Average SNR Research Articles

WaveFlex: A Smart Surface for Private 5G CBRS Networks

We present the design and implementation of WaveFlex, the first smart surface that enhances Private 5G networks operating under the shared-license framework in the Citizens Broadband Radio Service frequency band. WaveFlex works in the presence of frequency diversity: multiple nearby base stations operating on different frequencies, as dictated by a Spectrum Access System coordinator. It also handles time dynamism: due to the dynamic sharing rules of the CBRS band, base stations occasionally switch channels, especially when priority users enter the network. Finally, WaveFlex operates independently of the network itself, not requiring access to nor modification of the gNB or UEs, yet it remains compliant with and effective on prevailing cellular protocols. We have designed and fabricated WaveFlex on a custom multi-layer PCB, software defined radio based network monitor, and supporting control software and hardware. Our experimental evaluation benchmarks operational Private 5G and LTE networks running at full line rate. In a realistic indoor office scenario, 5G experimental results demonstrate an 8.58~dB average SNR gain, and an average throughput gain of 10.77 Mbps under a single gNB, and 12.84 Mbps under three gNBs, corresponding to throughput improvements of 18.4% and 19.5%, respectively.

Sparse representation-based noise reduction for BOTDR monitoring signals in foundation pit anchor cables

Abstract In foundation pit monitoring, the Brillouin optical time-domain reflectometer (BOTDR) system typically has a low signal-to-noise ratio (SNR). To solve this problem, a BOTDR signal noise-suppression method based on sparse representation is proposed in this paper. The initial dictionary is constructed from the eigenvectors of the normalized graph Laplace matrix, and K-SVD and OMP algorithms are combined to update the dictionary and coefficient matrix to sparsely represent the essential characteristics of the BOTDR signal, filtering out random noise lacking sufficient similarity data and improving the quality of the reconstructed signal. To verify the effectiveness of the proposed algorithm, a BOTDR temperature-sensing experimental system was designed and used to test the denoising performance of the sparse representation algorithm quantitatively. The experimental results showed that the average SNR of the algorithm on six temperature levels was 27.4%, 15.4%, 13.1%, and 17.9% higher than that of WDD, EMT, EMD, and the raw signals, respectively. The average sample entropy (SE) was 24.4%, 16.0%, 15.4%, and 47.9% lower than that of WDD, EMT, EMD, and the raw signals, respectively. Additionally, the proposed Laplace-based dictionary outperformed the DCT dictionary. Finally, the monitoring project of the Beijing Stomatological Hospital was used as a test site. The sparse representation algorithm was used to conduct noise reduction experiments on the on-site anchor cable fiber optic monitoring signals. The average signal SE decrease of monitoring signals at the site reached 45.2%. This study provides an effective signal denoising method for the application of BOTDR technology in foundation pit monitoring.

Development and evaluation of a free-form-based optical antenna with enhanced channel performance

Optical receiving antennas play a pivotal role in enhancing the communication quality of visible light communication (VLC) systems. In this study, we propose an innovative optical receiving antenna based on free-form surfaces. Initially, the layout scheme for the LED array is meticulously optimized to ensure uniform indoor illumination. Subsequently, a three-piece integrated optical receiving antenna is designed using XY polynomial free-form surfaces with the primary objectives of amplifying the optical gain, augmenting the received power, and elevating the signal-to-noise ratio (SNR). To further validate the efficacy of the proposed optical receiving antenna, an indoor VLC channel model is established, and its performance is rigorously analyzed. Experimental outcomes reveal that the mean square error of indoor illumination stands at 113.3 lx, the optical gain of the free-form optical receiving antenna reaches an impressive 11.29, the semiregular field of view spans 35.2°, the average received power amounts to 6.1251 dBm, the average SNR attains 84.7054 dB, and the radius of the optical spot is a mere 1.5 mm. Consequently, the optimized free-form optical receiving antenna can guarantee high-speed and stable communication within indoor VLC systems, thereby furnishing crucial technical support for the advancement of VLC communication technology.

