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arXiv 2024年

作者： Jun, Yohan Liu, Qiang Gong, Ting Cho, Jaejin Fujita, Shohei Yong, Xingwang Huang, Susie Y. Ning, Lipeng Yendiki, Anastasia Rathi, Yogesh Bilgic, Berkin Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital BostonMA United States Department of Radiology Harvard Medical School BostonMA United States Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Electrical and Computer Engineering Northeastern University BostonMA United States Department of Artificial Intelligence and Robotics Sejong University Seoul Korea Republic of Zhejiang University Hangzhou China Harvard/MIT Health Sciences and Technology CambridgeMA United States Department of Psychiatry Brigham and Women’s Hospital BostonMA United States Department of Radiology Brigham and Women’s Hospital BostonMA United States

Purpose: To develop and evaluate a new pulse sequence for highly accelerated distortion-free diffusion MRI (dMRI) by inserting an additional echo without prolonging TR, when generalized slice dithered enhanced resolution (gSlider) radiofrequency encoding is used for volumetric acquisition. Methods: A phase-reversed interleaved multi-echo acquisition (PRIME) was developed for rapid, high-resolution, and distortion-free dMRI, which includes two echoes where the first echo is for target diffusion-weighted imaging (DWI) acquisition with high-resolution and the second echo is acquired with either 1) lower-resolution for high-fidelity field map estimation, or 2) matching resolution to enable efficient diffusion relaxometry acquisitions. The sequence was evaluated on in vivo data acquired from healthy volunteers on clinical and Connectome 2.0 scanners. Results: In vivo experiments demonstrated that 1) high in-plane acceleration (Rin-plane of 5-fold with 2D partial Fourier) was achieved using the high-fidelity field maps estimated from the second echo, which was made at a lower resolution/acceleration to increase its SNR while matching the effective echo spacing of the first readout, 2) high-resolution diffusion relaxometry parameters were estimated from dual-echo PRIME data using a white matter model of multi-TE spherical mean technique (MTE-SMT), and 3) high-fidelity mesoscale DWI at 550 μm isotropic resolution could be obtained in vivo by capitalizing on the high-performance gradients of the Connectome 2.0 scanner. Conclusion: The proposed PRIME sequence enabled highly accelerated, high-resolution, and distortion-free dMRI using an additional echo without prolonging scan time when gSlider encoding is utilized. Copyright © 2024, The Authors. All rights reserved.

关键词： Nuclear magnetic resonance

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Microsystems for biofilm characterization and sensing - A review (vol 2, 100015, 2020)

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BIOFILM 2020年 2卷 100015页

作者： Subramanian, Sowmya MEMS Sensors and Actuators Laboratory University of Maryland College Park MD USA Department of Electrical and Computer Engineering University of Maryland College Park MD USA Institute for Systems Research University of Maryland College Park MD USA Fischell Department of Bioengineering University of Maryland College Park MD USA Robert E. Fischell Institute for Biomedical Devices University of Maryland College Park MD USA

Biofilms are the primary cause of clinical bacterial infections and are impervious to typical amounts of antibiotics, necessitating very high doses for elimination. Therefore, it is imperative to have suitable methods for characterization to develop novel methods of treatment that can complement or replace existing approaches using significantly lower doses of antibiotics. This review presents some of the current developments in microsystems for characterization and sensing of bacterial biofilms. Initially, we review current standards for studying biofilms that are based on invasive and destructive end-point biofilm characterization. Additionally, biofilm formation and growth is extremely sensitive to various growth and environmental parameters that cause large variability in biofilms between repeated experiments, making it very difficult to compare experimental repeats and characterize the temporal characteristics of these organisms. To address these challenges, recent developments in the field have moved toward systems and miniature devices that can aid in the non-invasive characterization of bacterial biofilms. Our review focuses on several types of microsystems for biofilm evaluation including optical, electrochemical, and mechanical systems. This review will show how these devices can lead to better understanding of the physiology and function of these communities of bacteria, which can eventually lead to the development of novel treatments that do not rely on high-dosage antibiotics.

