Journal of Medical Engineering and Technology最新文献_第6页

Progressive X-ray tube degradation detected via daily mammography quality control. 通过日常乳房x线摄影质量控制检测进行性x射线管退化。

Journal of Medical Engineering and Technology Pub Date : 2026-01-01 Epub Date: 2025-10-07 DOI: 10.1080/03091902.2025.2553132

Túlio Guilherme Soares Marques, Diana Rodrigues de Pina, Matheus Alvarez

{"title":"Progressive X-ray tube degradation detected via daily mammography quality control.","authors":"Túlio Guilherme Soares Marques, Diana Rodrigues de Pina, Matheus Alvarez","doi":"10.1080/03091902.2025.2553132","DOIUrl":"10.1080/03091902.2025.2553132","url":null,"abstract":"This study evaluated whether routine daily quality control (QC) tests can anticipate X-ray tube degradation in a digital mammography system. Over 30 months, tube loading, contrast-to-noise ratio (CNR), and image quality scores were extracted from daily QC tests and analysed alongside a documented tube failure in September 2024. These results were compared with annual tube output measurements and environmental data. A progressive rise in tube loading was observed prior to tube failure, increasing from 84.45 to 94.58 mAs (12.0%). The Mann-Kendall test confirmed a significant upward trend (τ = 0.461; p < 0.001), with Sen's slope indicating +0.19 mAs/month. Despite this, CNR values remained stable (mean = 14.76 ± 0.20), and image quality showed no degradation. However, tube output declined consistently (from 30.95 ± 3.08 to 28.76 ± 0.36 μGy/mAs), confirming reduced efficiency. Temperature and humidity remained within recommended limits. These findings suggest that gradual increases in tube loading can indicate early tube degradation, even when image quality remains unaffected. Beyond confirming equipment performance, daily QC may serve as a strategic tool to detect early signs of degradation, extend device lifespan, reduce unplanned downtime, and promote patient safety without added costs.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145240046","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

Development of a low-cost laparoscopic appendicectomy simulation model with automated progress tracking: enhancing surgical training through innovation and accessibility. 具有自动进度跟踪的低成本腹腔镜阑尾切除术模拟模型的开发：通过创新和可及性加强手术训练。

Journal of Medical Engineering and Technology Pub Date : 2026-01-01 Epub Date: 2025-10-21 DOI: 10.1080/03091902.2025.2570160

Bishow Bekhyat Karki, Swodesh Sharma, Puskar Neupane, Shashwot Shrestha, Sushil Phuyal, Josephine Walshaw, Sanjivan Satyal, Mahmoud Loubani

{"title":"Development of a low-cost laparoscopic appendicectomy simulation model with automated progress tracking: enhancing surgical training through innovation and accessibility.","authors":"Bishow Bekhyat Karki, Swodesh Sharma, Puskar Neupane, Shashwot Shrestha, Sushil Phuyal, Josephine Walshaw, Sanjivan Satyal, Mahmoud Loubani","doi":"10.1080/03091902.2025.2570160","DOIUrl":"10.1080/03091902.2025.2570160","url":null,"abstract":"Laparoscopic surgery has become the standard for many surgical procedures globally, including laparoscopic Appendicectomy. However, access to adequate training, particularly in lower and middle-income countries (LMICs) remains challenging, impacting surgical proficiency and patient outcomes. This paper presents the development of a Laparoscopic Appendicectomy Simulation (LaApSi) model, a silicone-based, low-cost solution designed to enhance laparoscopic skills training, particularly in resource-constrained settings. The LaApSi model was developed by creating a negative mould based on anatomically accurate dimensions. High-grade silicone was used to replicate the texture of human tissue. The model integrates strategically placed assessment electronics with an Automated Progress Tracking System (APTS), offering real-time feedback on surgical manoeuvres and tracking trainee progress during simulations. The model is cost-effective, with initial production costs of £12.69 for the docking system and negative mould. This system can be used with multiple LaApSi models, each costing only £0.66 to produce. Equipped with the APTS, the LaApSi model provides a realistic and affordable option for simulation-based training in laparoscopic appendicectomy. Its cost-effectiveness and automated progress tracking make it a viable option for widespread adoption, particularly in LMICs. Additionally, the production methodology is adaptable to other laparoscopic procedures, presenting opportunities for broader applications in surgical education and training.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"75-81"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145349119","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

Developing an intelligent model to detect the level of diabetic retinopathy using blood vessel pattern extraction in retinal images. 开发了一种基于视网膜图像血管模式提取的糖尿病视网膜病变智能检测模型。

