Medical & Biological Engineering & Computing最新文献_第10页

Hybrid model of feature-driven modular neural network-based grasshopper optimization algorithm for diabetic retinopathy classification using fundus images. 基于特征驱动模块化神经网络的混合算法用于眼底图像的糖尿病视网膜病变分类。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-08-01 Epub Date: 2025-03-06 DOI: 10.1007/s11517-025-03307-z

D Binny Jeba Durai, T Jaya

{"title":"Hybrid model of feature-driven modular neural network-based grasshopper optimization algorithm for diabetic retinopathy classification using fundus images.","authors":"D Binny Jeba Durai, T Jaya","doi":"10.1007/s11517-025-03307-z","DOIUrl":"10.1007/s11517-025-03307-z","url":null,"abstract":"Diabetic retinopathy (DR) is a progressive condition that can lead to blindness if undiagnosed or untreated. Automatic systems for DR prediction using fundus images have been developed, but challenges like variable illumination, overfitting, small datasets, poor feature learning, high computational complexity, and suboptimal feature weighting persist. To address these, a hybrid model called the modular neural network with grasshopper optimization algorithm (MNN-GOA) is proposed. This model integrates neural network capabilities with the grasshopper optimization algorithm (GOA) to enhance feature selection and classification accuracy. It begins with preprocessing to improve image quality, followed by data augmentation and histogram-based segmentation to focus on critical regions. Features are extracted using techniques like histogram of oriented gradients (HOG), scale-invariant feature transform (SIFT), color features, and mutual information (MI). GOA optimizes feature weights, balancing exploration and exploitation, while reducing computational complexity. The model integrates features from ground truth and original images to predict DR stages accurately. Achieving performance metrics of accuracy (98.8%), specificity (97.6%), sensitivity (96.8%), precision (96.4%), and F1 score (96.2%), the MNN-GOA model was validated on four datasets like DIARETDB1, DDR, APTOS 2019, and EyePACS and outperformed existing methods, proving to be a robust and efficient solution for DR classification and severity prediction.","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":"2423-2436"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143568598","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}

引用次数: 0

Paradigms and methods of noninvasive brain-computer interfaces in motor or communication assistance and rehabilitation: a systematic review. 非侵入性脑机接口在运动或交流辅助和康复中的范例和方法：系统综述。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-08-01 Epub Date: 2025-03-10 DOI: 10.1007/s11517-025-03340-y

Jianjun Meng, Yuxuan Wei, Ximing Mai, Songwei Li, Xu Wang, Ruijie Luo, Minghao Ji, Xiangyang Zhu

{"title":"Paradigms and methods of noninvasive brain-computer interfaces in motor or communication assistance and rehabilitation: a systematic review.","authors":"Jianjun Meng, Yuxuan Wei, Ximing Mai, Songwei Li, Xu Wang, Ruijie Luo, Minghao Ji, Xiangyang Zhu","doi":"10.1007/s11517-025-03340-y","DOIUrl":"10.1007/s11517-025-03340-y","url":null,"abstract":"Noninvasive brain-computer interfaces (BCIs) have rapidly developed over the past decade. This new technology utilizes magneto-electrical recording or hemodynamic imaging approaches to acquire neurophysiological signals noninvasively, such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). These noninvasive signals have different temporal resolutions ranging from milliseconds to seconds and various spatial resolutions ranging from centimeters to millimeters. Thanks to these neuroimaging technologies, various BCI modalities like steady-state visual evoked potential (SSVEP), P300, and motor imagery (MI) could be proposed to rehabilitate or assist patients' lost function of mobility or communication. This review focuses on the recent development of paradigms, methods, and applications of noninvasive BCI for motor or communication assistance and rehabilitation. The selection of papers follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), obtaining 223 research articles since 2016. We have observed that EEG-based BCI has gained more research focus due to its low cost and portability, as well as more translational studies in rehabilitation, robotic device control, etc. In the past decade, decoding approaches such as deep learning and source imaging have flourished in BCI. Still, there are many challenges to be solved to date, such as designing more convenient electrodes, improving the decoding accuracy and efficiency, designing more applicable systems for target patients, etc., before this new technology matures enough to benefit clinical users.","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":"2209-2233"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143587916","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}