Signal-to-Noise Ratio Analysis of Bandpass Sampling Time-Modulated Fourier Transform Spectroscopy

In Bandpass Sampling Fourier Transform Spectroscopy, a comprehensive method for evaluating signal-to-noise ratio (SNR) has not yet been established. This paper employs an energy conservation approach to analyze the relationship of SNR between interferogram and spectra in Bandpass Sampling Time-Modulated Fourier Transform Spectroscopy (BPS-FTS). It systematically presents models for the average SNR of the system interferogram and the average SNR of reconstructed spectra under different parameters. These models are compared with SNR models in traditional Fourier transform spectroscopy (FTS) and are mutually validated through theoretical modeling and simulation analysis. It provides a theoretical basis and simulation verification for the design and implementation of the system.

Hybrid Wavelet‐Deep Learning Framework for Fluorescence Microscopy Images Enhancement

ABSTRACTFluorescence microscopy is a powerful tool for visualizing cellular structures, but it faces challenges such as noise, low contrast, and autofluorescence that can hinder accurate image analysis. To address these limitations, we propose a novel hybrid image enhancement method that combines wavelet‐based denoising, linear contrast enhancement, and convolutional neural network‐based autofluorescence correction. Our automated method employs Haar wavelet transform for noise reduction and a series of adaptive linear transformations for pixel value adjustment, effectively enhancing image quality while preserving crucial details. Furthermore, we introduce a semantic segmentation approach using CNNs to identify and correct autofluorescence in cellular aggregates, enabling targeted mitigation of unwanted background signals. We validate our method using quantitative metrics, such as signal‐to‐noise ratio (SNR) and peak signal‐to‐noise ratio (PSNR), demonstrating superior performance compared to both mathematical and deep learning‐based techniques. Our method achieves an average SNR improvement of 8.5 dB and a PSNR increase of 4.2 dB compared with the original images, outperforming state‐of‐the‐art methods such as BM3D and CLAHE. Extensive testing on diverse datasets, including publicly available human‐derived cardiosphere and fluorescence microscopy images of bovine endothelial cells stained for mitochondria and actin filaments, showcases the flexibility and robustness of our approach across various acquisition conditions and artifacts. The proposed method significantly improves fluorescence microscopy image quality, facilitating more accurate and reliable analysis of cellular structures and processes, with potential applications in biomedical research and clinical diagnostics.

Outage Probability Analysis For Dual-Hop Asymmetric Fading WBAN

Wireless Body Area Networks (WBANs) involve wireless communication among resource constrained sensors located on the human body, which are used to capture physiological signals. A significant challenge faced by WBANs is their reliability. It is crucial to analyze the outage of the system to ensure improved reliability in the system design. This study focuses on analyzing the outage performance of dual hop WBANs under different fading scenarios, wherein the channel coefficients follow different distributions. Outage performance is evaluated using the CDF of the SNR of different fading scenarios. Furthermore, the outage performance of these fading distributions are compared to each other and a target outage probability of 10% was pre-set to evaluate the performance of the composite channels from worst to best. Results show that the minimum acceptable threshold SNRs at average SNR = 15 dB for Gamma-Weibull, Gamma-Log-Normal, Gamma-Rayleigh, Gamma–Gamma, Gamma-Rician and Gamma-Nakagami-m are - 4 dB, 2 dB, 4 dB, 6 dB, 8 dB and 10 dB respectively. The analytical outcomes for all the results for different cases are validated through Monte Carlo simulations. There is a lack of comprehensive frameworks in the literature that address all scenarios according to the authors’ knowledge.

