Medical Engineering & Physics最新文献

{"title":"Assessment of pre- and post-operative gait dynamics in total knee arthroplasty by a wearable capture system","authors":"Zhuoxi Bi ,&nbsp;Wenquan Cui ,&nbsp;Luming Feng ,&nbsp;Yaxin Liu ,&nbsp;Xin Ma ,&nbsp;Shihao Li ,&nbsp;Changle Ren ,&nbsp;Liming Shu","doi":"10.1016/j.medengphy.2025.104309","DOIUrl":"10.1016/j.medengphy.2025.104309","url":null,"abstract":"<div><h3>Background</h3><div>Walking function reconstruction is suboptimal after total knee arthroplasty. However, a comprehensive investigation of kinematic and kinetic parameters before and after total knee arthroplasty is lacking. This study aimed to quantitatively compare the differences in gait parameters before and after total knee arthroplasty with those of healthy control group.</div></div><div><h3>Methods</h3><div>This study utilized a wearable capture system to obtain gait parameters from pre- operative and one-year post- operative patients, as well as from the healthy control group. The parameters included walking speed, the stance phase percentage during the gait cycle, knee flexion angle, center of pressure trajectory, vertical ground reaction force, and its moment on the coronal plane of the knee joint.</div></div><div><h3>Results</h3><div>Post-total knee arthroplasty patients presented an averaged 12.5 % improvement in walking speed and an averaged 19.75 % increasement in the maximum knee flexion angle during the gait cycle, although both were still lower than those of the healthy control group. During the stance phase, the vertical ground reaction force exhibited a less pronounced double-hump feature, and compared to preoperative levels, the peak of the coronal plane moment of the knee was reduced by approximately half.</div></div><div><h3>Conclusion</h3><div>One-year post- total knee arthroplasty patients exhibited improved walking function compared to preoperative levels, but a gap remained compared to healthy control group. Additionally, preoperative gait abnormalities persisted postoperatively.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104309"},"PeriodicalIF":1.7,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394474","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 novel 3D lightweight model for COVID-19 lung CT Lesion Segmentation","authors":"Jingdong Yang ,&nbsp;Shaoyu Huang ,&nbsp;Han Wang ,&nbsp;Yuhang Lu ,&nbsp;Wei liu ,&nbsp;Yan Shen ,&nbsp;Xiaohong Fu","doi":"10.1016/j.medengphy.2025.104297","DOIUrl":"10.1016/j.medengphy.2025.104297","url":null,"abstract":"<div><div>3D-based medical image segmentation, offering enhanced spatial information compared to 2D slice-based methods, encounters challenges arising from factors such as a restricted clinical sample size, imbalanced foreground-background pixel distribution, and suboptimal generalization performance. To address these challenges, we propose a lightweight segmentation model tailored to 3D medical images. Employing the K-means algorithm, our approach efficiently extracts the Region of Interest (ROI) from medical images, facilitating lung area segmentation while minimizing interference from background pixels. We address the risk of model overfitting by adopting the Focal loss in conjunction with the Dice coefficient as our loss function. Feature extraction capabilities are bolstered through the incorporation of a parallel attention mechanism at skip connections, aiming to enhance the representation of both shallow and deep layers. Moreover, we optimize computational efficiency and memory utilization by substituting 3 × 3 convolutions with depth-wise separable convolutions and integrating residual connections for improved gradient propagation. The introduction of Ghost-inspired 1 × 1 convolution ensures consistent feature dimensions before and after residual connections. Experimental evaluation, conducted on a dataset comprising 199 COVID-19-Seg cases through 5-fold cross-validation, underscores the superior performance of our proposed model. Evaluation metrics, including Average Surface Distance (ASD), accuracy, sensitivity, Dice coefficient, and Intersection over Union (IOU) accuracy, yield values of 19.880, 99.90 %, 58.90 %, 56.10 %, and 41.00 %, respectively. In comparison to the other state-of-the-art segmentation models, our approach achieves heightened segmentation accuracy and generalization performance while incurring only a marginal increase in parameters and computational complexity.