Journal of Medical Engineering and Technology Pub Date : 2026-01-01 Epub Date: 2025-09-05 DOI: 10.1080/03091902.2025.2553137

Fatemeh Darakhshan, Hamid Reza Naji

{"title":"Developing an intelligent model to detect the level of diabetic retinopathy using blood vessel pattern extraction in retinal images.","authors":"Fatemeh Darakhshan, Hamid Reza Naji","doi":"10.1080/03091902.2025.2553137","DOIUrl":"10.1080/03091902.2025.2553137","url":null,"abstract":"Diabetic retinopathy is a chronic and progressive eye disease in which the human retina is affected by an increase in the amount of insulin in the blood. Diabetic retinopathy, if not detected and treated in time, threatens the patient's vision and eventually causes complete blindness. Among various clinical symptoms, microaneurysm appears as the first sign of diabetic retinopathy. Accurate and reliable detection of microaneurysms is a challenging problem due to its small size and low contrast. The successful detection of microaneurysms will be more useful for the proper treatment of the disease in its early stages. In this paper, we present a method for classifying medical images of the retina to accurately detect the level of development of diabetic retinopathy. Our proposed method has six main steps. In steps one to four, the input image is pre-processed. In the first step; the detection and segmentation of blood vessels using the morphological closing operation is done. The second step; performs circular edge detection using gradient morphological operation. The third step; optical disc detection using the circular Hough transform edge detection method is done. The fourth step; the detection and segmentation of microaneurysms is done by removing blood vessels, circular edges, and optical discs and we use circular Hough transformation. In the fifth step, feature extraction is performed by considering two features, blood vessel area and microaneurysm area, and four features obtained from the gray level co-occurrence matrix. Finally, the sixth step is classification using the SVM classifier (Gaussian kernel function). We evaluated the performance of the model using EyePacs retinal fundus image database and obtained 95.20% and 97% accuracy and specificity, respectively. Experimental results show that our proposed model performs better in terms of evaluated measures compared to other methods.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"9-22"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001588","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

Novel BDefRCNLSTM: an efficient ensemble deep learning approaches for enhanced brain tumor detection and categorization with segmentation. 新型BDefRCNLSTM：一种有效的集成深度学习方法，用于增强脑肿瘤检测和分割分类。

Journal of Medical Engineering and Technology Pub Date : 2026-01-01 Epub Date: 2025-09-11 DOI: 10.1080/03091902.2025.2555950

Malathi Janapati, Shaheda Akthar

{"title":"Novel BDefRCNLSTM: an efficient ensemble deep learning approaches for enhanced brain tumor detection and categorization with segmentation.","authors":"Malathi Janapati, Shaheda Akthar","doi":"10.1080/03091902.2025.2555950","DOIUrl":"10.1080/03091902.2025.2555950","url":null,"abstract":"Brain tumour detection and classification are critical for improving patient prognosis and treatment planning. However, manual identification from magnetic resonance imaging (MRI) scans is time-consuming, error-prone, and reliant on expert interpretation. The increasing complexity of tumour characteristics necessitates automated solutions to enhance accuracy and efficiency. This study introduces a novel ensemble deep learning model, boosted deformable and residual convolutional network with bi-directional convolutional long short-term memory (BDefRCNLSTM), for the classification and segmentation of brain tumours. The proposed framework integrates entropy-based local binary pattern (ELBP) for extracting spatial semantic features and employs the enhanced sooty tern optimisation (ESTO) algorithm for optimal feature selection. Additionally, an improved X-Net model is utilised for precise segmentation of tumour regions. The model is trained and evaluated on Figshare, Brain MRI, and Kaggle datasets using multiple performance metrics. Experimental results demonstrate that the proposed BDefRCNLSTM model achieves over 99% accuracy in both classification and segmentation, outperforming existing state-of-the-art approaches. The findings establish the proposed approach as a clinically viable solution for automated brain tumour diagnosis. The integration of optimised feature selection and advanced segmentation techniques improves diagnostic accuracy, potentially assisting radiologists in making faster and more reliable decisions.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"35-55"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145041663","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

Fabrication and experimental analysis of a novel flexible keel prosthetic foot utilizing functionally graded materials. 新型功能梯度材料柔性龙骨假肢足的制备与实验分析。

Journal of Medical Engineering and Technology Pub Date : 2026-01-01 Epub Date: 2025-10-06 DOI: 10.1080/03091902.2025.2570158