Weighted joint LRTs for cooperative spectrum sensing using K-means clustering

In this paper, a blind centralized cooperative spectrum sensing (CSS) with soft decision fusion is considered. The fusion center (FC) constructs the energy vector from the collaborating secondary nodes. The energy feature is assumed to be an efficient measure, as it is widely used and directly correlates with the strength of the received signal. The K-means clustering algorithm is employed to extract descriptive statistical features about the distributions of the absence and presence of the primary user (PU) signal, such as the mean and non-centrality parameter. In the framework of this statistical analysis, the signal-to-noise ratio (SNR) at each node is easily estimated and examined. Equal, selective, and weighted combining techniques are applied to develop three joint likelihood ratio test (JLRT)-based algorithms. These algorithms are implemented in the context of simple hypothesis testing, where the distribution of the data is fully specified. Furthermore, they are justified by the Neyman-Pearson theorem, which constructs the most powerful test for a given significance level. The proposed selective and weighted JLRT approaches are based on the estimated SNRs at each sensor, reflecting their reliability. Several comparison scenarios between the proposed algorithms, K-means, fuzzy c-means (FCM), and OR-rule are simulated over Rayleigh fading channel with low average SNR and few samples. The simulation results reveal that the proposed tests outperform other CSS techniques. Additionally, asymptotic theoretical expressions for probability of detection and the probability of false alarm are derived, which show high agreement with the simulated results.

Low-dose high-resolution chest CT in adults with cystic fibrosis: intraindividual comparison between photon-counting and energy-integrating detector CT

BackgroundRegular disease monitoring with low-dose high-resolution (LD-HR) computed tomography (CT) scans is necessary for the clinical management of people with cystic fibrosis (pwCF). The aim of this study was to compare the image quality and radiation dose of LD-HR protocols between photon-counting CT (PCCT) and energy-integrating detector system CT (EID-CT) in pwCF.MethodsThis retrospective study included 23 pwCF undergoing LD-HR chest CT with PCCT who had previously undergone LD-HR chest CT with EID-CT. An intraindividual comparison of radiation dose and image quality was conducted. The study measured the dose-length product, volumetric CT dose index, effective dose and signal-to-noise ratio (SNR). Three blinded radiologists assessed the overall image quality, image sharpness, and image noise using a 5-point Likert scale ranging from 1 (deficient) to 5 (very good) for image quality and image sharpness and from 1 (very high) to 5 (very low) for image noise.ResultsPCCT used approximately 42% less radiation dose than EID-CT (median effective dose 0.54 versus 0.93 mSv, p < 0.001). PCCT was consistently rated higher than EID-CT for overall image quality and image sharpness. Additionally, image noise was lower with PCCT compared to EID-CT. The average SNR of the lung parenchyma was lower with PCCT compared to EID-CT (p < 0.001).ConclusionIn pwCF, LD-HR chest CT protocols using PCCT scans provided significantly better image quality and reduced radiation exposure compared to EID-CT.Relevance statementIn pwCF, regular follow-up could be performed through photon-counting CT instead of EID-CT, with substantial advantages in terms of both lower radiation exposure and increased image quality.Key PointsPhoton-counting CT (PCCT) and energy-integrating detector system CT (EID-CT) were compared in 23 people with cystic fibrosis (pwCF).Image quality was rated higher for PCCT than for EID-CT.PCCT used approximately 42% less radiation dose and offered superior image quality than EID-CT.Graphical

Evaluating 4G Network Performance at UTeM Campus to Facilitate 5G Implementation in Malaysia

As Malaysia transitions to 5G technology, evaluating 4G coverage performance is essential for preparing the groundwork for advanced networks. This project focuses on assessing the radio communication link performance of 4G systems at the University Technical Malaysia Malacca (UTeM) campus. The goal is to assist Mobile Broadband (MBB) service providers in developing efficient long-term strategies for Malaysian university campuses and enhancing 4G coverage. The study conducted measurement campaigns and real-time performance analysis using the G-Net Track app, recording key metrics such as minimum RSRP (-115 dBm off-peak, -117 dBm peak), RSRQ (-18 dB off-peak, -17 dB peak), and average SNR (11.178 dB off-peak, 11.003 dB peak). Signal quality varied with 25.3% excellent and 4.5% poor in normal weather, and 21.8% excellent and 5.8% poor in rainy conditions. Proximity to the base station showed the best RSRP of -68 dBm at 56m and the worst at -110 dBm around 915m away. The study concludes that mobile network operator (MNO) performance is influenced by traffic load, weather conditions, and distance from the base station. Understanding these dynamics can help MBB service providers enhance coverage, reliability, and overall user experience on university campuses and beyond. Future research considering additional KPIs and environmental factors will further enrich these insights, supporting robust network planning and management.

