A Deep Learning Framework for Evaluating the Over-the-Air Performance of the Antenna in Mobile Terminals.

This study introduces RTEEMF (Real-Time Evaluation Electromagnetic Field)-PhoneAnts, a novel Deep Learning (DL) framework for the efficient evaluation of mobile phone antenna performance, addressing the time-consuming nature of traditional full-wave numerical simulations. The DL model, built on convolutional neural networks, uses the Near-field Electromagnetic Field (NEMF) distribution of a mobile phone antenna in free space to predict the Effective Isotropic Radiated Power (EIRP), Total Radiated Power (TRP), and Specific Absorption Rate (SAR) across various configurations. By converting antenna features and internal mobile phone components into near-field EMF distributions within a Huygens' box, the model simplifies its input. A dataset of 7000 mobile phone models was used for training and evaluation. The model's accuracy is validated using the Wilcoxon Signed Rank Test (WSR) for SAR and TRP, and the Feature Selection Validation Method (FSV) for EIRP. The proposed model achieves remarkable computational efficiency, approximately 2000-fold faster than full-wave simulations, and demonstrates generalization capabilities for different antenna types, various frequencies, and antenna positions. This makes it a valuable tool for practical research and development (R&D), offering a promising alternative to traditional electromagnetic field simulations. The study is publicly available on GitHub for further development and customization. Engineers can customize the model using their own datasets.

Attention Mask R-CNN with edge refinement algorithm for identifying circulating genetically abnormal cells.

Recent studies have suggested that circulating tumor cells with abnormalities in gene copy numbers in mononuclear cell-enriched peripheral blood samples, such as circulating genetically abnormal cells (CACs), can be used as a non-invasive tool to detect patients with benign pulmonary nodules. These cells are identified through fluorescence signals counting by using 4-color fluorescence in situ hybridization (FISH) technology that exhibits high stability, sensitivity, and specificity. When FISH data are analyzed, the overlapping cells and fluorescence noise is a great challenge for identifying of CACs, thereby seriously affecting the efficiency of clinical diagnosis. To address this problem, in this study, we proposed an end-to-end FISH-based method (CACNET) for CAC identification. CACNET achieved nuclear segmentation and counted 4-color staining signals through improved Mask region-based convolutional neural network (R-CNN), followed by cell category (normal cell, deletion cell, gain cell, or CAC) according to pathological criteria. Firstly, the segmentation accuracy of overlapping nuclei was improved by adding an edge constraint head during training. Then, the interference of fluorescence noise was reduced by fusing non-local module to reconstruct the feature extraction network of Mask R-CNN. We trained and tested the proposed model on a dataset comprising 700 frames with 58,083 nuclei. The Accuracy, Sensitivity, and Specificity (overall performance metric for the algorithm) of CAC identification with CACNET were 94.06%, 92.1%, and 99.8%, respectively. Moreover, the developed method exhibited approximately identification speed of approximately 0.22 s per frames. The results showed that the proposed method outperformed the existing CAC identification methods, making it a promising approach for early screening of lung cancer.

Dynamic Gesture Recognition Based on FMCW Millimeter Wave Radar: Review of Methodologies and Results.

As a convenient and natural way of human-computer interaction, gesture recognition technology has broad research and application prospects in many fields, such as intelligent perception and virtual reality. This paper summarized the relevant literature on gesture recognition using Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar from January 2015 to June 2023. In the manuscript, the widely used methods involved in data acquisition, data processing, and classification in gesture recognition were systematically investigated. This paper counts the information related to FMCW millimeter wave radar, gestures, data sets, and the methods and results in feature extraction and classification. Based on the statistical data, we provided analysis and recommendations for other researchers. Key issues in the studies of current gesture recognition, including feature fusion, classification algorithms, and generalization, were summarized and discussed. Finally, this paper discussed the incapability of the current gesture recognition technologies in complex practical scenes and their real-time performance for future development.

A Lightweight and Robust Framework for Circulating Genetically Abnormal Cells (CACs) Identification Using 4-Color Fluorescence In Situ Hybridization (FISH) Image and Deep Refined Learning.

