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Magnetic Micromanipulation for In Vivo Measurement of Stiffness Heterogeneity and Anisotropy in the Mouse Mandibular Arch

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Research 2020年第1期2020卷 1409-1419页

作者： Min Zhu Kaiwen Zhang Hirotaka Tao Sevan Hopyan Yu Sun Department of Mechanical and Industrial Engineering University of TorontoCanada M5S 3G8 Program in Developmental and Stem Cell Biology Research InstituteThe Hospital for Sick ChildrenTorontoONCanada M5G 0A4 Department of Molecular Genetics University of TorontoCanada M5S 1A8 Division of Orthopaedic Surgery The Hospital for Sick Children and University of TorontoCanada M5G 1X8 Institute of Biomaterials and Biomedical Engineering University of TorontoCanada M5S 3G9 Department of Electrical and Computer Engineering University of TorontoCanada M5S 3G4

The mechanical properties of tissues are pivotal for morphogenesis and disease *** approaches have enabled measurements of the spatial distributions of viscoelastic properties among embryonic and pathological model systems and facilitated the generation of important hypotheses such as durotaxis and tissue-scale phase *** likely are many unexpected aspects of embryo biomechanics we have yet to discover which will change our views of mechanisms that govern development and *** area in the blind spot of even the most recent approaches to measuring tissue stiffness is the potentially anisotropic nature of that ***,we report a magnetic micromanipulation device that generates a uniform magnetic field gradient within a large workspace and permits measurement of the variation of tissue stiffness along three orthogonal *** applying the device to the organ-stage mouse embryo,we identify spatially heterogenous and directionally anisotropic stiffness within the mandibular *** properties correspond to the domain of expression and the angular distribution of fibronectin and have potential implications for mechanisms that orient collective cell movements and shape tissues during *** of anisotropic properties extends the repertoire of current methods and will enable the generation and testing of hypotheses.

关键词： transition. stiffness anisotropic

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Multi-Channel FLANN Adaptive Filter for Speckle & Impulse Noise Elimination from Color Doppler Ultrasound Images

Multi-Channel FLANN Adaptive Filter for Speckle & Impulse No...

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Emerging Trends in Communication, Control and Computing (ICONC3), International Conference on

作者： Manish Kumar Sunil Kumar Jangir Sudhansu Kumar Mishra Sumit Kumar Choubey Dilip Kumar Choubey Biomedical Engineering School of Engineering & Technology Mody University of Science & Technology Lachhamangarh India Computer Science & Engineering School of Engineering & Technology Mody University of Science & Technology Lachhamangarh India Electrical Engineering Birla Institute of Technology Mesra Ranchi India Electronics & Telecommunication Engineering Pune Institute of Engineering Technology Pune India School of Computer Science & Engineering Vellore Institute of Technology Vellore India

ISBN: (数字)9781728114200

ISBN: (纸本)9781728114217

The conventional fixed filters cannot be employed for removing the mixed noise of Color Doppler Ultrasound (CDUS) images because it affects the features of the image awkwardly. Consequently, identifying an internal blockage or hemorrhage of the patient become arduous in such conditions. Hence, the evolutionary multi-channel Functional Link Artificial Neural Network (M-FLANN) has been proposed to get rid of Speckle noise from the CDUS images. In this paper, the performance of the M-FLANN and other five competitive filters is evaluated in terms of qualitative and quantitative measures.

关键词： Color Doppler Ultasound Denoising Functional Link Artificial Neural Network Impulse Noise Speckle Noise Impulse noise Noise reduction speckle noise color Doppler ultrasound feature image images adaptive filters

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Modulating hip stiffness with a robotic exoskeleton immediately changes gait

Modulating hip stiffness with a robotic exoskeleton immediat...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jongwoo Lee Haley R. Warren Vibha Agarwal Meghan E. Huber Neville Hogan Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Biomedical Engineering University of Vermont Burlington VT USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Restoring healthy kinematics is a critical component of assisting and rehabilitating impaired locomotion. Here we tested whether spatiotemporal gait patterns can be modulated by applying mechanical impedance to hip joints. Using the Samsung GEMS-H exoskeleton, we emulated a virtual spring (positive and negative) between the user's legs. We found that applying positive stiffness with the exoskeleton decreased stride time and hip range of motion for healthy subjects during treadmill walking. Conversely, the application of negative stiffness increased stride time and hip range of motion. These effects did not vary over long nor short repeated exposures to applied stiffness. In addition, minimal transient behavior was observed in spatiotemporal measures of gait when the stiffness controller transitioned between on and off states. These results suggest that changes in gait behavior induced by applying hip stiffness were purely a mechanical effect. Together, our findings indicate that applying mechanical impedance using lower-limb assistive devices may be an effective, minimally-encumbering intervention to restore healthy gait patterns.