RMS asymmetry: a robust metric of galaxy shapes in images with varied depth and resolution

Structural disturbances, such as galaxy mergers or instabilities, are key candidates for driving galaxy evolution, so it is important to detect and quantify galaxies hosting these disturbances spanning a range of masses, environments, and cosmic times. Traditionally, this is done by quantifying the asymmetry of a galaxy as part of the concentration-asymmetry-smoothness system, , and selecting galaxies above a certain threshold as merger candidates. However, in this work, we show that , is extremely dependent on imaging properties – both resolution and depth – and thus defining a single threshold is impossible. We analyze an alternative root-mean-squared asymmetry, , and show that it is independent of noise down to the average SNR per pixel of 1. However, both metrics depend on the resolution. We argue that asymmetry is, by design, always a scale-dependent measurement, and it is essential to define an asymmetry at a given physical resolution, where the limit should be defined by the size of the smallest features one wishes to detect. We measure asymmetry of a set of z≈0.1 galaxies observed with HST, HSC, and SDSS, and show that after matching the resolution of all images to 200 pc, we are able to obtain consistent measurements with all three instruments despite the vast differences in the original resolution or depth. We recommend that future studies use measurement when evaluating asymmetry, where x is defined by the physical size of the features of interest, and is kept consistent across the dataset, especially when the redshift or image properties of galaxies in the dataset vary.

Improvement of MRS at ultra-high field using a wireless RF array.

We aim to assess a straightforward technique to enhance spectral quality in the brain, particularly in the cerebellum, during 7 T MRI scans. This is achieved through a wireless RF array insert designed to mitigate signal dropouts caused by the limited transmit field efficiency in the inferior part of the brain. We recently developed a wireless RF array to improve MRI and 1H-MRS at 7 T by augmenting signal via inductive coupling between the wireless RF array and the MRI coil. In vivo experiments on a Siemens 7 T whole-body human scanner with a Nova 1Tx/32Rx head coil quantified the impact of the dorsal cervical array in improving signal in the posterior fossa, including the cerebellum, where the transmit efficiency of the coil is inherently low. The 1H-MRS experimental protocol consisted of paired acquisition of data sets, both with and without the RF array, using the semi-LASER and SASSI sequences. The overall results indicate that the localized 1H-MRS is improved significantly in the presence of the array. Comparison of in vivo 1H-MRS plots in the presence versus absence of the array demonstrated an average SNR enhancement of a factor of 2.2. LCModel analysis reported reduced Cramér-Rao lower bounds, indicating more confident fits. This wireless RF array can significantly increase detection sensitivity. It may reduce the RF transmission power and data acquisition time for 1H-MRS and MRI applications, specifically at 7 T, where 1H-MRS requires a high-power RF pulse. The array could provide a cost-effective and efficient solution to improve detection sensitivity for human 1H-MRS and MRI in the regions with lower transmit efficiency.

A Second-Order Continuous-Time Dynamical System for Solving Sparse Image Restoration Problems

The quality of images captured digitally or transmitted over networks is distorted by noise during the process. The current methods of image restoration can be ineffective in dealing with intricate noise patterns or may be slow or imprecise. This paper fills this gap by presenting a new second-order continuous-time dynamical system for denoising of images in image restoration. The approach used in this work poses the problem as a convex quadratic program that can, thus, be solved for optimality. The existence and uniqueness of a global solution are theoretically demonstrated, and the condition for the global strong convergence of the system’s trajectory is provided. The method presented in this paper is shown to be useful in a number of experiments on image restoration. As for the performance, it is higher than that of other known algorithms, with an average SNR equal to 34.78 and a Structural Similarity Index Measure (SSIM) of 0.959 for the reconstructed images. Such improvements demonstrate the effectiveness of the second-order dynamical system approach in actual image restoration applications.

