IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology最新文献_第4页

QRWOA-VMD Enhanced Heart Rate Monitoring Using PCR Radar QRWOA-VMD增强PCR雷达心率监测

IF 3.2

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-07-03 DOI: 10.1109/JERM.2025.3578677

Zhimeng Xu;Yichun Chen;Dan Li;Liangqin Chen;Yueming Gao;Zhizhang David Chen

{"title":"QRWOA-VMD Enhanced Heart Rate Monitoring Using PCR Radar","authors":"Zhimeng Xu;Yichun Chen;Dan Li;Liangqin Chen;Yueming Gao;Zhizhang David Chen","doi":"10.1109/JERM.2025.3578677","DOIUrl":"https://doi.org/10.1109/JERM.2025.3578677","url":null,"abstract":"Monitoring vital signs is essential for assessing individuals' health status and supporting various medical interventions; however, conventional methods depend on expensive and invasive hospital-based or wearable devices. This article presents a novel approach to contactless heart rate monitoring that leverages an Antenna-on-Package Pulse Coherent Radar (AoP PCR) system. To address the inherently low sampling rates associated with the pulse repetition frequency of the PCR during remote monitoring, a signal enhancement algorithm is presented. This algorithm leverages the quasi-periodic nature of chest displacement signals, leading to significantly improved temporal resolution and enabling reliable heart rate monitoring using a cost-effective PCR system. Furthermore, extracting heartbeat signals faces a significant challenge in optimally tuning the parameters of Variational Modal Decomposition (VMD) due to variations in distance and angle. To tackle this, an enhanced method called VMD based on the Whale Optimization Algorithm with Quasi-Reflection Learning (QRWOA-VMD) has been devised to enhance the precision of parameter optimization in VMD, thereby improving the decomposition accuracy of heartbeat signals across diverse angles and distances, leading to more reliable and robust heartbeat signal extraction. Comprehensive evaluation demonstrates that the proposed method achieves over 97% accuracy in heart rate monitoring under standard conditions, with the radar facing the chest within a 1.5-meter range. Even in challenging scenarios, such as a ±30° azimuth angles and a 20° elevation angle relative to the chest, accuracy remains above 93%.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 4","pages":"455-465"},"PeriodicalIF":3.2,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560642","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

Cardiac Pulsed-Field Ablation: Deep Learning Solutions for Multi-Parameter Predictions 心脏脉冲场消融：多参数预测的深度学习解决方案

IF 3.2

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-06-16 DOI: 10.1109/JERM.2025.3577268

R. Crusi;N. Colistra;F. Camera;G. Monti;M. S. Zappatore;C. Merla;L. Tarricone

引用次数: 0

Breast Cancer Detection Using a Metasurface-Based Microwave Probe 基于超表面的微波探针检测乳腺癌

IF 3.2

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-06-13 DOI: 10.1109/JERM.2025.3572116

Mauricio Hernández;Hamid Akbari-Chelaresi;Ghazaleh Tashtarian;Omar M. Ramahi

{"title":"Breast Cancer Detection Using a Metasurface-Based Microwave Probe","authors":"Mauricio Hernández;Hamid Akbari-Chelaresi;Ghazaleh Tashtarian;Omar M. Ramahi","doi":"10.1109/JERM.2025.3572116","DOIUrl":"https://doi.org/10.1109/JERM.2025.3572116","url":null,"abstract":"This work introduces an electromagnetic energy scanning technique with specific application to the detection of breast cancer. The technique is based on a metasurface field detector probe composed of an ensemble of electrically small elements resonating at 700 MHz, where the middle single element represents the field detector. The sensor scans the two-dimensional plane that contains the energy transmitted through the breast. Once the scan is completed, we generate a contrast image composed of N X N pixels that represent the different components of the breast tissue. We then compile a dataset of these contrast images to train a convolutional neural network (CNN) to differentiate between healthy and unhealthy breast tissue. Thie probe provides a resolution that cannot be matched by either electrically small probes or resonance-based probes that have dimensions comparable to the wavelength. The field emanating from a specific structure, such as a human female breast, can be scanned by the proposed probe to achieve a resolution in the millimeter range while operating in the low-microwave frequency spectrum. The probe was tested numerically, and a prototype was tested experimentally, demonstrating its effectiveness in providing a field resolution of approximately 5 mm.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 4","pages":"436-444"},"PeriodicalIF":3.2,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560761","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

