Pub Date : 2024-08-29DOI: 10.1109/JERM.2024.3442693
Arno Thielens
Wearables on human limbs commonly require wireless connections with other body-worn devices. These links can be established using radio-frequency electromagnetic fields emitted by parallel-plate capacitors (PPCs) as transducing elements. The propagation of the electric (E-) fields emitted by such PPCs on the surface of human limbs is studied by simulations with a stratified, lossy, dielectric cylinder as a limb model. In contrast to currently existing models, this analysis demonstrates that this propagation depends strongly on propagating modes within the lossy dielectric waveguide and that this is associated with an optimal frequency band of operation for such wireless links, which is tied to cut-off frequencies for propagation along the cylindrical waveguide and the radiation efficiency of the PPC, which is also dependent on the limb size. A channel-loss model in the 0.1–1 GHz frequency range is determined based on the simulations. This model is validated using channel loss measurements using a PPC placed on the limbs of three human subjects.
{"title":"Propagation of Radio-Frequency Electromagnetic Fields Emitted by Surface-Mounted Parallel-Plate Couplers Along Human Limbs","authors":"Arno Thielens","doi":"10.1109/JERM.2024.3442693","DOIUrl":"https://doi.org/10.1109/JERM.2024.3442693","url":null,"abstract":"Wearables on human limbs commonly require wireless connections with other body-worn devices. These links can be established using radio-frequency electromagnetic fields emitted by parallel-plate capacitors (PPCs) as transducing elements. The propagation of the electric (E-) fields emitted by such PPCs on the surface of human limbs is studied by simulations with a stratified, lossy, dielectric cylinder as a limb model. In contrast to currently existing models, this analysis demonstrates that this propagation depends strongly on propagating modes within the lossy dielectric waveguide and that this is associated with an optimal frequency band of operation for such wireless links, which is tied to cut-off frequencies for propagation along the cylindrical waveguide and the radiation efficiency of the PPC, which is also dependent on the limb size. A channel-loss model in the 0.1–1 GHz frequency range is determined based on the simulations. This model is validated using channel loss measurements using a PPC placed on the limbs of three human subjects.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"70-79"},"PeriodicalIF":3.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455312","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}
Pub Date : 2024-08-22DOI: 10.1109/JERM.2024.3443782
Chandler Bauder;Abdel-Kareem Moadi;Vijaysrinivas Rajagopal;Tianhao Wu;Jian Liu;Aly E. Fathy
This study presents 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, 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, mm-MuRe shows promise for potential deployment to efficient and accurate near-real-time contactless respiration monitoring systems.
本研究提出了mm-MuRe，一种通过端到端深度神经网络处理原始多输入多输出毫米波雷达数据来执行多受试者非接触式呼吸波形监测的新方法。传统的毫米波雷达生命体征监测信号处理方案包括模拟或数字波束形成、人体受试者定位、相位变化提取、滤波以及速率或生物标志物分析。这种传统的方法有很多缺点，包括对所选波束形成权重的敏感性和对相位变化的过度依赖。为了避免这些缺点，mm-MuRe（基于毫米波的多主体呼吸监测）被开发出来，通过采用未处理的60 GHz MIMO FMCW雷达数据和输出感兴趣的呼吸波形，有效地模仿自适应波束形成器，绕过传统定位和生命体征提取技术的需要，提高重建精度和可靠性。在不同的范围、角度、环境和主题数量的场景中进行的广泛测试表明，该网络具有强大的性能，平均余弦相似度超过0.95。结果与两种基线方法进行了比较，结果显示，在单主题和多主题场景下，波形重建精度平均提高了10%以上。再加上在10秒的数据窗口上8.57毫秒的快速推断时间，mm-MuRe有望部署到高效、准确的近实时非接触式呼吸监测系统中。
{"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</small>, 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</small> (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</small> 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}
Pub Date : 2024-08-22DOI: 10.1109/JERM.2024.3442073
{"title":"IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology About this Journal","authors":"","doi":"10.1109/JERM.2024.3442073","DOIUrl":"https://doi.org/10.1109/JERM.2024.3442073","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"C3-C3"},"PeriodicalIF":3.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643730","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041406","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}
Pub Date : 2024-08-22DOI: 10.1109/JERM.2024.3442071
{"title":"IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Publication Information","authors":"","doi":"10.1109/JERM.2024.3442071","DOIUrl":"https://doi.org/10.1109/JERM.2024.3442071","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"C2-C2"},"PeriodicalIF":3.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643733","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041465","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}
Pub Date : 2024-08-19DOI: 10.1109/JERM.2024.3433008
Rakesh Singh;Dharmendra Singh;Manoj Gupta