关键词： Biofilm Microsystems Sensors Microfluidics

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Dynamically Adjusting Case Reporting Policy to Maximize Privacy and Public Health Utility in the Face of a Pandemic

arXiv

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arXiv 2021年

作者： Brown, James Thomas Yan, Chao Xia, Weiyi Yin, Zhijun Wan, Zhiyu Gkoulalas-Divanis, Aris Kantarcioglu, Murat Malin, Bradley A. Department of Biomedical Informatics Vanderbilt University Medical Center NashvilleTN United States Department of Electrical Engineering and Computer Science Vanderbilt University NashvilleTN United States IBM Watson Health CambridgeMA United States Department of Computer Science University of Texas at Dallas DallasTX United States Department of Biostatistics Vanderbilt University Medical Center NashvilleTN United States

Objective: Supporting public health research and the public’s situational awareness during a pandemic requires continuous dissemination of infectious disease surveillance data. Legislation, such as the Health Insurance Portability and Accountability Act of 1996 (HIPAA) and recent state-level regulations, permits sharing de-identified person-level data;however, current de-identification approaches are limited. Namely, they are inefficient, relying on retrospective disclosure risk assessments, and do not flex with changes in infection rates or population demographics over time. In this paper, we introduce a framework to dynamically adapt de-identification for near-real time sharing of person-level surveillance data. Materials and Methods: The framework leverages a simulation mechanism, capable of application at any geographic level, to forecast the re-identification risk of sharing the data under a wide range of generalization policies. The estimates inform weekly, prospective policy selection to maintain the proportion of records corresponding to a group size less than 11 (PK11) at or below 0.1. Fixing the policy at the start of each week facilitates timely dataset updates and supports sharing granular date information. We use August 2020 through October 2021 case data from Johns Hopkins University and the Centers for Disease Control and Prevention to demonstrate the framework’s effectiveness in maintaining the PK11 threshold of 0.01. Results: When sharing COVID-19 county-level case data across all US counties, the framework’s approach meets the threshold for 96.2% of daily data releases, while a policy based on current de-identification techniques meets the threshold for 32.3%. Conclusion: Periodically adapting the data publication policies preserves privacy while enhancing public health utility through timely updates and sharing epidemiologically critical features. © 2021, CC BY.

关键词： Diseases

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Knee deep in Error: Unraveling the accuracy limitations of consumer-grade wearable motion sensors with limited degrees of freedom computing knee joint angles

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computers in biology and medicine 2025年 193卷 110469页

作者： Abby L Hollingworth Jayson B Hutchinson Jocelynn R Bechtel Ryan M Chapman University of Rhode Island Department of Electrical Computer and Biomedical Engineering Fascitelli Center for Advanced Engineering 2 East Alumni Avenue Kingston RI 02881 USA. Electronic address: ahollingworth@uri.edu. University of Rhode Island Department of Kinesiology 25 W. Independence Way Kingston RI 02881 USA. Electronic address: hutchinsonja20@uri.edu. University of Rhode Island Department of Kinesiology 25 W. Independence Way Kingston RI 02881 USA. Electronic address: jbechtel@uri.edu. University of Rhode Island Department of Electrical Computer and Biomedical Engineering Fascitelli Center for Advanced Engineering 2 East Alumni Avenue Kingston RI 02881 USA University of Rhode Island Department of Kinesiology 25 W. Independence Way Kingston RI 02881 USA. Electronic address: rmchapman@uri.edu.

Consumer-grade wearable inertial measurement units (IMUs) with limited degrees of freedom (DOF) are common computing knee motion before/after clinical intervention. Appropriate use requires attaching sensors per manufacturer's instructions. However, IMU misplacement error remains problematic. Thus, we assessed error computing sagittal knee angles across sensor misplacement orientations of one consumer-grade IMU system with 6DOF. We hypothesized error would increase during frontal plane misplacement. Ten young, healthy individuals (20.9 ± 0.7 years) were enrolled. IMUs were adhered/calibrated per manufacturer instructions and IMU-computed knee angles were compared to optical motion capture (MOCAP) during self-selected speed treadmill walking. Shin/thigh IMUs were then moved across sagittal, frontal, and transverse planes (±10°, ±20°). At each orientation, IMU calibration and treadmill walking was re-completed. Error was computed between MOCAP/IMU by calculating the difference and computing the absolute value (i.e. absolute value error). This was averaged across participants at each sensor position (i.e. average absolute value error). Bland Altman analyses assessed MOCAP/IMU agreement. ANOVAs assessed how plane, segment, and falsified IMU angle impacted error. MOCAP/IMUs were highly correlated with IMUs achieving clinically acceptable error (<5°) when placed correctly or with sagittal/transverse plane misalignment. Frontal plane (varus and valgus) and shin sensor misalignment caused significantly greater error (∼7°), likely due to limited IMU DOF. Limited DOF IMUs can accurately compute knee motion even with significant sagittal/transverse plane misalignment. However, frontal plane placement is critical for proper function, implying patients with frontal plane deformities should not use reduced DOF IMUs. Moreover, patient education is critical for appropriate deployment of wearable IMUs.

