIUrl":"10.1088/2057-1976/adebf4","url":null,"abstract":"This study aims to enhance the accuracy of pneumonia diagnosis from x-ray images by developing a model that integrates Vision Transformer (ViT) and Graph Convolutional Networks (GCN) for improved feature extraction and diagnostic performance. The ViT-GCN model was designed to leverage the strengths of both ViT, which captures global image information by dividing the image into fixed-size patches and processing them in sequence, and GCN, which captures node features and relationships through message passing and aggregation in graph data. A composite loss function combining multivariate cross-entropy, focal loss, and GHM loss was introduced to address dataset imbalance and improve training efficiency on small datasets. The ViT-GCN model demonstrated superior performance, achieving an accuracy of 91.43% on the COVID-19 chest x-ray database, surpassing existing models in diagnostic accuracy for pneumonia. The study highlights the effectiveness of combining ViT and GCN architectures in medical image diagnosis, particularly in addressing challenges related to small datasets. This approach can lead to more accurate and efficient pneumonia diagnoses, especially in resource-constrained settings where small datasets are common.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144564326","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}

引用次数: 0

Dosimetric investigation of a rotating gamma ray system. 旋转伽马射线系统的剂量学研究。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-21 DOI: 10.1088/2057-1976/adecab

A Eldib, Veltchev I, L Chen, R Price, C-M Ma

{"title":"Dosimetric investigation of a rotating gamma ray system.","authors":"A Eldib, Veltchev I, L Chen, R Price, C-M Ma","doi":"10.1088/2057-1976/adecab","DOIUrl":"10.1088/2057-1976/adecab","url":null,"abstract":"Background. Radiosurgery has become an important treatment alternative to surgery for a variety of intracranial lesions. All commercially available systems use convergent beam techniques, but they differ in their treatment delivery methods depending on the machine design and workspace.Purpose. The aim of this work is to investigate a new design for a gamma ray system developed for both intra and extra-cranial stereotactic body radiation therapy (SBRT).Methods. Monte Carlo simulations have been conducted to evaluate rotational radiation delivery using Cobalt-60 gamma beams as compared to linac beams with higher energies. A rotating gamma ray system (RGS), has been modeled using the MCBEAM Monte Carlo code. Treatment plans have been generated utilizing MCPLAN, which is an in-house Monte Carlo treatment planning system. Dosimetric differences between RGS Cobalt-60 beams and Robotic arm linac (RAL) 6 MV beams have been compared in a lung phantom and for previously treated SBRT patients.Results. Results showed that the need for high-energy photon beams decreases with rotational delivery treatments. Cobalt-60 beams could provide a reasonable compromise between beam penetration and penumbra characteristics for lung SBRT applications. The proper combination of available collimator cone sizes and various oblique beam angles allows RGS to shape the isodose lines effectively to match the target volume. The treatment plan quality for RGS has been comparable to that of RAL for both intra- and extra cranial cases. Intensity modulated arcs are feasible with RGS and can add more planning capabilities.Conclusions. The rotating design of the RGS can be of clinical benefit for stereotactic radiation therapy treating cranial cases plus the added ability of treating extra-cranial cases.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582962","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}

引用次数: 0

Statistical toolkit for analysis of radiotherapy DICOM data. 放射治疗DICOM数据分析统计工具包。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-17 DOI: 10.1088/2057-1976/ade9cb

Marvin Kinz, Christina Molodowitch, Joseph Killoran, Jürgen Hesser, Piotr Zygmanski

