Subjects -> ENGINEERING (Total: 2688 journals)
    - CHEMICAL ENGINEERING (229 journals)
    - CIVIL ENGINEERING (237 journals)
    - ELECTRICAL ENGINEERING (176 journals)
    - ENGINEERING (1325 journals)
    - ENGINEERING MECHANICS AND MATERIALS (452 journals)
    - HYDRAULIC ENGINEERING (56 journals)
    - INDUSTRIAL ENGINEERING (98 journals)
    - MECHANICAL ENGINEERING (115 journals)

ENGINEERING (1325 journals)            First | 1 2 3 4 5 6 7 | Last

Showing 201 - 400 of 1205 Journals sorted alphabetically
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 8)
Control Engineering Practice     Hybrid Journal   (Followers: 46)
Control Theory and Informatics     Open Access   (Followers: 9)
Corrosion Science     Hybrid Journal   (Followers: 23)
CT&F - Ciencia, Tecnología y Futuro     Open Access  
CTheory     Open Access  
Current Applied Physics     Full-text available via subscription   (Followers: 4)
Current Applied Science and Technology     Open Access  
Current Journal of Applied Science and Technology     Open Access  
Current Research in Nanotechnology     Open Access   (Followers: 23)
Current Science     Open Access   (Followers: 115)
Dams and Reservoirs     Hybrid Journal   (Followers: 3)
Data-Centric Engineering     Open Access  
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 1)
Design Journal : An International Journal for All Aspects of Design     Hybrid Journal   (Followers: 33)
Designed Monomers and Polymers     Open Access   (Followers: 1)
Designs     Open Access  
Designs, Codes and Cryptography     Hybrid Journal   (Followers: 7)
Development Engineering     Open Access   (Followers: 3)
Diálogos Interdisciplinares     Open Access  
Diffusion Foundations     Full-text available via subscription   (Followers: 4)
Digital Signal Processing     Hybrid Journal   (Followers: 34)
Dinamisia : Jurnal Pengabdian Kepada Masyarakat     Open Access  
Discrete Optimization     Full-text available via subscription   (Followers: 7)
Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi     Open Access  
Düzce Üniversitesi Bilim ve Teknoloji Dergisi / Duzce University Journal of Science & Technology     Open Access  
Dyes and Pigments     Hybrid Journal   (Followers: 1)
Dynamical Systems : An International Journal     Hybrid Journal  
E&S Engineering and Science     Open Access  
e-Phaïstos : Revue d’histoire des techniques / Journal of the history of technology     Open Access  
EAU Heritage Journal Science and Technology     Open Access   (Followers: 1)
El-Cezeri Fen ve Mühendislik Dergisi / El-Cezeri Journal of Science and Engineering     Open Access  
Electromagnetics     Hybrid Journal   (Followers: 13)
Electrophoresis     Hybrid Journal   (Followers: 18)
Elkawnie : Journal of Islamic Science and Technology     Open Access  
Emerging Science Journal     Open Access   (Followers: 1)
Emitter : International Journal of Engineering Technology     Open Access  
ENERGETIKA. Proceedings of CIS higher education institutions and power engineering associations     Open Access  
Energies     Open Access   (Followers: 4)
Energy and Power Engineering     Open Access   (Followers: 23)
Energy Conversion and Management     Hybrid Journal   (Followers: 15)
Energy Conversion and Management : X     Open Access   (Followers: 1)
Energy Engineering     Full-text available via subscription   (Followers: 8)
Energy for Sustainable Development     Hybrid Journal   (Followers: 13)
Energy Science & Engineering     Open Access   (Followers: 6)
Energy Science and Technology     Open Access   (Followers: 10)
Energy Sources, Part A: Recovery, Utilization, and Environmental Effects     Hybrid Journal   (Followers: 1)
Energy Sources, Part B: Economics, Planning, and Policy     Hybrid Journal   (Followers: 7)
Energy Systems     Hybrid Journal   (Followers: 11)
EnergyChem     Hybrid Journal   (Followers: 1)
Engenharia de Interesse Social     Open Access  
ENGEVISTA     Open Access  
Engineer : Journal of the Institution of Engineers, Sri Lanka     Open Access  
Engineering     Open Access   (Followers: 1)
Engineering & Technology     Hybrid Journal   (Followers: 22)
Engineering Analysis with Boundary Elements     Hybrid Journal   (Followers: 2)
Engineering Computations     Hybrid Journal   (Followers: 3)
Engineering Economics     Open Access   (Followers: 4)
Engineering Economist, The     Hybrid Journal   (Followers: 4)
Engineering Failure Analysis     Hybrid Journal   (Followers: 68)
Engineering Geology     Hybrid Journal   (Followers: 16)
Engineering Journal of Research and Development     Open Access  
Engineering Management in Production and Services     Open Access  
Engineering Management Research     Open Access   (Followers: 6)