Joint k-ω Space Image Reconstruction and Data Fitting for Chemical Exchange Saturation Transfer Magnetic Resonance Imaging.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is a novel MRI technology to image certain compounds at extremely low concentrations. Long acquisition time to measure signals at a set of offset frequencies of the Z-spectra and to repeat measurements to reduce noise pose significant challenges to its applications. This study explores correlations of CEST MR images along the spatial and Z-spectral dimensions to improve MR image quality and robustness of magnetization transfer ratio (MTR) asymmetry estimation via a joint k-ω reconstruction model. The model was formulated as an optimization problem with respect to MR images at all frequencies ω, while incorporating regularizations along the spatial and spectral dimensions. The solution was subject to a self-consistency condition that the Z-spectrum of each pixel follows a multi-peak data fitting model corresponding to different CEST pools. The optimization problem was solved using the alternating direction method of multipliers. The proposed joint reconstruction method was evaluated on a simulated CEST MRI phantom and semi-experimentally on choline and iopamidol phantoms with added Gaussian noise of various levels. Results demonstrated that the joint reconstruction method was more tolerable to noise and reduction in number of offset frequencies by improving signal-to-noise ratio (SNR) of the reconstructed images and reducing uncertainty in MTR asymmetry estimation. In the choline and iopamidol phantom cases with 10.5% noise in the measurement data, our method achieved an averaged SNR of 31.0 dB and 32.2 dB compared to the SNR of 24.7 dB and 24.4 dB in the conventional reconstruction approach. It reduced uncertainty of the MTR asymmetry estimation over all regions of interest by 54.4% and 43.7%, from 1.71 and 2.38 to 0.78 and 1.71, respectively.

Analysis of signal-to-noise ratio of spatial heterodyne spectroscopy

We have established a novel spatial heterodyne spectroscopy (SHS) signal-to-noise ratio (SNR) model, relating the spectral SNR to the spectral band and resolution, which helps guide the instrument's design and optimization and assess the spectral quality. The experimental and simulation results show that the spectral resolution affects the SNR differently under different noise types and spectral characteristics of the measured targets, which fully validates the novel SHS SNR model. Despite the disadvantage of multiplexing in SHS, we determine the SNR advantage of SHS over the grating spectroscopy (GS) through rigorous theoretical derivations. In 94.34 % of the polychromatic light detections, the average SNR of SHS is 2–31 times higher than that of GS. In emission spectra detections, the SNR gain of SHS relative to GS is up to 1–2 orders of magnitude. In additive noise domination, the SNR gain reaches 1–3 orders of magnitude.

Time-Resolved Dynamic Optical Coherence Tomography for Retinal Blood Flow Analysis.

Optical coherence tomography (OCT) representations in clinical practice are static and do not allow for a dynamic visualization and quantification of blood flow. This study aims to present a method to analyze retinal blood flow dynamics using time-resolved structural OCT. We developed novel imaging protocols to acquire video-rate time-resolved OCT B-scans (1024 × 496 pixels, 10 degrees field of view) at four different sensor integration times (integration time of 44.8 µs at a nominal A-scan rate of 20 kHz, 22.4 µs at 40 kHz, 11.2 µs at 85 kHz, and 7.24 µs at 125 kHz). The vessel centers were manually annotated for each B-scan and surrounding subvolumes were extracted. We used a velocity model based on signal-to-noise ratio (SNR) drops due to fringe washout to calculate blood flow velocity profiles in vessels within five optic disc diameters of the optic disc rim. Time-resolved dynamic structural OCT revealed pulsatile SNR changes in the analyzed vessels and allowed the calculation of potential blood flow velocities at all integration times. Fringe washout was stronger in acquisitions with longer integration times; however, the ratio of the average SNR to the peak SNR inside the vessel was similar across all integration times. We demonstrated the feasibility of estimating blood flow profiles based on fringe washout analysis, showing pulsatile dynamics in vessels close to the optic nerve head using structural OCT. Time-resolved dynamic OCT has the potential to uncover valuable blood flow information in clinical settings.

