IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology最新文献_第2页

Dynamic Electromagnetic Model to Detect Human Vital Signs Based on Time-Domain Finite Integration Theorem 基于时域有限积分定理的人体生命体征动态电磁检测模型

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-12-03 DOI: 10.1109/JERM.2024.3507005

Xinyu Li;Jingyuan Zhang;Zixuan Cai;Xiong Wei Wu;Qiaocong Peng;Qian Ma;Jian Wei You;Tie Jun Cui

{"title":"Dynamic Electromagnetic Model to Detect Human Vital Signs Based on Time-Domain Finite Integration Theorem","authors":"Xinyu Li;Jingyuan Zhang;Zixuan Cai;Xiong Wei Wu;Qiaocong Peng;Qian Ma;Jian Wei You;Tie Jun Cui","doi":"10.1109/JERM.2024.3507005","DOIUrl":"https://doi.org/10.1109/JERM.2024.3507005","url":null,"abstract":"Contactless human vital-sign sensing using electromagnetic (EM) waves has made significant progress over the past few years and been practically applicable to a variety of fields such as smart home and healthcare. However, the further development of this technology is hindered by factors such as large volumes of data, long observation periods, and data variability. To deal with this challenge, a dynamic human EM model composed of customized time-varying EM materials is proposed to simulate the periodic characteristics of human cardiopulmonary motions and obtain physiological signals caused by the movements. The EM problem is subsequently addressed by employing the Time-Domain Finite Integration Technique (TDFIT), so that the EM scattering properties associated with human cardiopulmonary movements can be accurately analyzed. To validate the effectiveness of the proposed human EM model, we process the simulated human physiological signals for respiration and heartbeat rate estimation, with the error less than 4% and 8%, respectively. Furthermore, measured experiments are conducted to collected actual human vital-sign signals for comparison. Good agreement between the measured and simulated results demonstrates that the proposed human EM model is capable of accurately simulating the periodic cardiopulmonary motions and thus providing simulated physiological measurements for preliminary validation of vital sign sensing algorithms.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"240-250"},"PeriodicalIF":3.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117265","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}

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IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology About this Journal IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology 关于本期刊

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-11-22 DOI: 10.1109/JERM.2024.3496595

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IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Publication Information IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology 出版信息

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-11-22 DOI: 10.1109/JERM.2024.3496599

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Integrated Boundary-Overlap-Size Metric for Local Assessment of Deep Learning Methods in Medical Microwave Imaging 医学微波成像中深度学习方法局部评价的边界-重叠大小综合度量

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-11-04 DOI: 10.1109/JERM.2024.3485250

Fei Xue;Lei Guo;Alina Bialkowski;Amin M. Abbosh

{"title":"Integrated Boundary-Overlap-Size Metric for Local Assessment of Deep Learning Methods in Medical Microwave Imaging","authors":"Fei Xue;Lei Guo;Alina Bialkowski;Amin M. Abbosh","doi":"10.1109/JERM.2024.3485250","DOIUrl":"https://doi.org/10.1109/JERM.2024.3485250","url":null,"abstract":"Deep learning has been a game-changer in enhancing the speed and accuracy of medical microwave imaging in detecting abnormal lesions. Nonetheless, the challenge lies in establishing a universal objective metric to assess the reliability of these methods. Current evaluation practices often rely on a single geometric metric, which presents inherent constraints. Consequently, the evaluations of results generated by deep learning methods may not always reflect clinicians’ insights and judgments. To overcome this, a local assessment metric incorporating the following three geometric dimensions is proposed: the overlap between the detected anomaly and the actual lesion, the proximity of their boundaries, and the proportionality of the lesion sizes determined by the algorithm versus the actual lesion. This approach to evaluation ensures that the resulting metric's score is in line with professional medical diagnostics. The presented results on head imaging using five deep learning algorithms confirm the significant advantages of the proposed metric, validating its effectiveness in providing objective evaluation of various algorithms in medical electromagnetic imaging. This objective metric is poised to guide future algorithm development to ensure a reliable assessment of their capability in abnormality detection and diagnosis.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"229-239"},"PeriodicalIF":3.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117170","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}

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Low-Cost and Easy-to-Fabricate Microwave Sensor for Sensitive Glucose Monitoring: A Step Towards Continuous Glucose Monitoring 用于敏感血糖监测的低成本和易于制造的微波传感器：迈向连续血糖监测的一步

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-10-22 DOI: 10.1109/JERM.2024.3477596

Ahnaf Tahmid;Tanzim Rahman;S. M. Ali Emam;Syeda Maliha Reza;Md Ismail Hosen;Reefat Inum;Ahsan Habib