Circulating genetically abnormal cells (CACs) constitute an important biomarker for cancer diagnosis and prognosis. This biomarker offers high safety, low cost, and high repeatability, which can serve as a key reference in clinical diagnosis. These cells are identified by counting fluorescence signals using 4-color fluorescence in situ hybridization (FISH) technology, which has a high level of stability, sensitivity, and specificity. However, there are some challenges in CACs identification, due to the difference in the morphology and intensity of staining signals. In this concern, we developed a deep learning network (FISH-Net) based on 4-color FISH image for CACs identification. Firstly, a lightweight object detection network based on the statistical information of signal size was designed to improve the clinical detection rate. Secondly, the rotated Gaussian heatmap with a covariance matrix was defined to standardize the staining signals with different morphologies. Then, the heatmap refinement model was proposed to solve the fluorescent noise interference of 4-color FISH image. Finally, an online repetitive training strategy was used to improve the model's feature extraction ability for hard samples (i.e., fracture signal, weak signal, and adjacent signals). The results showed that the precision was superior to 96%, and the sensitivity was higher than 98%, for fluorescent signal detection. Additionally, validation was performed using the clinical samples of 853 patients from 10 centers. The sensitivity was 97.18% (CI 96.72-97.64%) for CACs identification. The number of parameters of FISH-Net was 2.24 M, compared to 36.9 M for the popularly used lightweight network (YOLO-V7s). The detection speed was about 800 times greater than that of a pathologist. In summary, the proposed network was lightweight and robust for CACs identification. It could greatly increase the review accuracy, enhance the efficiency of reviewers, and reduce the review turnaround time during CACs identification.

Assessment of Twin Fetal Exposure to Environmental Magnetic and Electromagnetic Fields.

Fetal development is vital in the human lifespan. Therefore, it is essential to characterize exposure by a series of typical environmental magnetic and electromagnetic fields. In particular, there has recently been a sharp increase in the twin birth rate. However, lack of appropriate models has prohibited dosimetric evaluation, restricting characterization of the impact of these environmental factors on twins. The present study developed two whole-body pregnant models of 31 and 32 weeks of gestation with twin fetuses and explored several typical exposure scenarios, including 50-Hz uniform magnetic field exposure, local 125-kHz magnetic field (MF), and 13.56-MHz electromagnetic field exposure, as well as wideband planewave radiofrequency (RF) exposure from 20 to 6000 MHz. Finally, dosimetric results were derived. Compared to the singleton pregnancy with similar weeks of gestation, twin fetuses were overexposed at 50-Hz uniform MF, but they were probably underexposed in the RF scenarios with frequencies for wireless communications. Furthermore, the twin fetuses manifested large dosimetric variability compared to the singleton, which was attributed to the incident direction and fetal position. Based on the analysis, the dosimetric results over the entire gestation period were estimated. The results can be helpful to estimate the risk of twin-fetal exposure to electromagnetic fields and examine the conservativeness of the international guidelines.© 2022 Bioelectromagnetics Society.

Exposure of Infants to Gradient Fields in a Baby MRI Scanner.

In pediatric magnetic resonance imaging (MRI), infants are exposed to rapid, time-varying gradient magnetic fields, leading to electric fields induced in the body of infants and potential safety risks (e.g. peripheral nerve stimulation). In this numerical study, the in situ electric fields in infants induced by small-sized gradient coils for a 1.5 T MRI scanner were evaluated. The gradient coil set was specially designed for the efficient imaging of infants within a small-bore (baby) scanner. The magnetic flux density and induced electric fields by the small x, y, z gradient coils in an infant model (8-week-old with a mass of 4.3 kg) were computed using the scalar potential finite differences method. The gradient coils were driven by a 1 kHz sinusoidal waveform and also a trapezoidal waveform with a 250 µs rise time. The model was placed at different scan positions, including the head area (position I), chest area (position II), and body center (position III). It was found that the induced electric fields in most tissues exceeded the basic restrictions of the ICNIRP 2010 guidelines for both waveforms. The electric fields were similar in the region of interest for all coil types and model positions but different outside the imaging region. The y-coil induced larger electric fields compared with the x- and z- coils. Bioelectromagnetics. 43:69-80, 2022. © 2021 Bioelectromagnetics Society.

Modulation of resting-state brain functional connectivity by exposure to acute fourth-generation long-term evolution electromagnetic field: An fMRI study.