Ehab N Abbas, Kadhim K Resan, Muhsin J Jweeg, Emad K Njim, Royal Madan

{"title":"Fabrication and experimental analysis of a novel flexible keel prosthetic foot utilizing functionally graded materials.","authors":"Ehab N Abbas, Kadhim K Resan, Muhsin J Jweeg, Emad K Njim, Royal Madan","doi":"10.1080/03091902.2025.2570158","DOIUrl":"10.1080/03091902.2025.2570158","url":null,"abstract":"The present study performs the fabrication and experimental performance analysis of a novel flexible keel prosthetic foot made up of functionally graded materials (FGMs). To obtain the desired mechanical properties, the keel of the prosthetic foot was fabricated by combining wood and carbon fibre-reinforced polymer (CFRP). The FGM in the foot was introduced by creating layers of a blend of burnt rice husk particles and silica rubber with different weight percentages (2%, 4%, 6%, 8%, 10%, and 12%). Moreover, a casting was performed to develop a keel prosthetic foot using a metal mould. Experimental tests were conducted to investigate the foot performance and compared with Solid Ankle Cushion Heel (SACH) foot designs by carrying out tests such as tensile test, hardness test, dorsiflexion analysis, and fatigue testing. Fatigue life and dorsiflexion angle values are found to be higher for the proposed design in comparison to the SACH foot. This study presents important insights into the potential benefits and practicality of using flexible keel prosthetic feet made from functionally graded materials. The enhanced mechanical characteristics and tailored design of these prosthetic feet can significantly improve user comfort, stability, and overall biomechanical performance.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"56-64"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145240052","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

Development of a low-cost insulin infusion pump software simulator: a case study with a Brazilian company. 低成本胰岛素输注泵软件模拟器的开发：以一家巴西公司为例。

Journal of Medical Engineering and Technology Pub Date : 2026-01-01 Epub Date: 2025-09-04 DOI: 10.1080/03091902.2025.2554851

Felipe Dos Santos Rocha, Luiz Eduardo Galvão Martins, Tiago de Oliveira, Sebastião Vagner Arêdes, Sergio Atala Dib, Dulce Elena Casarini, Juliana Almada Colucci, Monica Andrade Lima Gabbay, Tatiana Sousa Cunha

{"title":"Development of a low-cost insulin infusion pump software simulator: a case study with a Brazilian company.","authors":"Felipe Dos Santos Rocha, Luiz Eduardo Galvão Martins, Tiago de Oliveira, Sebastião Vagner Arêdes, Sergio Atala Dib, Dulce Elena Casarini, Juliana Almada Colucci, Monica Andrade Lima Gabbay, Tatiana Sousa Cunha","doi":"10.1080/03091902.2025.2554851","DOIUrl":"10.1080/03091902.2025.2554851","url":null,"abstract":"The purpose of this paper is to describe the development of a low-cost insulin infusion pump software simulator. The simulator was built using Java programming language and replicates the interface and functions of a real low-cost insulin infusion pump currently under development. Potential users participated in a remote session, and assessment was conducted using a standard usability scale (SUS). With a sample size of 34 participants possessing different levels of knowledge regarding diabetes and infusion pumps, the mean SUS score obtained was 67.43. While the insulin infusion pump is a specialised device and its system may not be immediately familiar to all users, the results suggest that usability can improve with appropriate training and clinical support. Employing a simulation model during the development of the physical prototype may provide advantages for system design, safety, and effectiveness in health care technology delivery.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"23-34"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001672","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

Heart rate study using the cardiac sounds. 使用心音进行心率研究。

Journal of Medical Engineering and Technology Pub Date : 2026-01-01 Epub Date: 2025-10-10 DOI: 10.1080/03091902.2025.2570159

Abdelhakim Souidi, Amine Debbal, Fadia Meziani

{"title":"Heart rate study using the cardiac sounds.","authors":"Abdelhakim Souidi, Amine Debbal, Fadia Meziani","doi":"10.1080/03091902.2025.2570159","DOIUrl":"10.1080/03091902.2025.2570159","url":null,"abstract":"The purpose of this paper is to present a straightforward framework for Heart Rate (HR) estimation from a Phonocardiogram (PCG) record and study the association between murmur severity levels and HR. The system focuses primarily on data processing procedure, which is based on signal preprocessing using Maximal Overlap Discrete Wavelet Transform (MODWT) to delineate murmurs from heart sounds. We exploit the characteristics of Logistic function to derive an enhanced PCG envelope that serves as prerequisite for HR algorithm detection. In fact, the PCG envelope presents a cyclostationarity that can be easily detected throughout a cross-covariance autocorrelation function to calculate the Heart Rate (HR). In addition, the effect of minor and pronounced murmurs is gauged by the Energetic Ratio (ER) that provides a comprehensive idea about the superimposed murmur energy on first and second Heart sounds. The study was conducted on PASCAL dataset with 335 real clinical records. Results shows that mild murmurs with low ER are not associated with HR (p-value = 0.846). However, moderate-severe murmurs indicate a significant association with HR (p-value = 0.0002). Furthermore, HR decreases as Energetic Ratio increases. These findings could be valuable to medical professionals operating in the emergency departments.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"65-74"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145276221","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