关键词： Hip Exoskeletons Legged locomotion Read only memory Kinematics Springs Time measurement

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Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI

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Neuroimage: Reports 2022年第2期2卷 100091-100091页

作者： DiGregorio, J. Gibicar, A. Khosravani, H. Maralani, P. Jabehdar Tardif, J.-C. Tyrrell, P.N. Moody, A.R. Khademi, A. Electrical Computer and Biomedical Engineering Dept. Ryerson University Toronto ON Canada Division of Neurology Department of Medicine University of Toronto Toronto ON Canada Department of Medical Imaging University of Toronto Toronto ON Canada Montreal Heart Institute Montreal QU Canada Department of Medicine Université de Montréal QU Canada Department of Statistical Science University of Toronto Toronto ON Canada Keenan Research Center for Biomedical Science St. Michael's Hospital Unity Health Network Toronto ON Canada Institute for Biomedical Engineering Science and Technology (iBEST) A Partnership Between St. Michael's Hospital and Ryerson University Canada

Fluid-attenuated inversion recovery (FLAIR) MRI has emerged as an important sequence for the analysis of cerebrovascular (CVD) and Alzheimer's disease (AD). Large-scale, automated cross-sectional and longitudinal cerebral biomarker extraction from FLAIR datasets could progress disease characterization, improve disease monitoring, and help to determine optimal intervention times. Despite this, most automated biomarker extraction algorithms are designed for T1-weighted or multi-modal inputs. In this work, automated tools were used to extract biomarkers from large, FLAIR-only datasets to evaluate the feasibility of this sequence to characterize healthy, AD, and CVD subjects in a similar manner to traditional approaches. Total brain volume (TBV), cerebrospinal fluid (CSF) volume, and white matter lesion (WML) volume was measured for the cross-sectional biomarkers and the corresponding annual rates of change over multiple scans represented the longitudinal biomarkers. Biomarkers were extracted from two dementia cohorts (4356 vol, 162 233 images) and one vascular disease cohort (869 vol, 42 850 images) using deep learning-based segmentation algorithms designed specifically for FLAIR. Biomarkers from all cohorts were summarized using descriptive statistics, correlation analysis, and ANCOVA to assess differences in diagnostic labels while accounting for demographic and acquisition factors. Biomarkers from FLAIR MRI had similar trends with those extracted from traditional modalities in the literature for characterizing healthy, AD, and CVD subjects. This demonstrates that FLAIR MRI can be used for end-to-end analysis of large AD and CVD datasets, which can lower acquisition costs, simplify clinical translation, and reduce measurement error associated with multi-modal approaches. © 2022 The Author(s)

关键词： Alzheimer's disease Cerebral biomarkers Cerebrovascular disease FLAIR MRI

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Revolutionizing sperm selection: A biomimetic approach using vertical temperature differences for enhanced clinical efficiency

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Sensors and Actuators B: Chemical 2025年 442卷

作者： Chung-Hsien Huang Pei-An Chen Wen-Wen Chen Chen-Yen Chung Ching-Wen Chang Ching Hung Chen Farn Lu Wen-Ju Yang Jack Yu Jen Huang Ming-I. Hsu Maw-Sheng Lee Bor-Ran Li Institute of Biomedical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan iPreg Inc New Taipei City Taiwan Taiwan IVF Group Hsinchu Taiwan Ton Yen General Hospital Hsinchu Taiwan Division of Reproductive Endocrinology & Infertility The Department of Obstetrics and Gynecology at Stanford University Stanford CA USA Huayu Fertility Center Taipei Taiwan Lee Women's Hospital Taichung Taiwan Center for Emergent Functional Matter Science National Yang Ming Chiao Tung University Hsinchu Taiwan Medical Device Innovation and Translation R&D Center National Yang Ming Chiao Tung University Hsinchu Taiwan

Biochips have emerged as promising platforms capable of mimicking in vivo environments to purify motile sperm cells and reduce the damage to sperm caused by the currently common clinical centrifugal sperm separation method. Here, we introduce a biomimetic sperm separation method inspired by the temperature gradient variance observed in the female reproductive tract. This method efficiently isolates motile sperm by directing them to swim in a specific direction based on their intrinsic behavior and temperature sensitivity. Clinical trials using human samples demonstrated that the proposed vertical temperature difference device leverages the concepts of swim-up and thermotaxis to enhance both the processed sample volume and the recovery rate, surpassing traditional microfluidic devices that rely on flow fields for sperm separation. The recovered sperm concentration of our device reached two million per milliliter, and the proportion of healthy sperm reached 99 %. It can be directly utilized in clinical settings. This device improves upon current sperm selection methods used in assisted reproduction by minimizing sperm damage.

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Microfluidic high-throughput cell pairing and retrieval for studying breast cancer-MSC engulfment 21

Microfluidic high-throughput cell pairing and retrieval for ...