关键词： Biomechanics Error Inertial measurement unit Knee Knee angles Wearable sensor

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Structural and performance comparison between SU-8 microfabricated and 3D-printed microneedle electrodes

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Journal of 3D Printing in Medicine 2020年第1期4卷 29-44页

作者： Soltanzadeh, Ramin Afsharipour, Elnaz Anssari, Neda Mansouri, Behzad Shafai, Cyrus Biomedical Graduate Studies Program University of Manitoba Winnipeg R3T 5V6 MB Canada Electrical and Computer Engineering Department University of Manitoba Winnipeg R3T 5V6 MB Canada Department of Internal Medicine (Neurology) University of Manitoba Winnipeg R3A 1R9 MB Canada

Aim: This study is aimed to compare the structure and performance of 3D-printed and microfabricated microneedle arrays (MNAs). Materials & methods: MNAs were produced using either stereolithography printing or were micro-fabricated using SU-8 polymer. The structure of both MNA types were tested and compared through scanning electron microscopy. MNA performance was also evaluated through electrical impedence spectroscopy and nerve conduction velocity testing. Results & conclusion: The 3D-printed MNAs were shown to have higher gain than microfabricated MNAs at high frequencies. However, the selectivity of the microfabricated MNAs is more than 3D-printed MNAs. Scanning electron microscopy image comparison also showed significant differences between the output of the 3D-printed MNAs and the microfabricated MNAs. It was understood that the microfabricated MNAs' geometries are closer to the primary design than the 3D-printed MNAs. © 2020 Future Medicine Ltd.

关键词： 3D printing microfabrication microneedle array performance difference strucutral difference

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Additive manufacturing of multilayered microfluidic devices with densely packed microscale features 23

Additive manufacturing of multilayered microfluidic devices ...

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23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019

作者： Chu, Chia-Heng Buretugs, Enerelt Owens, Jacob M. Liu, Ruxiu Lee, Dohwan Fatih Sarioglu, A. School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA United States School of Chemical and Biomolecular Engineering Georgia Institute of Technology AtlantaGA United States Wallace H. Coutler Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA United States

ISBN: (纸本)9781733419000

The challenges in effectively removing the support material from a fully enclosed microfluidic device hinder the use of 3D printing to create microfluidic devices with intricate geometries. Here, we introduce a fabrication method that utilizes centrifugation that can effortlessly and efficiently remove the sacrificial support materials from 3D printed microfluidic devices with densely packed microfeatures. By using our fabrication method, we were able to print a complex multi-layered microfluidic device (with a >120mb file size) with more than 85,000 embedded micropillars and effectively remove the wax support material from the printed microfluidic device. © 2019 CBMS-0001.

关键词： Microfluidics

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The Response of EEG Signal on Brain Relaxation Meditation Using Different Type of Zikr

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Journal of Physics: Conference Series 2021年第1期2071卷

作者： N N Abd Razak K A Sidek K Y D Alaa N F Mohd Nasir Department of Electrical and Computer Engineering Kulliyyah of Engineering International Islamic University Malaysia. Department of Computer Engineering College of Computer Science and Engineering University of Ha'il Kingdom of Saudi Arabia. Biomedical Electronic Engineering Programme Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Malaysia.