Engineering Optimization     Hybrid Journal   (Followers: 19)
Engineering Reports     Open Access  
Engineering Science and Technology, an International Journal     Open Access   (Followers: 1)
Engineering Sciences     Open Access  
Engineering Studies     Hybrid Journal   (Followers: 1)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Engineering, Technology & Applied Science Research     Open Access   (Followers: 1)
ENP Engineering Science Journal     Open Access  
Entramado     Open Access  
Entre Ciencia e Ingeniería     Open Access  
Entropy     Open Access   (Followers: 5)
Environmental & Engineering Geoscience     Full-text available via subscription   (Followers: 5)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Environmetrics     Hybrid Journal  
Épités - Épitészettudomány     Full-text available via subscription   (Followers: 1)
EPJ Photovoltaics     Open Access   (Followers: 2)
Ergonomics in Design: The Quarterly of Human Factors Applications     Hybrid Journal   (Followers: 21)
ESAIM: Control Optimisation and Calculus of Variations     Open Access   (Followers: 2)
ESAIM: Mathematical Modelling and Numerical Analysis     Open Access   (Followers: 5)
ESAIM: Proceedings     Open Access  
eScience     Open Access   (Followers: 1)
Estuaries and Coasts     Hybrid Journal   (Followers: 22)
EUREKA : Physics and Engineering     Open Access  
Euro-Mediterranean Journal for Environmental Integration     Hybrid Journal  
European Journal of Combinatorics     Full-text available via subscription   (Followers: 3)
European Journal of Engineering Education     Hybrid Journal   (Followers: 9)
European Journal of Lipid Science and Technology     Hybrid Journal   (Followers: 1)
European Journal of Mass Spectrometry     Hybrid Journal   (Followers: 16)
European Physical Journal - Applied Physics     Full-text available via subscription   (Followers: 19)
European Transport Research Review     Open Access   (Followers: 22)
Evolutionary Intelligence     Hybrid Journal   (Followers: 2)
Evolving Systems     Hybrid Journal  
Experimental and Computational Multiphase Flow     Hybrid Journal  
Experimental Techniques     Hybrid Journal   (Followers: 51)
Experiments in Fluids     Hybrid Journal   (Followers: 17)
Farm Engineering and Automation Technology Journal     Open Access  
Fibers and Polymers     Full-text available via subscription   (Followers: 4)
FIGEMPA : Investigación y Desarrollo     Open Access   (Followers: 1)
Filtration & Separation     Full-text available via subscription   (Followers: 4)
Finite Fields and Their Applications     Full-text available via subscription   (Followers: 5)
Fırat University Turkish Journal of Science & Technology     Open Access  
Fire Science Reviews     Open Access   (Followers: 12)
Flexible Services and Manufacturing Journal     Hybrid Journal   (Followers: 2)
Flow, Turbulence and Combustion     Hybrid Journal   (Followers: 30)
Fluid Dynamics     Hybrid Journal   (Followers: 27)
Fluid Phase Equilibria     Hybrid Journal   (Followers: 4)
Focus on Catalysts     Full-text available via subscription  
Focus on Pigments     Full-text available via subscription   (Followers: 3)
Focus on Powder Coatings     Full-text available via subscription   (Followers: 5)
Focus on Surfactants     Full-text available via subscription   (Followers: 2)
Food Engineering Reviews     Hybrid Journal   (Followers: 2)
Food Science and Technology     Open Access   (Followers: 2)
Forces in Mechanics     Open Access   (Followers: 2)
Formación Universitaria     Open Access   (Followers: 4)
FORMakademisk - forskningstidsskrift for design og designdidaktikk     Open Access   (Followers: 2)
Formal Methods in System Design     Hybrid Journal   (Followers: 6)
Forschung     Hybrid Journal   (Followers: 1)
Forschung im Ingenieurwesen     Hybrid Journal  
Foundations and Trends in Systems and Control     Full-text available via subscription   (Followers: 4)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Electronic Design Automation     Full-text available via subscription   (Followers: 1)
Foundations of Science     Hybrid Journal   (Followers: 1)
Frontiers in Aerospace Engineering     Open Access   (Followers: 20)
Frontiers in Energy     Hybrid Journal   (Followers: 4)
Frontiers in Nanotechnology     Open Access   (Followers: 1)
Frontiers of Environmental Science & Engineering     Hybrid Journal   (Followers: 3)
Fuel and Energy Abstracts     Full-text available via subscription   (Followers: 7)
Fuel Cells     Hybrid Journal   (Followers: 8)
Fuel Cells Bulletin     Full-text available via subscription   (Followers: 9)
Fusion Engineering and Design     Hybrid Journal   (Followers: 6)
Fuzzy Information and Engineering     Open Access   (Followers: 2)