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21st International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2017

作者： Chen, Yu-Chih Gonzalez, Maria E. Hiziroglu, Ayse Buke Zhao, Xintao Brien, Riley Cheng, Yu-Heng Zhang, Zhixiong Kleer, Celina G. Yoon, Euisik Dept. of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States Comprehensive Cancer Center University of Michigan Medical School Ann ArborMI United States Dept. of Pathology University of Michigan Medical School Ann ArborMI United States Dept. of Biomedical Engineering University of Michigan Ann ArborMI United States

ISBN: (纸本)9780692941836

Metastasis is the major cause of death in breast cancer patients. The interaction with mesenchymal stem/stromal cells promotes breast cancer metastasis. To investigate cellular engulfment in vitro, we have developed a high-throughput cell pairing and retrieval platform, which enables: (1) integration of 3,000 cell-pairing micro-chambers, allowing for contact of paired cancer cells and MSCs in each chamber, (2) automatic image collection and analysis to quantify engulfing rates, and (3) retrieval of target engulfing cells for downstream analysis. © 17CBMS-0001.

关键词： Microfluidics

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Tunneling current-controlled spin states in few-layer van der Waals magnets

arXiv

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arXiv 2024年

作者： Fu, ZhuangEn Samarawickrama, Piumi I. Ackerman, John Zhu, Yanglin Mao, Zhiqiang Watanabe, Kenji Taniguchi, Takashi Wang, Wenyong Dahnovsky, Yuri Wu, Mingzhong Chien, TeYu Tang, Jinke MacDonald, Allan H. Chen, Hua Tian, Jifa Department of Physics and Astronomy University of Wyoming LaramieWY82071 United States Center for Quantum Information Science and Engineering University of Wyoming LaramieWY82071 United States Department of Chemical Biomedical Engineering University of Wyoming LaramieWY82071 United States Department of Physics The Pennsylvania State University University ParkPA16801 United States Research Center for Electronic and Optical Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Department of Physics Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Department of Physics The University of Texas at Austin AustinTX78712 United States Department of Physics School of Advanced Materials Discovery Colorado State University Fort CollinsCO80523 United States

Effective control of magnetic phases in two-dimensional magnets would constitute crucial progress in spintronics, holding great potential for future computing technologies. Here, we report a new approach of leveraging tunneling current as a tool for controlling spin states in CrI3. We reveal that a tunneling current can deterministically switch between spin-parallel and spin-antiparallel states in few-layer CrI3, depending on the polarity and amplitude of the current. We propose a mechanism involving nonequilibrium spin accumulation in the graphene electrodes in contact with the CrI3 layers. We further demonstrate tunneling current-tunable stochastic switching between multiple spin states of the CrI3 tunnel devices, which goes beyond conventional bi-stable stochastic magnetic tunnel junctions and has not been documented in two-dimensional magnets. Our findings not only address the existing knowledge gap concerning the influence of tunneling currents in controlling the magnetism in two-dimensional magnets, but also unlock possibilities for energy-efficient probabilistic and neuromorphic computing. © 2024, CC BY-NC-ND.

关键词： Van der Waals forces

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Evaluation of embedded platforms for lower limb prosthesis with visual sensing capabilities

arXiv

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arXiv 2020年

作者： da Silva, Rafael L. Starliper, Nathan Zhong, Boxuan Huang, He Helen Lobaton, Edgar Department of Electrical and Computer Engineering North Carolina State University RaleighNC27603 United States Joint Department of Biomedical Engineering University of North Carolina North Carolina State University

Lower limb prosthesis can benefit from embedded systems capable of applying computer vision techniques to enhance autonomous control and context awareness for intelligent decision making. In order to fill in the gap of current literature of autonomous systems for prosthetic legs employing computer vision methods, we evaluate the performance capabilities of two off-the-shelf platforms, the Jetson TX2 and Raspberry Pi 3, by assessing their CPU load, memory usage, run time and classification accuracy for different image sizes and widespread computer vision algorithms. We make use of a dataset that we collected for terrain recognition using images from a camera mounted on a leg, which would enable context-awareness for lower limb prosthesis. We show that, given reasonably large images and an appropriate frame selection method, it is possible to identify the terrain that a subject is going to step on, with the possibility of reconstructing the surface and obtaining its inclination. This is part of a proposed system equipped with an embedded camera and inertial measurement unit to recognize different types of terrain and estimate the slope of the surface in front of the subject. Copyright © 2020, The Authors. All rights reserved.