Depression and stress are increasingly prevalent in today's society, owing to people's hectic, competitive, and demanding lifestyles. These illnesses had become very common, particularly among young and middle-aged people, and suicidal ideation had been identified as one of the leading causes of death by the World Health Organization (WHO). Nature sound (sound of downpours or beach) has been linked to depression and anxiety in neurology research, and it has been shown to be an alternative to alleviate anxiety. The electroencephalogram (EEG) waveform has been discovered to possess the potential in identifying information from the brain signal as well as data from the past via Bluetooth communication. The waveform use in the study are the result of a few experiments. In this study, EEG data were collected from eight subjects, four males and four females, in between the age of 20 to 30 years old and in good health, using the BrainLink device. The participants were asked to listen to two playlists of zikr, Allah, Ya Allah, and SubhanAllah, during the experiments. To smooth the signal, the Butterworth filter was used. Later, the extracted features were Alpha, Beta, and Delta waves, which were segmented based on the filtered signal. To complete the decision-making stage, the average value of amplitude differences and the p-value test were performed in the final phase. Based on the results of the experiments, it is clear that zikr is dominant in Delta wave. In terms of data hypothesis analysis, the results of both experiment were differentiated to determine which brain signal was dominant, and p-value testing was performed. Furthermore, this research is an alternative to current methods because it suggest that zikr has the tendency to alter a person's brain state to be either in a relaxed or calm mode regardless of the type of zikr recitation. As an outcome, the study recommends the relationship of the reaction of EEG signal on brain relaxation with different types of zikr

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Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

arXiv

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arXiv 2022年

作者： Aubry, Jean-Francois Bates, Oscar Boehm, Christian Pauly, Kim Butts Christensen, Douglas Cueto, Carlos Gélat, Pierre Guasch, Lluis Jaros, Jiri Jing, Yun Jones, Rebecca Li, Ningrui Marty, Patrick Montanaro, Hazael Neufeld, Esra Pichardo, Samuel Pinton, Gianmarco Pulkkinen, Aki Stanziola, Antonio Thielscher, Axel Treeby, Bradley Van't Wout, Elwin Physics for Medicine Paris INSERM U1273 ESPCI Paris PSL University CNRS UMR 8063 France Department of Bioengineering Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Institute of Geophysics ETH Zürich Sonneggstrasse 5 Zürich8092 Switzerland Department of Radiology Stanford University StanfordCA United States Department of Biomedical Engineering Department of Electrical and Computer Engineering University of Utah United States Department of Surgical Biotechnology Division of Surgery and Interventional Science University College London LondonNW3 2PF United Kingdom Earth Science and Engineering Department Imperial College London London United Kingdom Centre of Excellence IT4Innovations Faculty of Information Technology Brno University of Technology Bozetechova 2 Brno612 00 Czech Republic Graduate Program in Acoustics The Pennsylvania State University University Park PA16802 United States Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill North Carolina State University NC United States Department of Electrical Engineering Stanford University StanfordCA United States Zurich Switzerland Laboratory for Acoustics / Noise control Empa Swiss Federal Laboratories for Materials Science and Technology Dubendorf Switzerland Zurich Switzerland Radiology and Clinical Neurosciences Departments Cumming School of Medicine University of Calgary Canada Department of Applied Physics University of Eastern Finland Kuopio70211 Finland Department of Medical Physics and Biomedical Engineering University College London Gower Street LondonWC1E 6BT United Kingdom Technical University of Denmark Denmark Danish Research Center for Magnetic Resonance Copenhagen University Hospital Hvidovre Denmark Institute for Mathematical and Computational Engineering School of Engineering and Faculty of Mathematics Pontificia Universidad Catolica de Chile Santiago Chile

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular-spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons. Copyright © 2022, The Authors. All rights reserved.