Fuzzy Sets and Systems     Hybrid Journal   (Followers: 3)
Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards     Hybrid Journal   (Followers: 8)
Géotechnique     Hybrid Journal   (Followers: 27)
Geothermics     Hybrid Journal   (Followers: 7)
Glass Technology - European Journal of Glass Science and Technology Part A     Full-text available via subscription   (Followers: 1)
Global Journal of Engineering Research     Full-text available via subscription  
Global Transitions Proceedings     Open Access  
GPS Solutions     Hybrid Journal   (Followers: 28)
Graphs and Combinatorics     Hybrid Journal   (Followers: 4)
Grass and Forage Science     Hybrid Journal   (Followers: 4)
Groundwater for Sustainable Development     Full-text available via subscription   (Followers: 5)
Heat Transfer - Asian Research     Hybrid Journal   (Followers: 10)
Heat Transfer Engineering     Hybrid Journal   (Followers: 36)
Heat Treatment and Surface Engineering     Open Access  
High Voltage     Open Access  
Himalayan Journal of Science and Technology     Open Access  
Historical Records of Australian Science     Hybrid Journal   (Followers: 2)
Human Behavior and Emerging Technologies     Hybrid Journal   (Followers: 1)
Human Factors in Ergonomics & Manufacturing     Hybrid Journal   (Followers: 12)
Human-Intelligent Systems Integration     Hybrid Journal  
I+D Revista de Investigaciones     Open Access  
IBM Journal of Research and Development     Hybrid Journal   (Followers: 16)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 112)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 88)
IEEE Communications Magazine     Full-text available via subscription   (Followers: 139)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 60)
IEEE Engineering Management Review     Full-text available via subscription   (Followers: 117)
IEEE Geoscience and Remote Sensing Letters     Hybrid Journal   (Followers: 150)
IEEE Geoscience and Remote Sensing Magazine     Hybrid Journal   (Followers: 6)
IEEE Industry Applications Magazine     Full-text available via subscription   (Followers: 82)
IEEE Instrumentation & Measurement Magazine     Hybrid Journal   (Followers: 148)
IEEE Journal of Biomedical and Health Informatics     Hybrid Journal   (Followers: 14)
IEEE Journal of Oceanic Engineering     Hybrid Journal   (Followers: 11)
IEEE Journal of Selected Topics in Quantum Electronics     Hybrid Journal   (Followers: 7)
IEEE Journal of Selected Topics in Signal Processing     Hybrid Journal   (Followers: 43)
IEEE Journal of Solid-State Circuits     Full-text available via subscription   (Followers: 24)
IEEE Journal on Selected Areas in Communications     Hybrid Journal   (Followers: 39)
IEEE Latin America Transactions     Full-text available via subscription   (Followers: 2)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
IEEE Microwave and Wireless Components Letters     Hybrid Journal   (Followers: 35)
IEEE Microwave Magazine     Full-text available via subscription   (Followers: 63)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 45)
IEEE Open Journal of Engineering in Medicine and Biology     Open Access   (Followers: 1)
IEEE Open Journal of Nanotechnology     Open Access   (Followers: 1)
IEEE Potentials     Full-text available via subscription   (Followers: 42)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 19)
IEEE Signal Processing Letters     Hybrid Journal   (Followers: 60)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 11)
IEEE Spectrum     Full-text available via subscription   (Followers: 219)
IEEE Technology and Society Magazine     Full-text available via subscription   (Followers: 8)
IEEE Transactions on Advanced Packaging     Full-text available via subscription   (Followers: 8)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 79)
IEEE Transactions on Applied Superconductivity     Hybrid Journal   (Followers: 5)
IEEE Transactions on Automation Science and Engineering     Full-text available via subscription   (Followers: 13)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 35)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 11)
IEEE Transactions on Circuits and Systems II: Express Briefs     Hybrid Journal   (Followers: 20)
IEEE Transactions on Components and Packaging Technologies     Full-text available via subscription   (Followers: 17)
IEEE Transactions on Control Systems Technology     Hybrid Journal   (Followers: 111)
IEEE Transactions on Education     Hybrid Journal   (Followers: 11)
IEEE Transactions on Electronics Packaging Manufacturing     Hybrid Journal   (Followers: 21)
IEEE Transactions on Energy Conversion     Hybrid Journal   (Followers: 16)
IEEE Transactions on Engineering Management     Hybrid Journal   (Followers: 74)