Lightweight, Battery-Less and Wireless Sensor for Monitoring Neuronal Activity in Swine 用于监测猪神经元活动的轻便、无电池和无线传感器

IF 3.2

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-06-12 DOI: 10.1109/JERM.2025.3574086

Melany Gutierrez-Hernandez;Sally P. Duarte;Daniel Parrado Triana;Satheesh Bojja-Venkatakrishnan;Jorge Riera Diaz;John L. Volakis

{"title":"Lightweight, Battery-Less and Wireless Sensor for Monitoring Neuronal Activity in Swine","authors":"Melany Gutierrez-Hernandez;Sally P. Duarte;Daniel Parrado Triana;Satheesh Bojja-Venkatakrishnan;Jorge Riera Diaz;John L. Volakis","doi":"10.1109/JERM.2025.3574086","DOIUrl":"https://doi.org/10.1109/JERM.2025.3574086","url":null,"abstract":"Electrocorticogram (ECoG) is frequently used to identify the origin of seizures. ECoG recording is highly invasive and usually involves wires that remain protruding from the skull. Alternative implantable ECoG systems have been designed. The latter requires a power supply with high power consumption that can generate heat, possibly causing tissue damage. Previously, our group introduced and developed a battery-less, wireless neurosensing system (WiNS). Also, comparable battery-free sensors demonstrated a minimum detectable signal (MDS) of 60 μVpp to 200 μVpp in benchtop measurements using high impedance electrodes (<inline-formula><tex-math>$sim$</tex-math></inline-formula> 33 k<inline-formula><tex-math>$Omega$</tex-math></inline-formula>). In this paper, we introduce a groundbreaking 3D-printed neural recorder with 50% reduced size over previous designs. Also, the matching circuit and antennas are designed for optimal communications and coupling, improving the MDS up to 10-fold. In addition, a full implantation in a large, regulated animal model (swine) was done for the first time, successfully recording evoked neural potentials. This will create the foundation for evaluating this system in chronic epileptic pigs and humans. Overall, the paper demonstrates the cutting-edge capabilities of our proposed recorder in the field of neurological activity monitoring.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 4","pages":"427-435"},"PeriodicalIF":3.2,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560760","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

Effects of Transcranial Focused Magnetoacoustic Electrical Stimulation on the EEG Signal of Alzheimer's Disease Rats 经颅聚焦磁声电刺激对老年痴呆症大鼠脑电图信号的影响

IF 3.2

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-06-03 DOI: 10.1109/JERM.2025.3573039

Ruolan Yang;Manxi Xu;Jixin Luan;Aocai Yang;Chao Zhang;Kuan Lv;Yuanyuan Li;Wenwei Zhang;Guoqiang Liu;Guolin Ma;Hui Xia

{"title":"Effects of Transcranial Focused Magnetoacoustic Electrical Stimulation on the EEG Signal of Alzheimer's Disease Rats","authors":"Ruolan Yang;Manxi Xu;Jixin Luan;Aocai Yang;Chao Zhang;Kuan Lv;Yuanyuan Li;Wenwei Zhang;Guoqiang Liu;Guolin Ma;Hui Xia","doi":"10.1109/JERM.2025.3573039","DOIUrl":"https://doi.org/10.1109/JERM.2025.3573039","url":null,"abstract":"Transcranial focused magnetoacoustic electrical stimulation (TFMAES) is an emerging composite neurostimulation technique, which can achieve precise electrical modulation of brain neural tissues with the help of low-intensity focused ultrasound. The aim of this study was to investigate the ameliorative effect of TFMAES on Alzheimer's disease (AD) symptoms. Through finite element simulation calculations, we determined the parameters of the TFMAES experiment. And 6 transgenic AD rats were used to perform continuous TFMAES experiments for 7 days at 2 different symptom stages in the progression of AD symptoms to observe the changes of electroencephalography (EEG) signals before and after the stimulation. The results showed that in the first stage, the amyloid beta (Aβ) deposition period, TFMAES led to a decrease in the delta-band energy percentage and an increase in the gamma-band energy percentage of EEG in AD rats. In the second stage, the onset of dementia symptoms, the effect of TFMAES on the delta-band power percentage of AD was significant compared to the gamma-band power percentage, but the effect on the overall EEG activity remained significant. These preliminary results suggest that TFMAES has a significant effect on the delta-band of EEG in AD rats, which may improve the activity of the cerebral cortex and thus improve AD symptoms. Moreover, this ameliorative effect is more significant in the early AD stage, which provides a basis for subsequent research on the mechanism of TFMAES quantitative parameters in AD improvement.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 4","pages":"417-426"},"PeriodicalIF":3.2,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560759","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