{"title":"Low-Cost and Easy-to-Fabricate Microwave Sensor for Sensitive Glucose Monitoring: A Step Towards Continuous Glucose Monitoring","authors":"Ahnaf Tahmid;Tanzim Rahman;S. M. Ali Emam;Syeda Maliha Reza;Md Ismail Hosen;Reefat Inum;Ahsan Habib","doi":"10.1109/JERM.2024.3477596","DOIUrl":"https://doi.org/10.1109/JERM.2024.3477596","url":null,"abstract":"Basal-bolus insulin therapy is associated with frequent injections, dosing errors, and hypoglycemia risks. Integrating continuous glucose monitoring (CGM) with insulin pumps offers several advantages. However, current CGM systems lack accuracy and have high costs. To overcome these challenges, a CGM system requires sensor with enhanced sensitivity and low cost. In this study, we develop a planar microwave resonator-based sensor for sensitive glucose detection in human serum and whole blood. We track the variation in the transmission coefficient (<inline-formula><tex-math>$s_{21}$</tex-math></inline-formula>) to deduce changes in glucose concentration. Utilizing combinations of complementary split ring resonators (CSRRs) and complementary electric-LC (CELC) structures, the sensor achieves remarkable sensitivity, notably 37.3 mdB/(mg/dL) for glucose in human serum and 1.557 mdB/(mg/dL) for glucose in whole blood. We also evaluate other performance metrics, linearity (<inline-formula><tex-math>$R^{2} = 0.985$</tex-math></inline-formula> for serum and <inline-formula><tex-math>$R^{2} = 0.963$</tex-math></inline-formula> for whole blood), and limit of detection (LOD) of 477.75 μg/dL for serum and 53.84 mg/dL for whole blood. While we initially use an FR-4 rigid substrate in our proof-of-concept demonstration, we also investigate the feasibility of employing a flexible polyimide substrate. Our flexible glucose sensor shows an order of magnitude better performance than our rigid sensor.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"221-228"},"PeriodicalIF":3.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117266","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}

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Movement Tracking and False Positive Reduction Method for Microwave Colonoscopy Systems 微波结肠镜系统的运动跟踪和假阳性减少方法

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-10-21 DOI: 10.1109/JERM.2024.3476964

Alejandra Garrido-Atienza;Marta Guardiola;Luz Maria Neira;Jordi Romeu;Andreas Fhager

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Fungal Tissue as a Medium for Electrical Signal Transmission: A Baseline Assessment With Melanized Fungus Curvularia Lunata 真菌组织作为电信号传输的媒介：黑化真菌弯孢菌的基线评估

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-10-16 DOI: 10.1109/JERM.2024.3476444

Robert M. Jones;Randall W. Reynolds;Alison K. Thurston;Robyn A. Barbato

{"title":"Fungal Tissue as a Medium for Electrical Signal Transmission: A Baseline Assessment With Melanized Fungus Curvularia Lunata","authors":"Robert M. Jones;Randall W. Reynolds;Alison K. Thurston;Robyn A. Barbato","doi":"10.1109/JERM.2024.3476444","DOIUrl":"https://doi.org/10.1109/JERM.2024.3476444","url":null,"abstract":"Fungal tissues are an underexplored medium for data and electrical signal transmission. Fungal tissues are a biodegradable material that can be cultivated in mass quantities; potentially making them sustainable materials for biological sensors or as a communication medium. Because the interactions of fungal tissues with communications signals are not thoroughly explored, a baseline assessment of the signal transmission capabilities of mat forming filamentous fungus, <italic>Curvularia lunata (<italic>C. lunata) was performed. In this paper, the band-pass characteristics of <italic>C. lunata were assessed through a frequency sweep from 1 Hz–5 MHz. The potential data transmission rates through a raw bit error rate analysis using a pseudorandom bit sequence between 1–1,000 kbps were evaluated. The passband for the tissue was between 1–500 kHz, characterizing it as a low-pass filter. Bit streams below 10 kbps had an error rate of <10%>500 kbps. The results suggest that this fungal tissue could serve as a low-speed data transmission medium specifically for low-pass signals related to general human health such as ECG, EEG, EMG signals as well as temperature and glucose monitoring. While more research is necessary to understand the morphological and species-specific impacts on signal propagation between different fungi, tissues from the fungus <italic>C. lunata and those with similar properties could potentially serve as a component in low-frequency biosensors and signal transmission.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"206-213"},"PeriodicalIF":3.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10720524","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117314","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}

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Advanced Microdosimetric and Neurofunctionalized Multiphysics on Stem Cells Models Under Microsecond Pulse Stimulation 微秒脉冲刺激下干细胞模型的高级微剂量学和神经功能化多物理场

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-10-15 DOI: 10.1109/JERM.2024.3468024