Breast cancer imaging technology requires the artificial breast phantom for early-stage breast cancer testing. The creation of a breast phantom that can replicate the dielectric properties found in real breast tissue holds significant importance in the optimization of the imaging system where computation of the effective dielectric properties of the breast, with and without the tumor needs more attention. Therefore, in this paper, an attempt has been made to develop the dielectric mixing model approach which may represent the real scenario of breast cancer like breast with different size of the tumor. This paper is also proposed to fabricate the phantom using gelatin and water and different size of tumor such as 2 mm, 4 mm, 6 mm, 8 mm and 10 mm which has been inserted in the phantom, and obtained result were compared with dielectric mixing model approach. The dielectric properties of a fabricated phantom, and phantom embedded with different sizes of tumor, were obtained using an open-ended coaxial probe method and computed the effective dielectric properties using dielectric mixing model approach spanning the frequency range from 1 GHz to 10 GHz. It is observed that the measurement results are in quite good agreement with the result of the dielectric mixing model. The main aim of the paper is to observe the change in dielectric properties when the tumor sizes are changing and it is found that there are considerable changes in dielectric with different dimension of the tumor in the frequency range 1 GHz to 10 GHz.
{"title":"Computation of Effective Dielectric Properties Using Dielectric Mixing Model Approach for Breast Cancer Detection","authors":"Rakesh Singh;Dharmendra Singh;Manoj Gupta","doi":"10.1109/JERM.2024.3433008","DOIUrl":"https://doi.org/10.1109/JERM.2024.3433008","url":null,"abstract":"Breast cancer imaging technology requires the artificial breast phantom for early-stage breast cancer testing. The creation of a breast phantom that can replicate the dielectric properties found in real breast tissue holds significant importance in the optimization of the imaging system where computation of the effective dielectric properties of the breast, with and without the tumor needs more attention. Therefore, in this paper, an attempt has been made to develop the dielectric mixing model approach which may represent the real scenario of breast cancer like breast with different size of the tumor. This paper is also proposed to fabricate the phantom using gelatin and water and different size of tumor such as 2 mm, 4 mm, 6 mm, 8 mm and 10 mm which has been inserted in the phantom, and obtained result were compared with dielectric mixing model approach. The dielectric properties of a fabricated phantom, and phantom embedded with different sizes of tumor, were obtained using an open-ended coaxial probe method and computed the effective dielectric properties using dielectric mixing model approach spanning the frequency range from 1 GHz to 10 GHz. It is observed that the measurement results are in quite good agreement with the result of the dielectric mixing model. The main aim of the paper is to observe the change in dielectric properties when the tumor sizes are changing and it is found that there are considerable changes in dielectric with different dimension of the tumor in the frequency range 1 GHz to 10 GHz.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"42-48"},"PeriodicalIF":3.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455266","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}
Pub Date : 2024-08-01DOI: 10.1109/JERM.2024.3434519
Robert Streeter;Jooeun Lee;Gabriel Santamaria Botello;Zorana Popović
Determination of the thickness, permittivity, and conductivity of tissue layers in the microwave region of the electromagnetic spectrum is relevant to a number of applications, such as breast-cancer imaging and non-invasive subcutaneous tissue thermometry. Many current characterization approaches are limited to one or two layers, often required to be aqueous. This paper presents simplified modeling of a stack of tissue layers as a series of complex impedance transmission lines in the 2–20 GHz decade. A near-field, broadband interrogation antenna designed for this frequency range and placed on the skin is validated with complex reflection coefficient measurements on seventeen different stacks of materials. Initial measurements are used to build a lookup table of features that are then used to classify three independent sets of follow-up measurements on the same stacks. After processing and consideration of very thin and very low loss materials, the error rates for classification are found to be between 5.9% and 14.7%. This confirms that features extracted from a simple, calibrated one-port broadband reflection coefficient measurement provide sufficient information to identify the composition of a layered stack, modeling tissue layers.