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104297"},"PeriodicalIF":1.7,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402751","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 patient-matched prosthesis for thumb amputations: Design, mechanical and functional evaluation","authors":"Federico Stacchiotti ,&nbsp;Chiara Bregoli ,&nbsp;Rubens Ferrari ,&nbsp;Jacopo Fiocchi ,&nbsp;Kavin Morellato ,&nbsp;Carlo Alberto Biffi ,&nbsp;Mattia Frascio ,&nbsp;Matilde Minuto ,&nbsp;Ausonio Tuissi ,&nbsp;Emanuele Gruppioni","doi":"10.1016/j.medengphy.2025.104296","DOIUrl":"10.1016/j.medengphy.2025.104296","url":null,"abstract":"<div><div>Thumb amputations strongly affect hand functionality in daily activities. The currently available solutions, such as microsurgical treatments and external vacuum prostheses present disadvantages, which can be successfully addressed through the osseointegration technique. However, despite its widespread use in oral applications, only a few osseointegrated solutions for the treatment of hand-finger amputations are available. Bone remaining limbs may have different lengths, diameters, and conditions and no patient-matched osseointegrated medical devices are available on the market. The manuscript presents the first patient-matched medical device for the treatment of thumb amputations. The prosthesis mainly consists of three components: an osseointegrated fixture which is implanted into the medullary canal of the bone remaining limb, an abutment, and an external digital prosthesis. The design phase is followed by computational and experimental analysis to optimize the design of each component attached to the osseointegrated fixture in order to preserve the implant fixture and bone. The maximum force generated during the pinch test in a healthy subject is approximately 80 N. The mechanical performance required during daily activities is achieved by the novel proposed device and the obtained results confirm that, in case of loads greater than daily ones, the failure may occur in the abutment component which is external to the body. A limitation of the current study consists in the lack of analysis on the bone-implant interface for which specific investigations would be required: currently, the contact between bone and fixture is assumed to be fixed, i.e. no micro motions are considered. Research is ongoing to test the entire device in a clinical study to collect quantitative and qualitative information from patients and surgeons.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104296"},"PeriodicalIF":1.7,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of surface type on outdoor gait parameters measured using an In-Shoe Motion Sensor System","authors":"Hiroki Shimizu ,&nbsp;Kyoma Tanigawa ,&nbsp;Anuradhi Bandara ,&nbsp;Shinichi Kawamoto ,&nbsp;Shota Suzuki ,&nbsp;Momoko Nagai-Tanima ,&nbsp;Tomoki Aoyama","doi":"10.1016/j.medengphy.2025.104295","DOIUrl":"10.1016/j.medengphy.2025.104295","url":null,"abstract":"<div><div>The objectives of this study were to measure outdoor gait parameters using an In-Shoe Motion Sensor System (IMS) and evaluate how different types of surfaces affect various gait dynamics. Accurate outdoor gait data are crucial for effective fall risk assessment because surface irregularities and tripping hazards often result in falls during walking. An IMS was used in this study to collect spatiotemporal, spatial, and foot parameters from 27 healthy adults walking on indoor asphalt, soil, and grass surfaces. Data were recorded during a 6-minute walk test, with measurements taken every 2 min and analyzed using the Statistical Package for the Social Sciences. The results showed significant differences in foot clearance, heel height, and gait cycle across surfaces. Walking on grass significantly increased foot height, swing time, and roll angle of heel contact. These findings may help develop interventions to prevent falls.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104295"},"PeriodicalIF":1.7,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ResGloTBNet: An interpretable deep residual network with global long-range dependency for tuberculosis screening of sputum smear microscopy images","authors":"Taocui Yan ,&nbsp;Yaqian Jin ,&nbsp;Shangqing Liu ,&nbsp;Qiuni Li ,&nbsp;Guowei Zuo ,&nbsp;Ziqian Ye ,&nbsp;Jin Li ,&nbsp;Baoru Han","doi":"10.1016/j.medengphy.2025.104300","DOIUrl":"10.1016/j.medengphy.2025.104300","url":null,"abstract":"<div><div>Tuberculosis is a high-mortality infectious disease. Manual sputum smear microscopy is a common and effective method for screening tuberculosis. However, it is time-consuming, labor-intensive, and has low sensitivity. In this study, we propose ResGloTBNet, a framework that integrates convolutional neural network and graph convolutional network for sputum smear image classification with high discriminative power. In this framework, the global reasoning unit is introduced into the residual structure of ResNet to form the ResGloRe module, which not only fully extracts the local features of the image but also models the global relationship between different regions in the image. Furthermore, we applied activation maximization and class activation mapping to generate explanations for the model's predictions on the test sets. ResGloTBNet achieved remarkable results on a publicly available dataset, reaching 97.2 % accuracy and 99.0 % sensitivity. It also maintained a high level of performance on a private dataset, attaining 98.0 % accuracy and 96.6 % sensitivity. In addition, interpretable analysis demonstrated that ResGloTBNet can effectively identify the features and regions in the input images that contribute the most to the model's predictions, providing valuable insights into the decision-making process of the deep learning model.