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Similar Journals
Journal Cover
IEEE Transactions on Biomedical Engineering
Journal Prestige (SJR): 1.267
Citation Impact (citeScore): 5
Number of Followers: 35  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9294
Published by IEEE Homepage  [228 journals]
  • Frontcover

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      Abstract: Presents the front cover for this issue of the publication.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • IEEE Engineering in Medicine and Biology Society

    • Free pre-print version: Loading...

      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • IEEE Transactions on Biomedical Engineering (T-BME)

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      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • IEEE Transactions on Biomedical Engineering Handling Editors

    • Free pre-print version: Loading...

      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Inter-Phase 4D Cardiac MRI Registration With a Motion Prior Derived From
           CTA

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      Authors: Yudi Sang;Minsong Cao;Michael McNitt-Gray;Yu Gao;Peng Hu;Ran Yan;Yingli Yang;Dan Ruan;
      Pages: 1828 - 1836
      Abstract: Objective: Registration between phases in 4D cardiac MRI is essential for reconstructing high-quality images and appreciating the dynamics. Complex motion and limited image quality make it challenging to design regularization functionals. We propose to introduce a motion representation model (MRM) into a registration network to impose customized, site-specific, and spatially variant prior for cardiac motion. Methods: We propose a novel approach to regularize deep registration with a deformation vextor field (DVF) representation model using computed tomography angiography (CTA). In the form of a convolutional auto-encoder, the MRM was trained to capture the spatially variant pattern of feasible DVF Jacobian. The CTA-derived MRM was then incorporated into an unsupervised network to facilitate MRI registration. In the experiment, 10 CTAs were used to derive the MRM. The method was tested on 10 0.35 T scans in long-axis view with manual segmentation and 15 3 T scans in short-axis view with tagging-based landmarks. Results: Introducing the MRM improved registration accuracy and achieved 2.23, 7.21, and 4.42 mm 80% Hausdorff distance on left ventricle, right ventricle, and pulmonary artery, respectively, and 2.23 mm landmark registration error. The results were comparable to carefully tuned SimpleElastix, but reduced the registration time from 40 s to 0.02 s. The MRM presented good robustness to different DVF sample generation methods. Conclusion: The model enjoys high accuracy as meticulously tuned optimization model and the efficiency of deep networks. Significance: The method enables model to go beyond the quality limitation of MRI. The robustness to training DVF generation scheme makes the method attractive to adapting to the available data and software resources in various clinics.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • A Neuromorphic Model With Delay-Based Reservoir for Continuous Ventricular
           Heartbeat Detection