{"title":"Classification of Multi-Layer Tissue-Mimicking Dielectric Stacks From 2 to 20 GHz","authors":"Robert Streeter;Jooeun Lee;Gabriel Santamaria Botello;Zorana Popović","doi":"10.1109/JERM.2024.3434519","DOIUrl":"https://doi.org/10.1109/JERM.2024.3434519","url":null,"abstract":"Determination of the thickness, permittivity, and conductivity of tissue layers in the microwave region of the electromagnetic spectrum is relevant to a number of applications, such as breast-cancer imaging and non-invasive subcutaneous tissue thermometry. Many current characterization approaches are limited to one or two layers, often required to be aqueous. This paper presents simplified modeling of a stack of tissue layers as a series of complex impedance transmission lines in the 2–20 GHz decade. A near-field, broadband interrogation antenna designed for this frequency range and placed on the skin is validated with complex reflection coefficient measurements on seventeen different stacks of materials. Initial measurements are used to build a lookup table of features that are then used to classify three independent sets of follow-up measurements on the same stacks. After processing and consideration of very thin and very low loss materials, the error rates for classification are found to be between 5.9% and 14.7%. This confirms that features extracted from a simple, calibrated one-port broadband reflection coefficient measurement provide sufficient information to identify the composition of a layered stack, modeling tissue layers.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"36-41"},"PeriodicalIF":3.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455279","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}
Malignant melanoma, the aggressive form of skin cancer, progresses via radial and vertical growth. The aim of this study is to assess the feasibility of microwave-based diagnosis of melanoma at different stages of tumor progression. To this end, we used the physiological data for melanoma progression to develop a theoretical model of melanoma growth, followed by the oil-in-gelatin based tissue phantoms, which aim to mimic the dielectric behavior of the tissues under consideration. The phantoms are then dielectrically characterized using a slim-form open-ended coaxial probe by systematically sampling dielectric values across the mimicked skin surfaces at a range of points over the 0.5 – 26.5 GHz frequency range. The resulting observations revealed that the microwave spectroscopy exhibits the capability not only to distinguish between healthy and malignant skin, but also differentiate between tumors at different stages of vertical growth, which may not be visually discernible from the skin surface. The measured results are compared with the estimated dielectric values of malignant melanoma using Lichteneker's mixing equation obtained from the literature and it was observed that the measured results closely agree with the literature values.