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104300"},"PeriodicalIF":1.7,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419036","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 numerical simulation study of airway flow: Impact of bronchial stenosis","authors":"Mingqian Mao ,&nbsp;Zhichen Yang ,&nbsp;Mengting Li ,&nbsp;Xiaoyu Ni ,&nbsp;Changwang Pan","doi":"10.1016/j.medengphy.2025.104303","DOIUrl":"10.1016/j.medengphy.2025.104303","url":null,"abstract":"<div><div>Obstructive lung diseases, marked by airway stenosis, are chronic and pose significant mortality risks. This study aims to analyze airflow patterns in obstructed bronchi, comparing them to healthy airways during tidal breathing to improve our comprehension of disease effects on respiratory function. The current studies mostly overlook the specific morphology of the patient's upper airway or the elastic deformation of the airway soft tissues, which results in the existing results not being sufficient to effectively guide surgical treatment. In this paper, a realistic model of bronchial stenosis was obtained by CT data from a 71-year-old female patient. Full consideration was given to the nonlinear elastic material properties of the tracheal wall cartilage and smooth muscle and the dynamic changes in intra-pulmonary pressure, which are significant factors affecting the airflow field within the airway. The dynamic mesh technology and the Fluid-Structure Interaction (FSI) method, in conjunction with Computational Fluid Dynamics (CFD), were employed to analyze the impact of bilateral bronchial stenosis on the airflow state and the nonlinear mechanical behavior of the airway wall under different respiratory intensities. The simulation results exposed the distribution pattern of key parameters, such as airflow velocity, pressure, wall shear stress, and turbulent kinetic energy, indicating that bronchial stenosis significantly influences the air-flow motion, resulting in increased pressure, wall shear stress, and deformation of the airway wall. The finding revealed that the maximum airflow velocity, pressure, and wall shear stress all occurred in the stenosis areas of the bronchi, while the maximum deformation occurred on the smooth muscle side of the middle part of the main trachea. Additionally, turbulence occurs near the main trachea and carina, potentially related to airflow separation and local geometric changes. These insights contribute to a deeper understanding of the effects of bronchial stenosis on airway airflow dynamics and provide a scientific basis for the determination of clinical treatment plans and the prediction of treatment outcomes.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104303"},"PeriodicalIF":1.7,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430089","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 multi-attention deep architecture to stratify lung nodule malignancy from CT scans","authors":"Alejandra Moreno ,&nbsp;Andrea Rueda ,&nbsp;Fabio Martínez","doi":"10.1016/j.medengphy.2025.104305","DOIUrl":"10.1016/j.medengphy.2025.104305","url":null,"abstract":"<div><div>Lung cancer remains the principal cause of cancer-related deaths. Nodules are the main radiological finding, typically observed from low-dose CT scans. Nonetheless, the nodule characterization diagnosis remains subjective, reporting a moderate agreement among experts' observations, especially in identifying malignancy stratification. The proposed approach presents a deep multi-attention strategy, validated exhaustively to classify nodule masses according to four malignancy degrees. This work introduces a multi-attention architecture dedicated to stratifying nodules among malignancy stages. The architecture receives volumetric nodule regions and learns multi-scale saliency maps, focusing on determinant malignancy patterns of the observed masses. Specialized attention heads capture related patterns associated with lobulated, textural, and spiculated features. Validation includes an extensive analysis regarding multiple attention features, allowing to establish a correlation with other radiological findings. The proposed approach achieves an AUC of 85.35% for a classical multi-classification and a mean AUC of 82.90% in a one-vs-all validation methodology, showing competitive results in the state-of-the-art. The introduced architecture has capabilities to support nodule stratification and to classify nodule features. The exhaustive validation also suggests a proper generalization performance, which is a potential property to transfer this strategy in real scenarios.