By now, the neurophysiological effect of electromagnetic field (EMF) exposure and its underlying regulating mechanisms are not well manifested. In this study, we aimed to investigate whether acute long-term evolution (LTE) EMF exposure could modulate brain functional connectivity using regional homogeneity (ReHo) method and seed-based analysis on resting-state functional magnetic resonance imaging (fMRI). We performed the LTE-EMF exposure experiment and acquired the resting-state brain activities before and after EMF exposure. Then we applied ReHo index to characterize the localized functional connectivity and seed-based method to evaluate the inter-regional functional connectivity. Statistical comparisons were conducted to identify the possible evidence of brain functional connectivity modulation induced by the acute LTE-EMF exposure. We found that the acute LTE-EMF exposure modulated localized intra-regional connectivity (p < 0.05, AlphaSim corrected, voxel size ≥ 18) and inter-regional connectivity in some brain regions (p < 0.05, AlphaSim corrected, voxel size ≥ 18). Our results may indicate that the approaches relying on network-level inferences could provide deeper insight into the acute effect on human functional activity induced by LTE-EMF exposure. Bioelectromagnetics. 40:42-51, 2019. © 2018 Wiley Periodicals, Inc.

Deformable torso phantoms of Chinese adults for personalized anatomy modelling.

In recent years, there has been increasing demand for personalized anatomy modelling for medical and industrial applications, such as ergonomics device development, clinical radiological exposure simulation, biomechanics analysis, and 3D animation character design. In this study, we constructed deformable torso phantoms that can be deformed to match the personal anatomy of Chinese male and female adults. The phantoms were created based on a training set of 79 trunk computed tomography (CT) images (41 males and 38 females) from normal Chinese subjects. Major torso organs were segmented from the CT images, and the statistical shape model (SSM) approach was used to learn the inter-subject anatomical variations. To match the personal anatomy, the phantoms were registered to individual body surface scans or medical images using the active shape model method. The constructed SSM demonstrated anatomical variations in body height, fat quantity, respiratory status, organ geometry, male muscle size, and female breast size. The masses of the deformed phantom organs were consistent with Chinese population organ mass ranges. To validate the performance of personal anatomy modelling, the phantoms were registered to the body surface scan and CT images. The registration accuracy measured from 22 test CT images showed a median Dice coefficient over 0.85, a median volume recovery coefficient (RCvlm ) between 0.85 and 1.1, and a median averaged surface distance (ASD) < 1.5 mm. We hope these phantoms can serve as computational tools for personalized anatomy modelling for the research community.

Dosimetry of electromagnetic field exposure of an active armlet and its electromagnetic interference to the cardiac pacemakers using adult, child and infant models.

Wearable devices have been popularly used with people from different age groups. As a consequence, the concerns of their electromagnetic field (EMF) exposure to the human body and their electromagnetic interference (EMI) to the implanted medical devices have attracted many studies. The aim of this study was to evaluate the human exposure to the EMF of an active radiofrequency identification (RFID) armlet as well as its EMI to the cardiac pacemaker (CP). Different human models from various age groups were applied to assess the result variability. The scalar potential finite element method was utilized in the simulation. Local EMF exposure and the exposure to the central nerve system tissues were evaluated using different metrics. EMI to the CP was assessed in terms of the conducted voltage to the CP. The results from all the models revealed that the studied RFID armlet would not produce the EMF exposure exceeding the safety limits. The calculated interference voltage was highly dependent on the distance between the RFID armlet and the CP (i.e. the physical dimension of the individual model). The results proposed to evaluate the appropriateness of the current EMI measurement protocol for this kind of devices used by the infants.

A reverberation chamber for rodents' exposure to wideband radiofrequency electromagnetic fields with different small-scale fading distributions.

A reverberation chamber (RC) is realized for the rodents' in vivo exposure to electromagnetic fields (EMFs) with various small-scale fading characteristics. Its performance is evaluated to ensure the exposure experiments from 0.85 to 2.60 GHz. By different configurations, line-of-sight and non-line-of-sight exposures can be established. The measured electric field in the RC is analyzed to determine its statistical distribution. We accordingly reconstruct the EMF environment by numerical methods. Simulations are carried to compare the dosimetric variability due to different small-scale fading characteristics. It demonstrates that the surveyed fading distribution will not change the specific absorption rate in the rats. The possibility to reproduce the realistic multi-reflective EMF environment by adjusting the structures of the RC is discussed. It is the first reported in vivo exposure system aiming to provide the EMF exposure with different small-scale fading distributions.

Dosimetry of infant exposure to power-frequency magnetic fields: variation of 99th percentile induced electric field value by posture and skin-to-skin contact.