关键词： Landforms

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TextAI 3.0 (Multimodal): multimodal sentiment analysis using attention-enabled ensemble-based deep learning in hyperbolic space

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International Journal of Information Technology (Singapore) 2025年 1-16页

作者： Singh, Jaskaran Sanga, Prabhav Khanna, Narendra N. Laird, John R. Singh, Inder M. Kalra, Mannudeep K. Mantella, Laura E. Johri, Amer M. Faa, Gavino Tiwari, Ekta Singh, Rajesh Abbas, Mohamed Saba, Luca Suri, Jasjit S. Stroke Monitoring and Diagnostic Division AtheroPoint™ Roseville 95661 CA United States Bharati Vidyapeeth’s College of Engineering New Delhi India Department of Cardiology Indraprastha APOLLO Hospitals New Delhi 110001 India Department of Neurology and Stroke Program University of Maryland School of Medicine Baltimore United States Department of Radiology Harvard Medical School Boston 02115 MA United States Department of Biomedical and Molecular Sciences Queen’s University Kingston ON Canada Division of Cardiology Department of Medicine Queen’s University Kingston ON Canada Department of Pathology University of Cagliari Cagliari Italy Department of Computer Science Visvesvaraya National Institute of Technology (VNIT) Nagpur 440010 India Department of Research and Innovation Uttaranchal Institute of Technology Uttaranchal University Dehradun 248007 India Central Labs King Khalid University P.O. Box 960 AlQura’a Abha Saudi Arabia Electrical Engineering Department College of Engineering King Khalid University Abha 61421 Saudi Arabia Department of Neurology University of Cagliari Cagliari Italy Department of ECE Idaho State University Pocatello 83209 ID United States Department of CE Graphic Era Deemed to Be University Dehradun 248002 India University Center for Research and Development Chandigarh University Mohali India Symbiosis Institute of Technology Symbiosis International (Deemed University) Nagpur Campus Pune India Department of Innovation Global Biomedical Technologies Inc. Roseville 95661 CA United States

The rising prevalence of depression presents a significant global health challenge, underscoring the need for effective early detection through sentiment analysis. Traditional multimodal sentiment analysis methods, which rely on Euclidean space for data representation, often fail to capture the complex hierarchical relationships and non-linear structures inherent in multimodal data. To address this limitation, we propose a novel multimodal architecture that operates in hyperbolic space and incorporates attention-based ensemble learning to enhance feature representation and model performance. We developed and evaluated ten AI models—five utilizing Euclidean space and five leveraging hyperbolic space—on the Spoken Language Understanding Evaluation (SLUE) benchmark dataset. The models were assessed using cross-validation techniques to ensure robustness, and statistical analyses were conducted to validate the findings. Our results indicate that hyperbolic-based multimodal models achieve a 2.32% improvement in accuracy compared to their Euclidean counterparts, while the integration of self-attention mechanisms further contributes an average accuracy gain of 0.96%. Additionally, we observed a 3.76% decline in performance when reducing the training-to-test data ratio from 90:10 to 50:50, highlighting the importance of data distribution in model training. These findings confirm that attention-enhanced multimodal models in hyperbolic space offer superior representations for sentiment analysis. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Attention-enabled Deep learning Euclidean space Hyperbolic space Multimodal Sentiment analysis

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Rapid TAURUS for relaxation-based color magnetic particle imaging

arXiv

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arXiv 2021年

作者： Arslan, Tunç Alper Özaslan, A. Kurt, Semih Muslu, Yavuz Saritas, Emine Ulku Department of Electrical and Electronics Engineering Bilkent University Ankara06800 Turkey Bilkent University Ankara06800 Turkey Neuroscience Program Sabuncu Brain Research Center Bilkent University Ankara06800 Turkey Department of Biomedical Engineering University of Wisconsin-Madison MadisonWI United States Department of Radiology University of Wisconsin-Madison MadisonWI United States Department of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Science for Life Laboratory Stockholm Sweden

Magnetic particle imaging (MPI) is a rapidly developing medical imaging modality that exploits the non-linear response of magnetic nanoparticles (MNPs). Color MPI widens the functionality of MPI, empowering it with the capability to distinguish different MNPs and/or MNP environments. The system function approach for color MPI relies on extensive calibrations that capture the differences in the harmonic responses of the MNPs. An alternative calibration-free x-space-based method called TAURUS estimates a map of the relaxation time constant, τ, by recovering the underlying mirror symmetry in the MPI signal. However, TAURUS requires a back and forth scanning of a given region, restricting its usage to slow trajectories with constant or piecewise constant focus fields (FFs). In this work, we propose a novel technique to increase the performance of TAURUS and enable τ map estimation for rapid and multi-dimensional trajectories. The proposed technique is based on correcting the distortions on mirror symmetry induced by time-varying FFs. We demonstrate via simulations and experiments in our in-house MPI scanner that the proposed method successfully estimates high-fidelity τ maps for rapid trajectories that provide orders of magnitude reduction in scanning time, while preserving the calibration-free property of TAURUS. Copyright © 2021, The Authors. All rights reserved.

关键词： Trajectories

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