Sara Fontana;Laura Caramazza;Micol Colella;Noemi Dolciotti;Alessandra Paffi;Victoria Moreno Manzano;Claudia Consales;Francesca Apollonio;Micaela Liberti

{"title":"Advanced Microdosimetric and Neurofunctionalized Multiphysics on Stem Cells Models Under Microsecond Pulse Stimulation","authors":"Sara Fontana;Laura Caramazza;Micol Colella;Noemi Dolciotti;Alessandra Paffi;Victoria Moreno Manzano;Claudia Consales;Francesca Apollonio;Micaela Liberti","doi":"10.1109/JERM.2024.3468024","DOIUrl":"https://doi.org/10.1109/JERM.2024.3468024","url":null,"abstract":"<bold>Objectives: in recent biomedical applications for regenerative and tissue engineering, the use of electric and magnetic fields is increasingly exploited. Among the wide application range, an innovative treatment for Spinal Cord Injury (SCI) is urgent. The European project RISEUP proposes a novel device development, that will provide highly intense microsecond pulsed electric fields (μsPEFs) to stimulate stem cells differentiation towards neuronal phenotypes, through an electroporation-driven process, and regenerate the lesioned tissue. Within RISEUP the use of advanced computational models is crucial to predict the cellular functional response through microdosimetry studies. <bold>Technology or Method: a multiphysic neuro-functionalized computational model has been built, using a realistic induced Neuronal Stem Cell (iNSC) model (a iNSC digital twin), to predict the effect of μsPEFs stimulation on both neuronal response and pore formation dynamics. <bold>Results: considering a 100-μsPEF and an intensity of 30 kV/m, the pore density can reach up to 1014 m−2 over the plasma membrane, with a consequent hyperpolarization and a phase shift of the neuronal firing. Whereas, where the pore density remains at its default value 109 m−2, the neuronal response is slightly affected in spikes frequency and shape, but still maintaining its firing functions. <bold>Conclusions: this study provides an innovative multiphysics implementation on a realist 2D iNSC model, that has demonstrated the 100-μsPEF influence on the neurodynamic response. <bold>Clinical or Biological Impact: the results obtained give powerful insights for further <italic>in vitro and <italic>in vivo experiments, that will validate the use of the device proposed within RISEUP for SCI regeneration.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"173-182"},"PeriodicalIF":3.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117316","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}

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Size-Adaptive Occipital 18-Channel Receive-Only RF Coil for 3T MRI 尺寸自适应枕骨18通道仅接收射频线圈用于3T MRI

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-10-08 DOI: 10.1109/JERM.2024.3465354

William Mathieu;Milica Popović;Reza Farivar

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Impact of Unit Cell Density on Grid and Stripe Metasurfaces for MRI Receive Enhancement 单元细胞密度对栅格和条纹超表面的影响

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-09-23 DOI: 10.1109/JERM.2024.3458078

Robert Kowal;Lucas Knull;Ivan Vogt;Max Joris Hubmann;Daniel Düx;Bennet Hensen;Frank Wacker;Oliver Speck;Holger Maune

{"title":"Impact of Unit Cell Density on Grid and Stripe Metasurfaces for MRI Receive Enhancement","authors":"Robert Kowal;Lucas Knull;Ivan Vogt;Max Joris Hubmann;Daniel Düx;Bennet Hensen;Frank Wacker;Oliver Speck;Holger Maune","doi":"10.1109/JERM.2024.3458078","DOIUrl":"https://doi.org/10.1109/JERM.2024.3458078","url":null,"abstract":"Metasurfaces enable magnetic resonance imaging (MRI) without cables inside the bore by locally improving the sensitivity of scanner-integrated receive coils. This study systematically evaluates a novel grid design to provide signal enhancement for patient imaging. The potential of the proposed metasurface grid design was analyzed regarding its unit cell density and compared with stripe type metasurfaces. The effects were examined in-depth by numerical simulation, workbench measurements, and MRI experiments at 3 Tesla. Differences in the signal-to-noise ratio (SNR) using either the integrated body or spine coils were evaluated, as well as the influence of the metasurface orientation. The grid design provided a favorable eigenmode usable for MR imaging, where it has shown significantly less dependence on orientation, compared to stripe metasurfaces. With the densest grid, more than 26% higher SNR than its most spaced design was achieved. Combining the metasurface for imaging with the spine coil proved to be superior to the body coil. Applying the metasurface for knee imaging, the SNR was locally enhanced by more than 10-fold compared to the scan with only the spine coil. The high-density grid metasurfaces provided benefits compared to the multitude of designs evaluated. This work provides a comprehensive foundation for future developments of metasurfaces for MRI, whose advantages may be exploited e.g. in the domain of interventional radiology.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"198-205"},"PeriodicalIF":3.0,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10685136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117319","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