Infant exposure to 50 Hz magnetic fields from power lines was numerically analyzed in this study. Dosimetric variability due to posture and skin-to-skin contact was evaluated using human anatomical models including a recently developed model of a 12-months-old infant. As proposed by the International Commission on Non-Ionizing Radiation Protection, the induced E-field strength (99th percentile value, E99 ) for the central nerve systems (E99_CNS ) and peripheral nerve system (E99_PNS ), were used as metrics. Results showed that the single (free of contact with others) infant model has lower E99 (E99_CNS and E99_PNS inclusive) compared with single adult and child models when exposed to the same power-frequency magnetic field. Also, studied postures of sitting, standing, or arm-up, would not change E99 _PNS . However, skin-to-skin contact with other models could significantly raise induced E-field strength in the infant (e.g., contact on 0.93% of the infant's total surface increased E99_PNS by 213%). Simulations with canonical models were conducted to assess different factors contributing to the E99 enhancement. Results indicated the importance of thoroughly investigating the conservativeness of current safety guidelines in the case of skin-to-skin contact, especially with infants.

Dosimetry for infant exposures to electronic article surveillance system: posture, physical dimension and anatomy.

The use of electronic article surveillance (EAS) systems has become popular in many public sites. As a consequence, concern has risen about infant exposure to magnetic fields (MFs) from this kind of device. To evaluate infant exposure to MFs of an EAS system (operating at 125 kHz and 13.56 MHz), we numerically compared dosimetric results among adult, child and infant models. Results revealed that postures insignificantly influenced dosimetric results if there was a similar cross-sectional area under exposure. Although safety limits are unlikely to be exceeded, the infant has higher SAR values for brain and central nervous system tissues compared with adult (1.5x at 125 kHz and 112x at 13.56 MHz), which deserve further investigation. Infant's specific anatomy (e.g., non-proportionally large head and high fat content) did not induce higher SAR values. The numerical models developed in the study (stroller and postured infant models) could be freely used for nonprofit academic research.

Generation of infant anatomical models for evaluating electromagnetic field exposures.

Realistic anatomical modeling is essential in analyzing human exposure to electromagnetic fields. Infants have significant physical and anatomical differences compared with other age groups. However, few realistic infant models are available. In this work, we developed one 12-month-old male whole body model and one 17-month-old male head model from magnetic resonance images. The whole body and head models contained 28 and 30 tissues, respectively, at spatial resolution of 1 mm × 1 mm × 1 mm. Fewer identified tissues in the whole body model were a result of the low original image quality induced by the fast imaging sequence. The anatomical and physical parameters of the models were validated against findings in published literature (e.g., a maximum deviation as 18% in tissue mass was observed compared with the data from International Commission on Radiological Protection). Several typical exposure scenarios were realized for numerical simulation. Dosimetric comparison with various adult and child anatomical models was conducted. Significant differences in the physical and anatomical features between adult and child models demonstrated the importance of creating realistic infant models. Current safety guidelines for infant exposure to radiofrequency electromagnetic fields may not be conservative.

Dosimetric variability of the rats' exposure to electromagnetic pulses.

Rats' exposure to electromagnetic pulses (EMPs) has been conducted using an EMP simulator for various biological endpoints. In contrast, information about the EMP energy distribution and its variability in rats is lacking. EMPs are signals with spectrum concentrating in several hundred MHz, leading to EM absorption patterns different from those obtained at high frequencies. In this study, two anatomical models of rats (a male and a female) were reconstructed from magnetic resonance imaging. The models had the same posture as in the exposure experiments. Realistic EMPs were acquired directly from the EMP simulator and applied to the simulations. The interaction of the EMP with the rat was analyzed through the finite-difference time-domain method. Two approaches were utilized to calculate the energy absorption at the tissue and whole-body levels. Dosimetric variability due to incident directions, polarizations, exposure signals simplification, and rat separation was evaluated in this study. The variability result differed substantially from that of the non-constrained rats' exposure experiments. The result sensitivity to frequency and amplitude was discussed as well. The work can be used as a basis to determine the uncertainty and to formulate a standard experimental protocol for this type of experiment.

Dosimetric study on eye's exposure to wide band radio frequency electromagnetic fields: variability by the ocular axial length.

This paper evaluates the variability of specific absorption rate (SAR) in the human eye. This variability results from changes in ocular axial length (OAL), which is common in many ophthalmologic and vision abnormalities, including myopia. A generic eye model was reconstructed according to published data. The feasibility of using the generic model in numerical research of electromagnetic fields (EMF) was demonstrated by means of comparative simulations with eye models reconstructed from magnetic resonance (MR) scans. Free-form deformation (FFD) was used to deform the OAL of the generic eye model. Thus, 64 deformed eyes were created and were categorized according to the OAL increase. The finite-difference time-domain (FDTD) method was applied in the simulations. The results revealed that changing the OAL does not increase EMF absorption in the eyes or the eye tissues. No additional induced temperature rise was produced by the changes of OAL. The results also indicated that the non-pathological increment of the OAL, which is inevitable during the childhood, does not increase the SAR in the eyes.