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      Authors: Xiangpeng Liang;Haobo Li;Aleksandra Vuckovic;John Mercer;Hadi Heidari;
      Pages: 1837 - 1849
      Abstract: There is a growing interest in neuromorphic hardware since it offers a more intuitive way to achieve bio-inspired algorithms. This paper presents a neuromorphic model for intelligently processing continuous electrocardiogram (ECG) signal. This model aims to develop a hardware-based signal processing model and avoid employing digitally intensive operations, such as signal segmentation and feature extraction, which are not desired in an analogue neuromorphic system. We apply delay-based reservoir computing as the information processing core, along with a novel training and labelling method. Different from the conventional ECG classification techniques, this computation model is a end-to-end dynamic system that mimics the real-time signal flow in neuromorphic hardware. The input is the raw ECG stream, while the amplitude of the output represents the risk factor of a ventricular ectopic heartbeat. The intrinsic memristive property of the reservoir empowers the system to retain the historical ECG information for high-dimensional mapping. This model was evaluated with the MIT-BIH database under the inter-patient paradigm and yields 81% sensitivity and 98% accuracy. Under this architecture, the minimum size of memory required in the inference process can be as low as 3.1 MegaByte(MB) because the majority of the computation takes place in the analogue domain. Such computational modelling boosts memory efficiency by simplifying the computing procedure and minimizing the required memory for future wearable devices.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Jet-Induced Tissue Disruption for Blood Release

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      Authors: Jiali Xu;James W. McKeage;Bryan P. Ruddy;Poul M. F. Nielsen;Andrew J. Taberner;
      Pages: 1850 - 1859
      Abstract: Objective: Needle-free jet injection is a drug delivery technique that uses the momentum of the fluid drug to break through the skin. This technique has recently also been applied to blood release, aiming to collect samples from capillaries in the skin without needing a lancet prick. This work provides new information about the wound geometry and tissue disruption caused by shallow jet injection with circular-shaped and slot-shaped jets. Methods: We use histological analysis to compare the disruption of tissue, including blood vessels, caused by lancet-pricking and jet injection with a circular-shaped jet and a lancet-inspired slot-shaped jet. Results: Intradermal injection into porcine skin using a slot-shaped jet disrupted more vascular endothelium in the tissue than a circular-shaped jet and did so at a smaller penetration depth with smaller wound volume. Our results suggest that shallow jet injections may have the potential to release more capillary blood than a lancet prick. Conclusion: These findings demonstrate that a reversible jet injector might be used in diabetes management as a device to release and collect blood samples, in addition to being used to deliver insulin. Significance: Tissue disruption is crucial to consider when using jet injection to deliver drugs and release capillary blood.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Non-Invasive Measurement of the Internal Pressure of a Pressurized
           Biological Compartment Using Lamb Waves