Long-term assessment and analysis of the radiometric quality of standard data products for Chinese Gaofen-1/2/6/7 optical remote sensing satellites

The first Chinese Gaofen (GF) remote sensing satellite was launched in August 2013 and has been in orbit for more than 10 years, providing a rich variety of image product data for remote sensing applications in various industries, with other remote sensing satellites of the GF series. To ensure the reliability of the information generated via remote sensing applications, all remote sensing images must undergo systematic quality evaluation. The quality of GF satellites is evaluated almost comprehensively during in-orbit testing at the early stage after launch; however, the remaining evaluations of product quality including geometric or radiometric calibrations are performed only annually. Thus, long-term systematic image quality evaluations are lacking, and the quality level and long-term change trends of the image products are unknown. These deficits have introduced uncertainty in the application of these products. This study aimed to establish a radiometric quality evaluation index framework for GF satellites to comprehensively measure the radiometric quality of GF image products. Multiple types of sample data, such as uniform field, knife-edge target, and radiometric calibration field data with different reflectance features, were acquired globally. Four core indexes, namely, the relative radiometric correction accuracy (RRCA), absolute radiometric correction accuracy (ARCA), modulation transfer function (MTF), and signal-to-noise ratio (SNR), were used to analyze and evaluate the long-term radiometric quality of the images from four GF optical remote sensing satellites: GF1, GF2, GF6, and GF7. The four GF satellites had high SNR and RRCA but low dynamic MTF and variable ARCA for different reflectance features. For example, the average SNRs for the four satellites reached 42.66, 43.91, 44.33, and 47.46 dB; the average RRCA (@root-mean-square errors) values reached 1.6%, 1.0%, 1.6%, and 0.1%; the average MTF values (at Nyquist frequency) of the panchromatic bands were only 0.15, 0.12, 0.07 and 0.04; and the difference in ARCA for different reflectance targets was approximately 10%. In the long time series, the SNRs for each sensor of the four GF satellites were high and stable for high-reflectance features, whereas the RCA and SNR values for low-reflectance features and the MTF of the sensors fluctuated in a cyclic manner. Meanwhile, large dynamic fluctuations and episodic image quality problems occurred at certain local time points, which must be considered during practical applications. The findings presented here will lay a foundation for the in-depth application of GF images.

Minimizing Task Age upon Decision for Low-Latency MEC Networks Task Offloading with Action-Masked Deep Reinforcement Learning.

In this paper, we consider a low-latency Mobile Edge Computing (MEC) network where multiple User Equipment (UE) wirelessly reports to a decision-making edge server. At the same time, the transmissions are operated with Finite Blocklength (FBL) codes to achieve low-latency transmission. We introduce the task of Age upon Decision (AuD) aimed at the timeliness of tasks used for decision-making, which highlights the timeliness of the information at decision-making moments. For the case in which dynamic task generation and random fading channels are considered, we provide a task AuD minimization design by jointly selecting UE and allocating blocklength. In particular, to solve the task AuD minimization problem, we transform the optimization problem to a Markov Decision Process problem and propose an Error Probability-Controlled Action-Masked Proximal Policy Optimization (EMPPO) algorithm. Via simulation, we show that the proposed design achieves a lower AuD than baseline methods across various network conditions, especially in scenarios with significant channel Signal-to-Noise Ratio (SNR) differences and low average SNR, which shows the robustness of EMPPO and its potential for real-time applications.