{"title":"Models of Melanoma Growth for Assessment of Microwave-Based Diagnostic Tools","authors":"Jasmine Boparai;Rachel Tchinov;Oliver Miller;Yanis Jallouli;Milica Popović","doi":"10.1109/JERM.2024.3430315","DOIUrl":"https://doi.org/10.1109/JERM.2024.3430315","url":null,"abstract":"Malignant melanoma, the aggressive form of skin cancer, progresses via radial and vertical growth. The aim of this study is to assess the feasibility of microwave-based diagnosis of melanoma at different stages of tumor progression. To this end, we used the physiological data for melanoma progression to develop a theoretical model of melanoma growth, followed by the oil-in-gelatin based tissue phantoms, which aim to mimic the dielectric behavior of the tissues under consideration. The phantoms are then dielectrically characterized using a slim-form open-ended coaxial probe by systematically sampling dielectric values across the mimicked skin surfaces at a range of points over the 0.5 – 26.5 GHz frequency range. The resulting observations revealed that the microwave spectroscopy exhibits the capability not only to distinguish between healthy and malignant skin, but also differentiate between tumors at different stages of vertical growth, which may not be visually discernible from the skin surface. The measured results are compared with the estimated dielectric values of malignant melanoma using Lichteneker's mixing equation obtained from the literature and it was observed that the measured results closely agree with the literature values.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"305-315"},"PeriodicalIF":3.0,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041463","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}
Pub Date : 2024-07-17DOI: 10.1109/JERM.2024.3426270
Ali Kaiss;Md. Asiful Islam;Asimina Kiourti
We report Beat Estimation, a novel method used to calculate Heart Rate Variability (HRV) from low Signal to Noise Ratio (SNR) data (−7 dB to −4 dB in this work) acquired via wearable magnetocardiography (MCG). MCG activity is first collected using an in-house wearable sensor and filtered to remove noise outside the band of interest. Beat Estimation extracts a single heart beat from the filtered recording and correlates it with a small number of beats individually to average out the remaining noise. The de-noised beat is then correlated with the full recording to identify the location of each of the heart beats. Using these locations, HRV parameters are, finally, calculated. Results show $sim$99.9% accuracy in estimating HRV metrics using beat-to-beat intervals as opposed to traditional R-to-R-peak intervals. The average accuracy of detecting the true location of beats is shown to increase to 96.43% using Beat Estimation as opposed to 59.98% using our previous method that relied on R-peak detection. In summary, Beat Estimation renders wearable MCG sensors capable of accurately estimating HRV, despite the low SNR levels associated with sensor operation. The approach can be game-changing in assessing heart health, cardiovascular fitness, stress levels, cognitive workload, and more.
{"title":"Estimating Heart Rate Variability in Challenging Low SNR Regimes Using Wearable Magnetocardiography Sensors","authors":"Ali Kaiss;Md. Asiful Islam;Asimina Kiourti","doi":"10.1109/JERM.2024.3426270","DOIUrl":"https://doi.org/10.1109/JERM.2024.3426270","url":null,"abstract":"We report <sc>Beat Estimation</small>, a novel method used to calculate Heart Rate Variability (HRV) from low Signal to Noise Ratio (SNR) data (−7 dB to −4 dB in this work) acquired via wearable magnetocardiography (MCG). MCG activity is first collected using an in-house wearable sensor and filtered to remove noise outside the band of interest. <sc>Beat Estimation</small> extracts a single heart beat from the filtered recording and correlates it with a small number of beats individually to average out the remaining noise. The de-noised beat is then correlated with the full recording to identify the location of each of the heart beats. Using these locations, HRV parameters are, finally, calculated. Results show <inline-formula><tex-math>$sim$</tex-math></inline-formula>99.9% accuracy in estimating HRV metrics using beat-to-beat intervals as opposed to traditional R-to-R-peak intervals. The average accuracy of detecting the true location of beats is shown to increase to 96.43% using <sc>Beat Estimation</small> as opposed to 59.98% using our previous method that relied on R-peak detection. In summary, <sc>Beat Estimation</small> renders wearable MCG sensors capable of accurately estimating HRV, despite the low SNR levels associated with sensor operation. The approach can be game-changing in assessing heart health, cardiovascular fitness, stress levels, cognitive workload, and more.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"27-35"},"PeriodicalIF":3.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455311","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}
Pub Date : 2024-07-08DOI: 10.1109/JERM.2024.3420737
Yuchen Ma;Changrong Liu;Yong Huang;Hua Ke;Xueguan Liu
To improve the wireless power transfer efficiency (PTE) of implantable medical devices (IMDs), a receiving rectenna consisting of a magneto-electric (ME) heterostructure mechanical antenna combined with an RF inductive coil is proposed in this paper. The receiving antenna, which operates at 54 kHz, consists of a ME antenna of 30 × 10 × 0.456 mm3 and a 60-turn inductive coil wound of 30 × 12 × 3 mm3. The receiving and transmitting antennas are analyzed and the wireless power transfer performance is measured. The specific absorption rate (SAR) at the resonant frequency is simulated to satisfy the safety standard. The final measured PTE at a distance of 15 mm between the transmitting coil and the proposed receiving antenna is 2.8159%, which is considerably higher than that of a single ME antenna or an inductive coil. The proposed receiving antenna is suitable for wireless biomedical devices.