{"title":"Statistical toolkit for analysis of radiotherapy DICOM data.","authors":"Marvin Kinz, Christina Molodowitch, Joseph Killoran, Jürgen Hesser, Piotr Zygmanski","doi":"10.1088/2057-1976/ade9cb","DOIUrl":"10.1088/2057-1976/ade9cb","url":null,"abstract":"Background:Radiotherapy (RT) has become increasingly sophisticated, necessitating advanced tools for analyzing extensive treatment data in hospital databases. Such analyses can enhance future treatments, particularly through Knowledge-Based Planning, and aid in developing new treatment modalities like convergent kV RT.Purpose:The objective is to develop automated software tools for large-scale retrospective analysis of over 10,000 MeV x-ray radiotherapy plans. This aims to identify trends and references in plans delivered at our institution across all treatment sites, focusing on: (A) Planning-Target-Volume, Clinical-Target-Volume, Gross-Tumor-Volume, and Organ-At-Risk (PTV/CTV/GTV/OAR) topology, morphology, and dosimetry, and (B) RT plan efficiency and complexity.Methods:The software tools are coded in Python. Topological metrics are evaluated using principal component analysis, including center of mass, volume, size, and depth. Morphology is quantified using Hounsfield Units, while dose distribution is characterized by conformity and homogeneity indexes. The total dose within the target versus the body is defined as the Dose Balance Index.Results:The primary outcome of this study is the toolkit and an analysis of our database. For example, the mean minimum and maximum PTV depths are about 2.5±2.3 cm and 9±3 cm, respectively.Conclusions:This study provides a statistical basis for RT plans and the necessary tools to generate them. It aids in selecting plans for knowledge-based models and deep-learning networks. The site-specific volume and depth results help identify the limitations and opportunities of current and future treatment modalities, in our case convergent kV RT. The compiled statistics and tools are versatile for training, quality assurance, comparing plans from different periods or institutions, and establishing guidelines. The toolkit is publicly available athttps://github.com/m-kinz/STAR.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144526384","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}

引用次数: 0

Artificial intelligence techniques in inherited retinal diseases: a review. 人工智能技术在遗传性视网膜疾病中的应用综述。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-16 DOI: 10.1088/2057-1976/ade9c7

Han Trinh, Jordan Vice, Zahra Tajbakhsh, Jason Charng, Khyber Alam, Fred K Chen, Ajmal Mian

{"title":"Artificial intelligence techniques in inherited retinal diseases: a review.","authors":"Han Trinh, Jordan Vice, Zahra Tajbakhsh, Jason Charng, Khyber Alam, Fred K Chen, Ajmal Mian","doi":"10.1088/2057-1976/ade9c7","DOIUrl":"10.1088/2057-1976/ade9c7","url":null,"abstract":"Inherited retinal diseases (IRDs) are a diverse group of genetic disorders that lead to progressive vision loss and are a major cause of blindness in working-age adults. The complexity and heterogeneity of IRDs pose significant challenges in diagnosis, prognosis, and management. Recent advancements in artificial intelligence (AI) offer promising solutions to these challenges. However, the rapid development of AI techniques and their varied applications have led to fragmented knowledge in this field. This review consolidates existing studies, identifies gaps, and provides an overview of AI's potential in diagnosing and managing IRDs. It aims to structure pathways for advancing clinical applications by exploring AI techniques like machine learning and deep learning, particularly in disease detection, progression prediction, and personalized treatment planning. Additionally, the integration of explainable AI is discussed, emphasizing its importance in clinical settings to improve transparency and trust in AI-based systems. The review addresses the need to bridge existing gaps in focused studies on AI's role in IRDs, offering a structured analysis of current AI techniques and outlining future research directions. It concludes with an overview of the challenges and opportunities in deploying AI for IRDs, highlighting the need for interdisciplinary collaboration and the continuous development of robust, interpretable AI models to advance clinical applications.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144526380","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}

引用次数: 0

Long-term potentiation and long-term depression are both impaired afterin vitrostretch injury measured with stretchable microelectrode arrays. 用可拉伸微电极阵列测量体外拉伸损伤后的长时程增强和长时程抑制均受损。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-14 DOI: 10.1088/2057-1976/adea7e

Mary Kate R Dwyer, Isabella Polsfuss, Keondre Herbert, Nevin Varghese, Barclay Morrison