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104305"},"PeriodicalIF":1.7,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376673","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":"Enhancing assistive technology design: Biomechanical finite element modeling for grasping strategy optimization in exoskeleton data gloves","authors":"Yan Zhang,&nbsp;Hong Xie,&nbsp;Md All Amin Newton","doi":"10.1016/j.medengphy.2025.104308","DOIUrl":"10.1016/j.medengphy.2025.104308","url":null,"abstract":"<div><div>This paper endeavors to enhance the control mechanisms governing the grasping strategy of exoskeleton data gloves. A comprehensive approach was devised, integrating finite element numerical simulation techniques with the computerized control system of exoskeleton data gloves, establishing a novel, precise, and three-dimensional biomechanical finite element model of the hand. By amalgamating finite element modeling technology, biomechanical understanding, and hand kinematics, a straightforward yet efficient virtual grasping methodology was introduced to replicate three typical grasping actions dynamically. This method accurately computes contact pressure values, offering valuable insights for formulating strategies for exoskeleton data gloves. Experimental validations were conducted to ascertain the model's simulation accuracy, comparing contact pressure across all fingertips during grasping tasks demonstrating the model's high fidelity. Compared to traditional methods reliant on pressure sensors and physical measurement experiments, this approach presents several advantages, including convenience, speed, low cost, and enhanced accuracy. The proposed finite element numerical simulation model presents an optimized and viable concept for developing grasping strategies in exoskeleton data gloves, facilitating precise gripping capabilities for individuals and aiding in enhancing their capacity for independent living. Furthermore, the current model focuses on replicating typical grasping actions and may require further development to encompass a wider variety of complex object shapes and grasping maneuvers. However, this finding is crucial to the ongoing evolution of exoskeleton data glove products and systems.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104308"},"PeriodicalIF":1.7,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394472","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":"Enhanced intravascular lithotripsy (IVL) with ultrasound-shockwave catheter","authors":"Chengxi Li ,&nbsp;Rui Zhang ,&nbsp;Peiyang Li ,&nbsp;Weiwei Shao ,&nbsp;Yaoyao Cui","doi":"10.1016/j.medengphy.2025.104306","DOIUrl":"10.1016/j.medengphy.2025.104306","url":null,"abstract":"<div><div>Intravascular shockwave lithotripsy (IVL) is an effective treatment for vascular calcification. Previous studies suggest that ultrasound can enhance the efficiency of extracorporeal shockwave lithotripsy (ESWL) by mitigating the bubble shielding effect. We developed a novel ultrasound-shockwave catheter that combines flowing liquid and ultrasound to suppress bubble shielding and enhance lithotripsy efficiency. Experimental results confirm the bubble shielding effect in IVL, which can be mitigated by flowing liquid or ultrasound. Fracture experiments using Ultracal-30 as phantoms demonstrate the ultrasound emitted after 10 ms of shockwave generation and combines with bubbles can enhance lithotripsy efficiency. Specifically, the addition of ultrasound and bubbles reduced the mass percentage of fragments larger than 4.5 mm by 38.56 % compared to the control. Spectrum analysis of ultrasound reveals cavitation's role in improving lithotripsy efficiency. In summary, while bubbles initially attenuate shockwave intensity and reduce lithotripsy efficiency, their combination with ultrasound-induced cavitation enhances treatment outcomes.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104306"},"PeriodicalIF":1.7,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437415","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 comparative analysis of Constant-Q Transform, gammatonegram, and Mel-spectrogram techniques for AI-aided cardiac diagnostics","authors":"Mohammed Saddek Mekahlia ,&nbsp;Mohamed Fezari ,&nbsp;Ahcen Aliouat","doi":"10.1016/j.medengphy.2025.104302","DOIUrl":"10.1016/j.medengphy.2025.104302","url":null,"abstract":"<div><div>Cardiovascular diseases (CVDs) are the leading global cause of death, which requires the early and accurate detection of cardiac abnormalities. Abnormal heart sounds, indicative of potential cardiac problems, pose a challenge due to their low-frequency nature. Utilizing digital signal processing and Phonocardiogram (PCG) analysis, this study employs advanced deep learning techniques for automated heart sound classification. Time-frequency representations capture multiple heart sound features, including gammatonegram, Mel-spectrogram, and Constant-Q Transform (CQT). A Convolutional Neural Network with Directed Acyclic Graph (DAG-CNN) architecture is designed and rigorously evaluated, achieving high classification accuracies of 100%, 99.7%, and 99.5% for gammatonegram, Mel-spectrogram, and CQT, respectively. Comparative analysis with pre-trained CNN models demonstrates the superior performance of the proposed model. This advancement in automated heart sound classification offers a promising and cost-effective tool for early diagnosis, particularly in resource-limited settings, helping to address the diagnostic gap and enhance cardiac care accessibility.</div></div>","PeriodicalId":49836,"journal":{"name":"Medical Engineering & Physics","volume":"137 ","pages":"Article 104302"},"PeriodicalIF":1.7,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376674","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}