{"title":"Combined Magnetoelectric/Coil Receiving Antenna for Biomedical Wireless Power Transfer","authors":"Yuchen Ma;Changrong Liu;Yong Huang;Hua Ke;Xueguan Liu","doi":"10.1109/JERM.2024.3420737","DOIUrl":"https://doi.org/10.1109/JERM.2024.3420737","url":null,"abstract":"To improve the wireless power transfer efficiency (PTE) of implantable medical devices (IMDs), a receiving rectenna consisting of a magneto-electric (ME) heterostructure mechanical antenna combined with an RF inductive coil is proposed in this paper. The receiving antenna, which operates at 54 kHz, consists of a ME antenna of 30 × 10 × 0.456 mm<sup>3</sup> and a 60-turn inductive coil wound of 30 × 12 × 3 mm<sup>3</sup>. The receiving and transmitting antennas are analyzed and the wireless power transfer performance is measured. The specific absorption rate (SAR) at the resonant frequency is simulated to satisfy the safety standard. The final measured PTE at a distance of 15 mm between the transmitting coil and the proposed receiving antenna is 2.8159%, which is considerably higher than that of a single ME antenna or an inductive coil. The proposed receiving antenna is suitable for wireless biomedical devices.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"15-26"},"PeriodicalIF":3.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455310","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}
Pub Date : 2024-07-04DOI: 10.1109/JERM.2024.3419232
Leonardo Makinistian;Leandro Vives
Over the last decades, the interest on the biological effects of static and extremely low frequency magnetic fields (ELF-MF) on living organisms has been continuously growing. A myriad of bioeffects has been reported in the most diverse models, from bacteria and fungi to plants and even humans. Motivation has encompassed the most basic scientific curiosity, but also the concern for possible detrimental effects and the search for therapeutic and technological uses of ELF-MF. Experimentation has, to some extent, also focused on putting to test theoretical models of interaction. A substantial variety of devices, and even whole facilities, were developed to explore this yet poorly understood topic. In this review, we provide an up-to-date survey of the said devices and facilities, plus a revision on the various types of shielding reported in the literature. Finally, we enumerate a wide range of possible applications that are currently under study, whose development inevitably depends on an appropriate choice of field-generating devices, facilities and shielding. This should help researchers design their own experimental set ups from a wide perspective of what has already been developed and tested to date.
{"title":"Devices, Facilities, and Shielding for Biological Experiments With Static and Extremely Low Frequency Magnetic Fields","authors":"Leonardo Makinistian;Leandro Vives","doi":"10.1109/JERM.2024.3419232","DOIUrl":"https://doi.org/10.1109/JERM.2024.3419232","url":null,"abstract":"Over the last decades, the interest on the biological effects of static and extremely low frequency magnetic fields (ELF-MF) on living organisms has been continuously growing. A myriad of bioeffects has been reported in the most diverse models, from bacteria and fungi to plants and even humans. Motivation has encompassed the most basic scientific curiosity, but also the concern for possible detrimental effects and the search for therapeutic and technological uses of ELF-MF. Experimentation has, to some extent, also focused on putting to test theoretical models of interaction. A substantial variety of devices, and even whole facilities, were developed to explore this yet poorly understood topic. In this review, we provide an up-to-date survey of the said devices and facilities, plus a revision on the various types of shielding reported in the literature. Finally, we enumerate a wide range of possible applications that are currently under study, whose development inevitably depends on an appropriate choice of field-generating devices, facilities and shielding. This should help researchers design their own experimental set ups from a wide perspective of what has already been developed and tested to date.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"141-156"},"PeriodicalIF":3.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117311","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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