Evaluation of Chinese populational exposure to environmental electromagnetic field based on stochastic dosimetry and parametric human modelling.

This study aimed to estimate the distribution of the whole-body averaged specific absorption rate (WBSAR) using several measurable physique parameters for Chinese adult population exposed to environmental electromagnetic fields (EMFs) of current wireless communication frequencies, and to discuss the effects of these physique parameters in the frequency-dependent dosimetric results. The physique distribution of Chinese adults was obtained from the National Physical Fitness and Health Database comprising 81,490 adult samples. The number of physique parameters used to construct the surrogate model was reduced to three via mutual information analysis. A stochastic method with 40 deterministic simulations was used to generate frequency-dependent and gender-specific surrogate models for WBSAR via polynomial chaos expansion. In the simulations, we constructed anatomically correct models conforming to the targeted physique parameters via deformable human modelling technique, which was based on deep learning from the image database including 767 Chinese adults. Thereafter, we analysed the sensitivity of the physique parameters to WBSAR by covariance-based Sobol decomposition. The results indicated that the generated models were consistent with the targeted physique parameters. The estimated dosimetric results were validated using finite-difference time-domain simulations (the error was < 6% across all the investigated frequencies for WBSAR). The novelty of the study included that it demonstrated the feasibility of estimating the individual WBSAR using a limited number of physique parameters with the aid of surrogate modelling. In addition, the population-based distribution of the WBSAR in Chinese adults was firstly presented in the manuscript. The results also indicated that the different combinations of physique parameter, dependent on genders and frequencies, significantly influenced the WBSAR, although the general conservativeness of the guidelines of the International Commission on Non-Ionizing Radiation and Protection can be confirmed in the surveyed population.

Semi-automatic Framework for Voxel Human Deformation Modeling.

BACKGROUND: With the advancement of computer and medical imaging technologies, a number of high-resolution, voxel-based, full-body human anatomical models have been developed for medical education, industrial design, and physics simulation studies. However, these models are limited in many applications because they are often only in an upstanding posture. OBJECTIVE: To quickly develop multi-pose human models for different applications. A semi-automatic framework for voxel deformation is proposed in the study. METHODS: This paper describes a framework for human pose deformation based on three-dimensional (3D) medical images. The voxel model is first converted into a surface model using a surface reconstruction algorithm. Second, a deformation skeleton based on human bones is defined, and the surface model is bound to the skeleton. The bone Glow algorithm is used to assign weights to the surface vertices. Then, the model is deformed to the target posture by using the Smoothed Rotation Enhanced As-Rigid-As-Possible (SR-ARAP) algorithm. Finally, the volume-filling algorithm is applied to refill the tissues into the deformed surface model. RESULTS: The proposed framework is used to deform two standing human models, and the sitting and running models are developed. The results show that the framework can successfully develop the target pose. When compared to the results of the As-Rigid-As-Possible algorithm, SR-ARAP preserves local tissues better. CONCLUSION: The study proposes a frame for voxel human model deformation and improves the local tissue integrity during deformation.

In utero and early-life exposure of rats to a Wi-Fi signal: screening of immune markers in sera and gestational outcome.

An experimental approach was used to assess immunological biomarkers in the sera of young rats exposed in utero and postnatal to non-ionizing radiofrequency fields. Pregnant rats were exposed free-running, 2 h/day and 5 days/week to a 2.45 GHz Wi-Fi signal in a reverberation chamber at whole-body specific absorption rates (SAR) of 0, 0.08, 0.4, and 4 W/kg (with 10, 10, 12, and 9 rats, respectively), while cage control rats were kept in the animal facility (11 rats). Dams were exposed from days 6 to 21 of gestation and then three newborns per litter were further exposed from birth to day 35 postnatal. On day 35 after birth, all pups were sacrificed and sera collected. The screening of sera for antibodies directed against 15 different antigens related to damage and/or pathological markers was conducted using enzyme-linked immunosorbent assay (ELISA). No change in humoral response of young pups was observed, regardless of the types of biomarker and SAR levels. This study also provided some data on gestational outcome following in utero exposure to Wi-Fi signals. Mass evaluation of dams and pups and the number of pups per litter was monitored, and the genital tracts of young rats were observed for abnormalities by measuring anogenital distance. Under these experimental conditions, our observations suggest a lack of adverse effects of Wi-Fi exposure on delivery and general condition of the animals.