IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology最新文献

IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology About this Journal 医学和生物学中的电磁学、射频和微波

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-02-20 DOI: 10.1109/JERM.2025.3539041

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IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Publication Information 医学和生物学中的电磁学、射频和微波杂志

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2025-02-20 DOI: 10.1109/JERM.2025.3539043

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2024 Index IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Vol. 8 电磁学，射频和微波在医学和生物学第8卷

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-12-11 DOI: 10.1109/JERM.2024.3512633

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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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Non-Contact Vital Sign Detection With High Noise and Clutter Immunity Based on Coherent Low-IF CW Radar 基于相干低中频连续波雷达的高噪声抗杂波非接触生命体征检测

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-09-20 DOI: 10.1109/JERM.2024.3454332

Jingtao Liu;Fei Tong;Changzhan Gu

{"title":"Non-Contact Vital Sign Detection With High Noise and Clutter Immunity Based on Coherent Low-IF CW Radar","authors":"Jingtao Liu;Fei Tong;Changzhan Gu","doi":"10.1109/JERM.2024.3454332","DOIUrl":"https://doi.org/10.1109/JERM.2024.3454332","url":null,"abstract":"Non-contact vital sign detection using Continuous-Wave (CW) radar is subject to noises and clutters. The heterodyne architecture of the radar transceiver resolves the flicker noise. However, it still suffers from other noise components. Moreover, the presence of clutter also significantly introduces distortions in the sensing results. In this paper, an extended Noise-Immune Motion Sensing (ENIMS) technique is proposed to tackle the noise and clutters simultaneously in the low intermediate-frequency (IF) CW radar. It works by synthesizing <italic>I/Q signals at the IF peak of the spectra of the sequentially divided signal segments. Each segment generates one pair of <italic>I/Q data points and thus improves the signal-to-noise ratio (<italic>SNR). During this process, clutters are also converted into DC components of the <italic>I/Q signals. The circle-fitting-based DC compensation technique can thus be used to resolve the clutter issues. High-accurate displacement motion is then reconstructed with the DC-compensated <italic>I/Q signals. The theory and noise performance analysis are presented. Simulation and experiments show that, with the proposed technique, the <italic>SNR is improved by around 34 dB. Mechanical vibration as small as 90 <italic>μm and the subject person's breath and heartbeat at 3.2 m away from the 5. 8 GHz radar were detected under cluttered office environments with a small transmitting power of only 10 <italic>μW, whereas the conventional methods fail in the same cases.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"90-100"},"PeriodicalIF":3.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455299","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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Programmable Pulse Generator by Envelope Detection for Implantable Medical Devices 可编程脉冲发生器的包络检测植入式医疗设备

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-08-30 DOI: 10.1109/JERM.2024.3435075

Hao Zhang;Xiaozhou Zhou;Wenlong Zhou

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Safeguarding Humans From Indoor Wireless Powering via Radar Detection 通过雷达探测保护人类免受室内无线供电

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-08-29 DOI: 10.1109/JERM.2024.3447469

Pouya Mehrjouseresht;Oluwatosin J. Babarinde;Vladimir Volski;Alexander Ye. Svezhentsev;Dominique M. M.-P. Schreurs

{"title":"Safeguarding Humans From Indoor Wireless Powering via Radar Detection","authors":"Pouya Mehrjouseresht;Oluwatosin J. Babarinde;Vladimir Volski;Alexander Ye. Svezhentsev;Dominique M. M.-P. Schreurs","doi":"10.1109/JERM.2024.3447469","DOIUrl":"https://doi.org/10.1109/JERM.2024.3447469","url":null,"abstract":"Ensuring the safety of electromagnetic exposure stands as an important concern in wireless power transfer (WPT) systems. This work proposes a distributed Fusion Radar WPT (FRWPT) system designed to maintain safe Electric Field Amplitude (EFA) levels at specific locations detected by the radar, primarily where an individual is present. This approach allows for higher EFA in areas without the person, thus optimizing overall power utilization within the system. Also, the radar's ability to detect a person's velocity allows for projecting the person's upcoming location to ensure safety in advance. We introduce an algorithm including power weighting factors for controlling power to not only mitigate dangerous radiation but also maximize power utilization. One significant challenge is the estimation of EFA considering multipath propagation, a common issue in indoor environments. To overcome this, we explore the indoor EFA distribution and suggest a simulation-based method for EFA estimation, taking into account the amplifying effect of the human body on EFA. Experimental results demonstrate that the system successfully maintains EFA below a predefined threshold across various human locations. Moreover, these experiments highlight the system's capability to maximize power utilization ratio (PUR), achieving a value exceeding 50%.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"62-69"},"PeriodicalIF":3.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455301","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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Propagation of Radio-Frequency Electromagnetic Fields Emitted by Surface-Mounted Parallel-Plate Couplers Along Human Limbs 表面安装平行板耦合器发射的射频电磁场沿人体四肢的传播

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-08-29 DOI: 10.1109/JERM.2024.3442693

Arno Thielens

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mm-MuRe: mmWave-Based Multi-Subject Respiration Monitoring via End-to-End Deep Learning mm-MuRe：基于毫米波的多主体呼吸监测，通过端到端深度学习

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IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-08-22 DOI: 10.1109/JERM.2024.3443782

Chandler Bauder;Abdel-Kareem Moadi;Vijaysrinivas Rajagopal;Tianhao Wu;Jian Liu;Aly E. Fathy

{"title":"mm-MuRe: mmWave-Based Multi-Subject Respiration Monitoring via End-to-End Deep Learning","authors":"Chandler Bauder;Abdel-Kareem Moadi;Vijaysrinivas Rajagopal;Tianhao Wu;Jian Liu;Aly E. Fathy","doi":"10.1109/JERM.2024.3443782","DOIUrl":"https://doi.org/10.1109/JERM.2024.3443782","url":null,"abstract":"This study presents <sc>mm-MuRe, a novel method to perform multi-subject contactless respiration waveform monitoring by processing raw multiple-input-multiple-output mmWave radar data with an end-to-end deep neural network. The traditional vital signs monitoring signal processing scheme for mmWave radar involves analog or digital beamforming, human subject localization, phase variation extraction, filtering, and rate or biomarker analysis. This traditional method has many downsides, including sensitivity to selected beamforming weights and over-reliance on phase variation. To avoid these drawbacks, <sc>mm-MuRe (for MM-wave based MUlti-subject REspiration monitoring) is developed to improve reconstruction accuracy and reliability by taking in unprocessed 60 GHz MIMO FMCW radar data and outputting respiratory waveforms of interest, effectively mimicking an adaptive beamformer and bypassing the need for traditional localization and vital signs extraction techniques. Extensive testing across scenarios differing in range, angle, environment, and subject count demonstrates the network's robust performance, with an average cosine similarity exceeding 0.95. Results are compared to two baseline methods and show more than a 10% average improvement in waveform reconstruction accuracy across single and multi-subject scenarios. Coupled with a rapid inference time of 8.57 ms on a 10 s window of data, <sc>mm-MuRe shows promise for potential deployment to efficient and accurate near-real-time contactless respiration monitoring systems.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"49-61"},"PeriodicalIF":3.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455267","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