Clinical Validations on Effective Skin Clutter Rejection for Microwave Breast Cancer Diagnosis 微波诊断乳腺癌有效皮肤杂波抑制的临床验证

IF 3.2

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-04-30 DOI: 10.1109/JERM.2025.3562571

Ayumi Ueda;Shouhei Kidera

引用次数: 0

Efficient Recording of Rodent Neuronal Activity Using Microelectrodes With a Battery Free Wireless Neurosensing System 利用微电极和无电池无线神经传感系统高效记录啮齿动物神经元活动

IF 3.2

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-04-21 DOI: 10.1109/JERM.2025.3559051

Carolina Moncion;Lakshmini Balachandar;Melany Gutierrez-Hernandez;John L. Volakis;Jorge Riera Diaz

{"title":"Efficient Recording of Rodent Neuronal Activity Using Microelectrodes With a Battery Free Wireless Neurosensing System","authors":"Carolina Moncion;Lakshmini Balachandar;Melany Gutierrez-Hernandez;John L. Volakis;Jorge Riera Diaz","doi":"10.1109/JERM.2025.3559051","DOIUrl":"https://doi.org/10.1109/JERM.2025.3559051","url":null,"abstract":"To address the limitations of existing wired and wireless battery-powered designs for monitoring neuronal activity, our team has developed a novel implantable, battery-free, Wireless Neurosensing System (WiNS). Here, we aim to develop low-impedance microelectrodes to improve the minimum detectable signal for recording intracranial activity. For the first time, WiNS is evaluated in vivo to capture multiunit neuronal spiking, after adding a passive impedance matching (PIM) network. We explored different techniques for fabricating microelectrodes and demonstrated the resulting reduction in our system signal attenuation. Specifically, we were able to recover signals of 20 µVpp, a 10-fold improvement over previous designs. Furthermore, we fabricated microdrives to facilitate neuronal recording activity with WiNS and a wired system as a “gold” standard comparison. With the necessary components for our experiment, rat somatosensory cortex evoked neural activity was recorded. Broadband electrophysiological recordings were analyzed on multiple scales by evaluating the low-frequency component for elements corresponding to local field potentials (LFP) and the high-frequency component for multiunit neuronal spiking activity. LFP analysis involved the extraction of somatosensory evoked potentials to evaluate the recordings of each system. Concurrently, the neuronal spiking contributions were analyzed for spike occurrence and characteristics. Results at both scales indicate that recordings performed with WiNS are comparable with those of a wired system (p-value <0.050, Mann-Whitney Test). Therefore, the addition of PIM and the careful design of microelectrodes, led to the validation of WiNS using commercially available wired system. Furthermore, WiNS enables countless applications in neuroscience for continuous monitoring of neuronal activity.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 4","pages":"393-399"},"PeriodicalIF":3.2,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560757","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

Employing Surface Waves for Characterizing Skin: Experimental Validation 利用表面波表征皮肤：实验验证

IF 3

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-04-09 DOI: 10.1109/JERM.2025.3555198

Shangyang Shang;Milad Mokhtari;Milica Popović

引用次数: 0

Deep Learning-Based Prediction of Specific Absorption Rate Induced by Ultra-High-Field MRI RF Head Coil 基于深度学习的超高场MRI射频头线圈比吸收率预测