引用次数: 0

Medical image-based 3D orthodontic wire optimization considering constraints at bracket and processing points. 考虑支架和加工点约束的基于医学图像的三维正畸线优化。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-08-01 DOI: 10.1007/s11517-025-03408-9

Youngwoo Kim, Ravindran Sajan Kumar, Jonghae Kim

引用次数: 0

A conformal regressor for predicting negative conversion time of Omicron patients. 用于预测 Omicron 患者负转换时间的共形回归器。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-08-01 Epub Date: 2024-02-16 DOI: 10.1007/s11517-024-03029-8

Pingping Wang, Shenjing Wu, Mei Tian, Kunmeng Liu, Jinyu Cong, Wei Zhang, Benzheng Wei

{"title":"A conformal regressor for predicting negative conversion time of Omicron patients.","authors":"Pingping Wang, Shenjing Wu, Mei Tian, Kunmeng Liu, Jinyu Cong, Wei Zhang, Benzheng Wei","doi":"10.1007/s11517-024-03029-8","DOIUrl":"10.1007/s11517-024-03029-8","url":null,"abstract":"In light of the situation and the characteristics of Omicron, the country has continuously optimized the rules for the prevention and control of COVID-19. The global epidemic is still spreading, and new cases of infection continue to emerge in China. To facilitate the infected person to estimate the course of virus infection, a prediction model for predicting negative conversion time is proposed in this article. The clinical features of Omicron-infected patients in Shandong Province in the first half of 2022 are retrospectively studied. These features are grouped by disease diagnosis result, clinical sign, traditional Chinese medicine symptoms, and drug use. These features are input to the eXtreme Gradient Boosting (XGBoost) model, and the output is the predicted number of negative conversion days. At the same time, XGBoost is used as the underlying algorithm of the conformal prediction (CP) framework, which can realize the probability interval estimation with a controllable error rate. The results show that the proposed model has a mean absolute error of 3.54 days and has the shortest interval prediction result. This shows that the method in this paper can carry more decision-making information and help people better understand the disease and self-estimate the course of the disease to a certain extent.","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":"2485-2495"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139742468","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}

引用次数: 0

A direct learning approach for detection of hotspots in microwave hyperthermia treatments. 微波热疗热点检测的直接学习方法。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-08-01 Epub Date: 2025-03-11 DOI: 10.1007/s11517-025-03343-9

Hulusi Onal, Enes Girgin, Semih Doğu, Tuba Yilmaz, Mehmet Nuri Akinci

{"title":"A direct learning approach for detection of hotspots in microwave hyperthermia treatments.","authors":"Hulusi Onal, Enes Girgin, Semih Doğu, Tuba Yilmaz, Mehmet Nuri Akinci","doi":"10.1007/s11517-025-03343-9","DOIUrl":"10.1007/s11517-025-03343-9","url":null,"abstract":"This paper presents a computational study for detecting whether the temperature values of the breast tissues are exceeding a threshold using deep learning (DL) during microwave hyperthermia (MH) treatments. The proposed model has a deep convolutional encoder-decoder architecture, which gets differential scattered field data as input and gives an image showing the cells exceeding the threshold. The data are generated by an in-house data generator, which mimics temperature distribution in the MH problem. The model is also tested with real temperature distribution obtained from electromagnetic-thermal simulations performed in commercial software. The results show that the model reaches an average accuracy score of 0.959 and 0.939 under 40 dB and 30 dB signal-to-noise ratio (SNR), respectively. The results are also compared with the Born iterative method (BIM), which is combined with some different conventional regularization methods. The results show that the proposed DL model outperforms the conventional methods and reveals the strong regularization capabilities of the data-driven methods for temperature monitoring applications.","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":"2451-2462"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12316837/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606342","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}

引用次数: 0

Real-time beat-to-beat pulse wave velocity estimation: a quality-driven approach using laser Doppler vibrometry. 实时拍对拍脉冲波速度估计：使用激光多普勒振动仪的质量驱动方法。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-07-30 DOI: 10.1007/s11517-025-03417-8

Silvia Seoni, Patrick Segers, Simeon Beeckman, Massimo Salvi, Marco Romanelli, Smriti Badhwar, Rosa Maria Bruno, Yanlu Li, Soren Aasmul, Nilesh Madhu, Filippo Molinari, Umberto Morbiducci