News and product update. 新闻和产品更新。

Journal of Medical Engineering and Technology Pub Date : 2025-11-20 DOI: 10.1080/03091902.2025.2581928

引用次数: 0

A review on the mechanical characterization of human atherosclerotic plaque. 人类动脉粥样硬化斑块力学特性的研究进展。

Journal of Medical Engineering and Technology Pub Date : 2025-11-01 Epub Date: 2025-08-07 DOI: 10.1080/03091902.2025.2540128

Subraya Krishna Bhat

{"title":"A review on the mechanical characterization of human atherosclerotic plaque.","authors":"Subraya Krishna Bhat","doi":"10.1080/03091902.2025.2540128","DOIUrl":"10.1080/03091902.2025.2540128","url":null,"abstract":"Atherosclerosis poses a significant health burden globally, contributing to a major proportion of all deaths in westernised societies. Atherosclerosis involves deposition of fat, cholesterol, calcium, and other substances on the inner walls of the artery, collectively called plaques, which finally manifests in various clinical forms, such as ischaemic heart disease and stroke. There have been consistent efforts to characterise and analyse the severity of plaques to devise comprehensive strategies targeting risk factors, early detection, and effective management. This article presents a broad overview of the mechanical characterisation of human atherosclerotic plaque, drawing from a diverse array of technical literature. The studies emphasise the importance of accurately assessing the mechanical behaviour of these plaques to better understand their pathophysiology and clinical implications. Advanced techniques, including experimental and computational hybrid approaches, provide insights into the complex mechanical properties of atherosclerotic plaques. In-silico analysis is found to be a valuable tool for investigating the mechanical behaviour of atherosclerotic tissues, particularly in plaques with softer fibrotic tissues. Overall, this review underscores the importance of advancing our understanding of the mechanical properties of human atherosclerotic plaque for improved risk stratification, patient management, and the development of targeted interventions to mitigate the burden of cardiovascular diseases.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"329-343"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144795806","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 cognitive state detection through deep Forest-based electroencephalogram signal analysis and classification. 通过基于深度森林的脑电图信号分析和分类增强认知状态检测。

Journal of Medical Engineering and Technology Pub Date : 2025-11-01 Epub Date: 2025-08-15 DOI: 10.1080/03091902.2025.2544802

Geetha S, Geetha R

{"title":"Enhancing cognitive state detection through deep Forest-based electroencephalogram signal analysis and classification.","authors":"Geetha S, Geetha R","doi":"10.1080/03091902.2025.2544802","DOIUrl":"10.1080/03091902.2025.2544802","url":null,"abstract":"The impacts of cognitive tasks on the brain through Electroencephalogram (EEG) signal analysis have commonly employed machine learning models like Support Vector Machines (SVMs), Artificial Neural Networks (ANNs), random forests etc. However, these traditional models may encounter limitations in effectively addressing the unique challenges inherent in EEG signal analysis, including high dimensionality and the potential presence of noise and artefacts. This critique underscores the need for advanced methodologies, capable of navigating these challenges to enhance the accuracy and reliability of cognitive task-related EEG studies. This study addresses the challenge of accurately detecting cognitive states using EEG signals. This helps in overcoming the challenges by high dimensionality, non-stationarity, and noise in raw EEG data. Traditional classifiers such as SVMs and ANNs often fail to fully exploit the temporal and frequency features present in EEG. In order to overcome these limitations, this work introduces a novel Deep Forest-based classification model. This model is optimised through XGBoost for feature selection. A self-acquired dataset using the g.Nautilus EEG device from 12 student volunteers performing cognitive tasks forms the basis of the evaluation. A total of 48 features, spanning time, frequency, entropy, and autoregressive domains, are extracted. The proposed model achieves high classification accuracy (99.692%) while reducing computational time. This method demonstrates strong potential for real-time cognitive monitoring in neuroscience and human-computer interaction contexts.","PeriodicalId":39637,"journal":{"name":"Journal of Medical Engineering and Technology","volume":" ","pages":"407-426"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144859711","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