{"title":"Long-term potentiation and long-term depression are both impaired afterin vitrostretch injury measured with stretchable microelectrode arrays.","authors":"Mary Kate R Dwyer, Isabella Polsfuss, Keondre Herbert, Nevin Varghese, Barclay Morrison","doi":"10.1088/2057-1976/adea7e","DOIUrl":"10.1088/2057-1976/adea7e","url":null,"abstract":"Objective. Traumatic brain injury (TBI) is a prevalent injury that can lead to long term deficits in memory and cognition. Predicting which patients will have long lasting memory issues following mild TBI is challenging.Approach.Organotypic hippocampal slice cultures were biaxially stretched to model a TBI. In thisin vitromodel, stretchable microelectrode arrays were embedded within the culture substrate to both deform the adhered culture and record neural signals, which are indicators of neuronal health and network connectivity. Multiple spontaneous and evoked recordings were obtained while maintaining sterility to study and modulate the electrophysiological response to injury.Main results. In the first set of experiments, neural signals were measured 2 and 24 h after stretch injury. Bursting activity increased 2 h after injury but returned to baseline by 24 h. However, 24 h after injury, both long-term potentiation (LTP) and long-term depression (LTD) were impaired. In another experiment, LTP was induced multiple times, both 24 h before and 24 h after injury, to study how the state of the pre-injury network affected electrophysiological outcome after injury. We provide preliminary evidence that induction of LTP before injury to increase synaptic strength was detrimental to neuronal plasticity (LTP) after injury. Future studies can use the stretchable microelectrode arrays and our induction paradigm to test if induction of LTD, a weakening of synaptic strength, could increase resiliency to injury.Significance.This research begins to examine the role of pre-injury network connectivity and synaptic strength on post-traumatic electrophysiological outcomes, which may increase understanding of the determinants of heterogeneous clinical outcomes in mild TBI.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12257917/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144537899","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}

引用次数: 0

A feasibility study of a computational modeling system for performance evaluation and development of ultrasound strain elastography systems. 超声应变弹性成像系统性能评估与开发计算建模系统的可行性研究。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-14 DOI: 10.1088/2057-1976/adeb91

Marjan Bakhtiari-Nejad, Nima Akhlaghi, Reza Zahiri Azar, Yunbo Liu, Marjan Nabili, Brian Garra

{"title":"A feasibility study of a computational modeling system for performance evaluation and development of ultrasound strain elastography systems.","authors":"Marjan Bakhtiari-Nejad, Nima Akhlaghi, Reza Zahiri Azar, Yunbo Liu, Marjan Nabili, Brian Garra","doi":"10.1088/2057-1976/adeb91","DOIUrl":"10.1088/2057-1976/adeb91","url":null,"abstract":"Ultrasound strain elastography (USE) is an imaging technology that enables us to detect changes in tissue stiffness resulting from cancer and other diseases. The objective of this study is to computationally model the application of USE for breast lesion characterization. We develop a well-defined simulation pipeline using open-source software to createin silicoUSE phantoms with one and two stiff targets. First, we use FreeCAD software for tissue 3D modeling and Gmsh software for finite element (FE) meshes. Second, we place randomly positioned point scatterers within the meshed models to form pre-deformation virtual ultrasound phantoms. Then, a simulated ultrasound transducer is used to compress and deform tissue in FE simulations using FEBio software to create a post-deformation virtual ultrasound phantom. Third, we use the k-Wave acoustics toolbox to generate pre- and post-deformation ultrasound echo signals and B-mode images. Finally, we estimate axial and lateral displacements using a speckle tracking method, and strain elastograms, using a least-squares method. Displacements from the USE simulation pipeline and phantom experiments were compared against true FEBio-simulated displacements for accuracy. We have also quantitatively compared the resultant strain elastograms obtained from FEBio simulations, USE simulation pipeline, and phantom experiments. Finally, model validation is performed by comparing the performance of the USE software platform and physical phantom experiments for a range of compression values (0.5%-5% axial strain). The results confirm the use of the well-validated USE simulation pipeline as a robust non-clinical assessment tool for USE system development.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144558926","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}

引用次数: 0

Efficacy of age, menopause, and dental radiographic measures in identifying women at risk of spine Osteoporosis: an investigation panorama. 年龄、绝经期和牙科x线测量在识别女性脊柱骨质疏松风险中的有效性：一项调查全景。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-10 DOI: 10.1088/2057-1976/adeab6