IF 3.2

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-04-07 DOI: 10.1109/JERM.2025.3555236

Xi Wang;Xiaofan Jia;Shao Ying Huang;Abdulkadir C. Yucel

{"title":"Deep Learning-Based Prediction of Specific Absorption Rate Induced by Ultra-High-Field MRI RF Head Coil","authors":"Xi Wang;Xiaofan Jia;Shao Ying Huang;Abdulkadir C. Yucel","doi":"10.1109/JERM.2025.3555236","DOIUrl":"https://doi.org/10.1109/JERM.2025.3555236","url":null,"abstract":"<italic>Objective: As magnetic resonance imaging (MRI) technologies advance, predicting local Specific Absorption Rate (SAR) distributions becomes more challenging. This difficulty arises from the unique anatomical structures and dielectric properties of individual subjects, coupled with the inherent non-uniformity of energy deposition within tissues during scanning. To rapidly estimate SAR values induced by ultra-high-field (UHF) MRI birdcage RF coil in near real-time, this paper proposes a deep learning-based framework. <italic>Methods: The proposed framework consists of two stages. During the dataset generation stage, high-dimensional model representation, a polynomial-based surrogate modeling technique, is used to generate a large and diverse dataset, thereby reducing the reliance on resource-intensive deterministic simulations performed by physics-based simulators. During the inference stage, the framework employs 3D Attention U-Net, processing relative permittivity and conductivity maps of head models along with incident electric fields to predict SAR distributions. <italic>Results: The 3D Attention U-Net outperforms all other 3D U-Net variants and demonstrates remarkable accuracy, with mean relative errors of 7.57% for voxel SAR, 5.63% for 10g-averaged SAR, and 2.60% for peak spatial SAR. Each prediction can be performed in less than half a second, outperforming traditional physics-based simulators by at least three orders of magnitude. <italic>Conclusion: The framework provides a significant computational advantage over traditional physics-based simulators while maintaining satisfactory accuracy. <italic>Significance: The computational framework, available on GitHub, enables real-time SAR predictions on permittivity and conductivity distributions on any unseen MRI head models. The framework will allow ultra-fast optimization and uncertainty quantification studies to be performed while designing new UHF MRI coils.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 4","pages":"379-392"},"PeriodicalIF":3.2,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560660","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

Impact of MRI Field Strengths on Metasurface Enhancement MRI场强对超表面增强的影响

IF 3

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-04-01 DOI: 10.1109/JERM.2025.3548169

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

{"title":"Impact of MRI Field Strengths on Metasurface Enhancement","authors":"Robert Kowal;Lucas Knull;Max Joris Hubmann;Ivan Vogt;Daniel Düx;Florian Maier;Marcel Gutberlet;Bennet Hensen;Frank Wacker;Oliver Speck;Holger Maune","doi":"10.1109/JERM.2025.3548169","DOIUrl":"https://doi.org/10.1109/JERM.2025.3548169","url":null,"abstract":"Metasurfaces have proved valuable in magnetic resonance imaging (MRI) applications through modifying the field profiles of radiofrequency coils to enhance imaging. Using metasurfaces to enhance a conventional coil, such as the table-integrated spine coil, allows imaging with practically no cables inside the bore. This work investigated the fundamental relationship between an MRI system's field strength and the enhancement effect of a metasurface. We simulated and manufactured grid metasurfaces for field strengths of 0.55 Tesla (0.55 T), 1.5 T and 3 T and evaluated them experimentally. We found increased enhancements of the signal-to-noise ratio (SNR) with lower field strengths. At 0.55 T, the enhancement in the vicinity of the metasurface (10.9-fold) was measured 3.8 times higher than at 3 T. Moreover, the SNR decreased less with field strength next to the metasurface compared to the spine coil. Our results indicate the capability of metasurfaces in low field MRI systems and can stimulate further research. This could benefit future applications in MRI-guided interventions through simplified handling, as well as countries currently underserved with MRIs due to low manufacturing costs.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"126-132"},"PeriodicalIF":3.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10946275","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117168","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