{"title":"Real-time beat-to-beat pulse wave velocity estimation: a quality-driven approach using laser Doppler vibrometry.","authors":"Silvia Seoni, Patrick Segers, Simeon Beeckman, Massimo Salvi, Marco Romanelli, Smriti Badhwar, Rosa Maria Bruno, Yanlu Li, Soren Aasmul, Nilesh Madhu, Filippo Molinari, Umberto Morbiducci","doi":"10.1007/s11517-025-03417-8","DOIUrl":"https://doi.org/10.1007/s11517-025-03417-8","url":null,"abstract":"Arterial stiffness, a key cardiovascular risk marker, is typically assessed via carotid-femoral pulse wave velocity (cf-PWV), the gold-standard method. In this study, we introduce CAPE (Continuous Automatic PWV Estimation), an innovative framework for near real-time cf-PWV estimation based on beat-to-beat analysis of laser-Doppler vibrometry (LDV) signals. CAPE integrates automatic fiducial point detection, systematic signal quality control, and a cross-channel strategy to provide a highly reliable assessment of cf-PWV. The framework was evaluated using LDV signals acquired from 100 patients with mild to moderate essential hypertension, using a multichannel laser vibrometry system. CAPE calculates cf-PWV as the ratio of carotid-femoral distance to pulse transit time (PTT), which is the delay between carotid and femoral fiducial points. These points are detected using template-matching on the second derivative of LDV displacement signals. Signal quality in CAPE is ensured through an integrated quality assessment based on the number of automatically detected carotid-femoral peaks, which assigns confidence scores (acceptable or excellent) to the PWV measurements. When validated against the gold-standard applanation tonometry, CAPE achieved a mean bias of 0.25 ± 0.77 m/s, demonstrating high reliability and precision. The optimized framework estimates cf-PWV in 3 s, making CAPE ideal for clinical applications requiring real-time cardiovascular assessment.","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745831","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}

引用次数: 0

Characterizing consciousness states: EEG microstate dynamics in patients with disorders of consciousness during naturalistic movie-viewing. 表征意识状态：自然观影过程中意识障碍患者的脑电图微态动力学。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-07-30 DOI: 10.1007/s11517-025-03415-w

Xiyuan Lei, Anqi Wang, Kexu Zhang, Siyang Liu, Ying Zhao, Steven Laureys, Shanbao Tong, Haibo Di, Nantu Hu, Xiaoli Guo

{"title":"Characterizing consciousness states: EEG microstate dynamics in patients with disorders of consciousness during naturalistic movie-viewing.","authors":"Xiyuan Lei, Anqi Wang, Kexu Zhang, Siyang Liu, Ying Zhao, Steven Laureys, Shanbao Tong, Haibo Di, Nantu Hu, Xiaoli Guo","doi":"10.1007/s11517-025-03415-w","DOIUrl":"https://doi.org/10.1007/s11517-025-03415-w","url":null,"abstract":"Consciousness assessment in disorders of consciousness (DoC) patients remains clinically challenging. Dynamic brain activities responsive to sensory stimulations have been suggested to contain consciousness-related information. However, primary sensory processing can occur unconsciously, necessitating evaluation of residual higher-order cognitive functions for effective assessment. In this study, we introduced a movie-viewing paradigm incorporating a scrambled version to control for primary sensory processing and applied electroencephalography (EEG) microstate analysis to capture higher-order neural dynamics. By comparing 23 DoC patients with 23 healthy individuals and 12 conscious brain-injured patients, we found significant abnormalities in microstate D in DoC patients. Healthy individuals and conscious brain-injured patients showed enhanced D-related parameters during intact movie-viewing compared to the scrambled condition. Conversely, DoC patients displayed a significant decrease in Duration, Coverage, Occurrence, and Transition Probabilities of microstate D during intact movie-viewing. Additionally, K-nearest neighbors classifier showed that the differences in microstate features between the intact and scrambled movie-viewing yielded the best classification outcome (AUC = 0.83), in which microstate D parameters serve as the most important features. Our results suggested that EEG microstates during naturalistic movie-viewing, especially microstate D, have the potential to serve as a novel, objective indicator for characterizing and diagnosing the state of consciousness.","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745830","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}

引用次数: 0

Slippage-suppression robot-assisted retraction for thyroid surgery with 5DoF contact force sensing. 五自由度接触式力传感甲状腺手术中滑移抑制机器人辅助后收。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-07-24 DOI: 10.1007/s11517-025-03420-z