关键词： Bone

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Combiner and HyperCombiner Networks: Rules to Combine Multimodality MR Images for Prostate Cancer Localisation

arXiv

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arXiv 2023年

作者： Yan, Wen Chiu, Bernard Shen, Ziyi Yang, Qianye Syer, Tom Min, Zhe Punwani, Shonit Emberton, Mark Atkinson, David Barratt, Dean C. Hu, Yipeng Department of Electrical Engineering City University of Hong Kong 83 Tat Chee Avenue Hong Kong Centre for Medical Image Computing Department of Medical Physics & Biomedical Engineering Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London Gower St LondonWC1E 6BT United Kingdom Centre for Medical Imaging Division of Medicine University College London LondonW1W 7TS United Kingdom Division of Surgery & Interventional Science University College London Gower St LondonWC1E 6BT United Kingdom Department of Physics & Computer Science Wilfrid Laurier University 75 University Avenue West WaterlooONN2L 3C5 Canada

One of the distinct characteristics of radiologists reading multiparametric prostate MR scans, using reporting systems like PI-RADS v2.1, is to score individual types of MR modalities, including T2-weighted, diffusion-weighted, and dynamic contrast-enhanced, and then combine these image-modality-specific scores using standardised decision rules to predict the likelihood of clinically significant cancer. This work aims to demonstrate that it is feasible for low-dimensional parametric models to model such decision rules in the proposed Combiner networks, without compromising the accuracy of predicting radiologic labels. First, we demonstrate that either a linear mixture model or a nonlinear stacking model is sufficient to model PI-RADS decision rules for localising prostate cancer. Second, parameters of these combining models are proposed as hyperparameters, weighing independent representations of individual image modalities in the Combiner network training, as opposed to end-to-end modality ensemble. A HyperCombiner network is developed to train a single image segmentation network that can be conditioned on these hyperparameters during inference for much-improved efficiency. Experimental results based on 751 cases from 651 patients compare the proposed rule-modelling approaches with other commonly-adopted end-to-end networks, in this downstream application of automating radiologist labelling on multiparametric MR. By acquiring and interpreting the modality combining rules, specifically the linear-weights or odds ratios associated with individual image modalities, three clinical applications are quantitatively presented and contextualised in the prostate cancer segmentation application, including modality availability assessment, importance quantification and rule *** Codes 68T07 © 2023, CC BY.

关键词： Magnetic resonance imaging

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An electrical model characterization of an electronic nose chemical sensor using a programmable system-on-a-chip based AFE

An electrical model characterization of an electronic nose c...

引用

International Young Engineers Forum (YEF-ECE)

作者： Joã o J. M. Santos Susana I. C. J. Palma Carina Esteves Hugo Gamboa Joã o Pedro Oliveira Ana C. A. Roque Department of Electrical and Computer Engineering NOVA School of Science and Technology NOVA University of Lisbon Caparica Portugal Associate Laboratory i4HB &#x2013 Institute for Health and Bioeconomy NOVA School of Science and Technology NOVA University of Lisbon Caparica Portugal UCIBIO &#x2013 Applied Molecular Biosciences Unit Department of Chemistry NOVA School of Science and Technology NOVA University of Lisbon Caparica Portugal LIBPhys - Laboratory for Instrumentation Biomedical Engineering and Radiation Physics NOVA School of Science and Technology NOVA University of Lisbon Caparica Portugal Center for Technology and Systems (CTS) &#x2013 UNINOVA NOVA School of Science and Technology NOVA University of Lisbon Caparica Portugal

ISBN: (数字)9781665467315

ISBN: (纸本)9781665467322

The diagnosis of many diseases involves invasive detection methods, which are both painful and stressing for patients. In the last decades, the ever-growing development in electronic nose (E-Nose) technology made them great candidates for non-invasive disease detection methods. Such devices mimic the human olfactory system through a set of sensors which produce signals that can be associated with diseases. Recently, a class of low-cost and innovative ionogel sensors, developed by our group demonstrated their full applicability in E-Nose systems, opening a new and promising approach to the field. However, the operation of such sensor needs a background calibration phase which relies on the correct characterization and parameterization of the corresponding electrical sensor *** paper proposes a model characterization methodology based on a set of frequency responses acquisitions of the sensor, under several humidity conditions. To obtain a flexible acquisition tool capable of acquiring accurate results, an analog front-end (AFE) circuit to interface with the interdigitated electrode (IDE) sensors is presented. Such AFE circuit is fully implemented using a programmable system-on-a-chip (PSoC), helping to reduce system size and cost. Lastly, a comparison between the electrical model and data acquired with the proposed system is presented.

关键词： Electrodes Chemical sensors Humidity Sensor phenomena and characterization Electronic noses Sensor systems Sensors

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