Feasibility study of real-time imaging of an Ir-192 source using compact gamma camera with curved diverging collimator for brachytherapy

Brachytherapy is a treatment method that requires the accurate positioning of a radioactive source to deliver high doses to a tumor while minimizing exposure to surrounding tissues. Herein, we propose a compact gamma camera system based on a diverging collimator for real-time source positioning during brachytherapy. In the process of developing and fabricating such a gamma camera system, Monte Carlo simulations for diverging and pinhole collimators are performed under conditions that are similar to the actual detection environment, with the camera-to-source distance set at 50 cm to verify the feasibility of the gamma camera. Full width at half maximum (FWHM) and signal-to-noise ratio (SNR) values are analyzed based on the horizontal and vertical profiles at each location as the source shifts stepwise from the center to the right and diagonal direction. On average, the diverging collimator had FWHM values of 18 and 13 mm and SNR values of 30 and 31, while the pinhole collimator had FWHM values of 26 and 25 mm and SNR values of 47 and 46 when profiled horizontally and vertically. The diverging collimator has a lower SNR than pinhole collimator but performs better in terms of spatial resolution. Additionally, to test the performance of the manufactured gamma camera, the distance between the camera and the source was set to 100 cm and an experiment was conducted. The experimental results exhibit a trend similar to the simulation. Numerically, the average FWHM value were 39 mm in the vertical direction and 71 mm in the horizontal direction. Additionally, the average SNR values were 27 for the vertical direction and 17 for the horizontal direction. Based on these results, we confirm the possibility of Ir-192 source imaging.

Exploration of Digital Filter on Cardiac Monitor through Carotid Pulse and PCG (Phonocardiogram)

Heart defect early detection and correct diagnosis have become important healthcare priorities. Tools for monitoring cardiac problems are constantly being developed, with the PCG (Phonocardiogram) and Cardiac Monitor via Carotid Pulse essential for heart evaluation. Although condenser microphones embedded in electric stethoscopes have been used in past research as PCG sensors, more advancements are still required to reduce received noise. This study investigates how well a Chebyshev type-II digital filter works to reduce noise on the cardiac monitor using PCG and carotid pulse. The PCG sensor is the GY-MAX 9814 module, which is interfaced with an Arduino Uno microcontroller. Matlab, Visual Studio (used as a graph viewer), and Doppler Simulator (used as a phantom cardiac signal) are used. SNR (Signal to Noise Ratio) is used in the analysis to assess the effectiveness of two digital filter orders. The average SNR value for the Doppler Simulator is 0.001404 dB at order 2, however, it climbs dramatically to 18.60023 dB at level 4 according to the results of the SNR analysis. The average SNR value in human signals is 11.50718 dB before the filter, 0.001404 dB after the post-order 2 filter, and 12.0009 dB after the post-order 4 filter. According to the results, the digital filter of order 4 is more effective in reducing noise. This study highlights the possibility of an order 4 digital filter to improve the Cardiac Monitor through PCG and Carotid Pulse. Through enhanced signal quality, the creation of this gadget holds the potential for streamlining the identification of cardiac problems. Future developments in this technology could lead to more precise and trustworthy cardiac exams, which would help with early diagnosis and treatment of cardiovascular health.

In vivo enhancement of calf MRI at 7 T via optimized flexible metasurfaces.

Ultrahigh field (≥7 T) MRI is at the cutting edge of medical imaging, enabling enhanced spatial and spectral resolution as well as enhanced susceptibility contrast. However, transmit ( ) field inhomogeneity due to standing wave effects caused by the shortened RF wavelengths at 7 T is still a challenge to overcome. Novel hardware methods such as dielectric pads have been shown to improve the field inhomogeneity but are currently limited in their corrective effect by the range of high-permittivity materials available and have a fixed shelf life. In this work, an optimized metasurface design is presented that demonstrates in vivo enhancement of the field. A prototype metasurface was optimized by an empirical capacitor sweep and by varying the period size. Phantom temperature experiments were performed to evaluate potential metasurface heating effects during scanning. Lastly, in vivo gradient echo images and maps were acquired on five healthy subjects on a 7 T system. Dielectric pads were also used as a comparison throughout the work as a standard comparison. The metasurfaces presented here enhanced the average relative SNR of the gradient echo images by a factor of 2.26 compared to the dielectric pads factor of 1.61. Average values reflected a similar enhancement of 27.6% with the metasurfaces present versus 8.9% with the dielectric pads. The results demonstrate that metasurfaces provide superior performance to dielectric padding as shown by maps reflecting their direct effects and resulting enhancements in image SNR at 7 T.