Kathirvelu D, Parimala D, Vinupritha P, Anitha G, S P Angeline Kirubha, Kamalakkannan S, Kalpana V

{"title":"Efficacy of age, menopause, and dental radiographic measures in identifying women at risk of spine Osteoporosis: an investigation panorama.","authors":"Kathirvelu D, Parimala D, Vinupritha P, Anitha G, S P Angeline Kirubha, Kamalakkannan S, Kalpana V","doi":"10.1088/2057-1976/adeab6","DOIUrl":"10.1088/2057-1976/adeab6","url":null,"abstract":"Background.Osteoporosis is a vulnerable condition that results in fragile bones and affects the quality of life of the concerned individuals and their family.Aim. The study is to estimate bone mineral density (BMD) at lumbar spine and investigate the influence of age, menopause and dental radiographic indicators in the assessment of osteoporosis.Materials and methods. The study involved 74 women aged 57.3 ± 11.9 years. All participants underwent BMD scans using a central DXA scanner (DPX Prodigy DXA Scanner; GE Lunar Corporation, Madison, WI, USA) and Orthopantomogram (OPG) using an Orthopantomogram scanner (Carestream CS8100 Dental OPG Machine). Radiographic assessments and image processing techniques were used to determine mandibular cortical width (MCW) and trabecular bone content (TBC). The participants were divided into three groups based on the lumbar spine T-score as Control, Osteopenia and Osteoporosis. Stepwise multivariate linear regression analysis was conducted to estimate AP (L1-L4) spine BMD (sBMD).Results.MCW, TBC and sBMD revealed a strong correlation (p < 0.01) with sBMD measured using DXA. MCW and TBC decreased by 18.5% and 4% respectively among osteoporotic subjects in comparison with the control group. MCW suffers a steep fall after 47.5 years and furthermore MCW, TBC and BMD decreased by 22.2%, 4.3% and 15.5%, respectively among the post-menopausal women. The sBMD exhibited (AUC = 0.837) in discriminating with low spine BMD.Conclusion.A threshold of MCW ≤ 2.4 mm and TBC ≤ 0.44 could be set as a baseline for south Indian women who require further assessment of osteoporosis.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144551845","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}

引用次数: 0

Enhancing surface electromyographic signal recognition accuracy for trans-radial amputees using broad learning systems. 使用广泛学习系统提高跨桡骨截肢者表面肌电信号识别的准确性。

IF 1.3

Biomedical Physics & Engineering Express Pub Date : 2025-07-10 DOI: 10.1088/2057-1976/adee28

Lei Zhang, Xuemei Zhang

{"title":"Enhancing surface electromyographic signal recognition accuracy for trans-radial amputees using broad learning systems.","authors":"Lei Zhang, Xuemei Zhang","doi":"10.1088/2057-1976/adee28","DOIUrl":"https://doi.org/10.1088/2057-1976/adee28","url":null,"abstract":"Gesture recognition based on surface electromyography (sEMG) plays a crucial role in human-computer interaction. By analyzing sEMG signals generated from residual forearm muscle activity in trans-radial amputees, it is possible to predict their hand movement intentions, enabling the control of myoelectric prostheses. Previous studies on gesture classification for trans-radial amputees have shown that as the number of hand movement types increases, the accuracy of gesture classification significantly decreases. To this end, this paper proposed a novel approach that integrates image feature flattening (IFF) with broad learning system (BLS). The IFF method mapped data features into a three-dimensional image, which was then converted to grayscale and flattened into a one-dimensional vector. Finally, it was used as input to the BLS network for precise gesture classification. The proposed method was validated on 49 hand movement data from radial amputees in the Ninapro DB3 dataset. The results showed that the method not only significantly reduced classification time but also achieved a gesture recognition accuracy of up to 98.1%, demonstrating its strong potential for application in gesture recognition for trans-radial amputees.&#xD.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144607189","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}

引用次数: 0