Shouhui Deng, Haojun Li, Yuxuan Lin, Aiguo Song, Lifeng Zhu

引用次数: 0

Towards a radiation-free clinical decision support system for intraoperative spinal alignment assessment. 一种用于术中脊柱对齐评估的无辐射临床决策支持系统。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-07-24 DOI: 10.1007/s11517-025-03412-z

Luis Serrador, Pedro Varanda, Bruno Direito-Santos, Cristina P Santos

{"title":"Towards a radiation-free clinical decision support system for intraoperative spinal alignment assessment.","authors":"Luis Serrador, Pedro Varanda, Bruno Direito-Santos, Cristina P Santos","doi":"10.1007/s11517-025-03412-z","DOIUrl":"https://doi.org/10.1007/s11517-025-03412-z","url":null,"abstract":"This paper introduces SpineAlign, a novel radiation-free clinical decision support system (CDSS) designed to address the challenge of intraoperative spinal alignment assessment during spinal deformity (SD) correction surgeries. SpineAlign aims to overcome the current limitations of existing systems by providing a quantitative assessment without radiation exposure in the operating room (OR), thus enhancing the safety and precision of computer-assisted spinal surgeries (CASS). The system focuses on spinal alignment calculation, leveraging Bézier curves and algorithm development to track vertebrae and estimate spinal curvature. Collaborative meetings with clinical experts identified challenges such as patient positioning complexities and limitations of minimal invasiveness. Thus, the method developed involves four algorithms: (1) tracking anatomical planes; (2) estimating the Bézier curve; (3) determining vertebrae positions; and (4) adjusting orientation. A proof of concept (PoC) using a porcine spinal segment validated SpineAlign's integrated algorithms and functionalities. The PoC demonstrated the system's accuracy and clinical applicability, successfully transitioning a spine without curvature to a lordotic spine. Quantitative evaluation of spinal alignment by the system showed high accuracy, with a maximum root mean squared error of 6 <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mo>∘</mo></mmultiscripts> </math> . The successful PoC marks an initial step towards developing a reliable CDSS for intraoperative spinal alignment assessment without medical image acquisition. Future steps will focus on enhancing system robustness and performing multi-surgeon serial studies to advance SpineAlign towards widespread clinical adoption.","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144700160","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}

引用次数: 0

A web-based system for real-time ECG monitoring using MySQL database and DigiMesh technology: design and implementation. 基于web的基于MySQL数据库和DigiMesh技术的心电实时监测系统的设计与实现。

IF 2.6 4区医学

Medical & Biological Engineering & Computing Pub Date : 2025-07-23 DOI: 10.1007/s11517-025-03421-y

Abdelkader Tigrine, Moufida Houamria, Halima Sahraoui, Ameur Dahani, Noureddine Doumi, Khaled Dine

{"title":"A web-based system for real-time ECG monitoring using MySQL database and DigiMesh technology: design and implementation.","authors":"Abdelkader Tigrine, Moufida Houamria, Halima Sahraoui, Ameur Dahani, Noureddine Doumi, Khaled Dine","doi":"10.1007/s11517-025-03421-y","DOIUrl":"https://doi.org/10.1007/s11517-025-03421-y","url":null,"abstract":"In today's world, rapid advancements in wireless sensor network (WSN) technologies hold the potential to revolutionize healthcare through future ubiquitous patient monitoring systems. Essential for continuous monitoring without restricting patient mobility, these systems comprise wearable or implanted sensors continuously tracking physiological parameters. Enabling seamless patient-doctor interaction, they monitor and transmit patient physiological data. This project involves designing an ECG monitoring system utilizing DigiMesh technology for wireless transmission to a remote device. Patient data is stored in the IoT-cloud via a MySQL database, enabling real-time remote monitoring by medical staff. The sensor node processes ECG data, transmitted to the Sink Node, and the MySQL database facilitates data storage. Utilizing a web-based system accessible on all devices, the proposed monitoring system displays ECG results, reports, and patient information. The goal is to create a reliable, cost-effective, low-power vital signs monitoring system transmitting various body parameters wirelessly to medical professionals. In hospitals, continuous monitoring is crucial for patients requiring extended medical care, ensuring constant surveillance even in non-emergency situations.","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692216","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}

引用次数: 0