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      Authors: David P. Rosen;Nicholas B. Larson;Azra Alizad;Mostafa Fatemi;
      Pages: 1860 - 1869
      Abstract: In this study, we propose a mechanical analysis for estimating the internal pressure of a finitely deformed spherical compartment from Lamb wave measurements. The proposed analysis produces a dispersion relation associating Lamb wave speed with pressure using limited material parameters (only a strain stiffening term). The analysis was validated on ultrasound bladder vibrometry (UBV) experiments collected from 9 ex vivo porcine bladders before and after formalin cross-linking. Estimated pressures were compared with pressures measured directly by a pressure transducer. The proposed analysis proved broadly effective at estimating pressure from UBV based Lamb wave without calibration as demonstrated by the observed concordance between estimated and measured pressures (Lin’s CCC = 0.82 (0.66-0.91). Theoretical limitations and potential refinements to improve the accuracy and generality of the approach are discussed.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • A Novel Capsule-Delivered Enteric Drug-Injection Device for Delivery of
           Systemic Biologics: A Pilot Study in a Porcine Model

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      Authors: Sunandita Sarker;Ben Wankum;Trevor Perey;Musharrat Mustaree Mau;Jeff Shimizu;Ryan Jones;Benjamin Terry;
      Pages: 1870 - 1879
      Abstract: Innovative swallowable capsule technologies such as drug-loaded, dissolvable microneedles, mucoadhesive patches, and various microdevices present unique drug-carrying capabilities to overcome challenges regarding oral delivery of biologics. Here, we report a swallowable capsule for intestinal drug delivery (SCIDD) with the potential of directly injecting biological therapeutics into the insensate small intestine wall. The design, optimization, and validation of the SCIDD's primary subsystems were performed both ex-vivo and in-vivo. The assembled capsule was further tested in vivo to validate the actuation sequence and showed a 70% (n = 17) success rate in an animal model. Additionally, a drug delivery study indicated systemic uptake of adalimumab via SCIDD compared with luminal delivery in the small intestine. The pilot study presented here establishes that the novel platform could be used to orally deliver systemic biologics.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Simultaneous Localized Brain Mild Hyperthermia and Blood-Brain Barrier
           Opening via Feedback-Controlled Transcranial MR-Guided Focused Ultrasound
           and Microbubbles

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      Authors: Bingbing Cheng;Chenchen Bing;Tak Ho Chu;Saud Alzahrani;Samuel Pichardo;G Bruce Pike;
      Pages: 1880 - 1888
      Abstract: Objective: Non-invasive methods to enhance drug delivery and efficacy in the brain have been pursued for decades. Focused ultrasound hyperthermia (HT) combined with thermosensitive therapeutics have been demonstrated promising in enhancing local drug delivery to solid tumors. We hypothesized that the presence of microbubbles (MBs) combined with transcranial MR-guided focused ultrasound (MRgFUS) could be used to reduce the ultrasound power required for HT while simultaneously increasing drug delivery by locally opening the blood-brain barrier (BBB). Methods: Transcranial HT (42 °C, 10 min) was performed in wild-type mice using a small animal MRgFUS system incorporated into a 9.4T Bruker MR scanner, with infusions of saline or Definity MBs with doses of 20 or 100 µl/kg/min (denoted as MB-20 and MB-100). MR thermometry data was continuously acquired as feedback for the ultrasound controller during the procedure. Results: Spatiotemporally precise transcranial HT was achieved in both saline and MB groups. A significant ultrasound power reduction (−45.7%, p = 0.006) was observed in the MB-20 group compared to saline. Localized BBB opening was achieved in MB groups confirmed by CE-T1w MR images. There were no structural abnormalities, edema, hemorrhage, or acutemicroglial activation in all groups, confirmed by T2w MR imaging and histology. Conclusion: Our investigations showed that it is feasible and safe to achieve spatiotemporally precise brain HT at significantly reduced power and simultaneous localized BBB opening via transcranial MRgFUS and MBs. Significance: This study provides a new synergistic brain drug delivery method with clinical translation potential.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Near-Infrared Window II Fluorescence Image-Guided Surgery of High-Grade
           Gliomas Prolongs the Progression-Free Survival of Patients

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      Authors: Xiaojing Shi;Zhe Zhang;Zeyu Zhang;Caiguang Cao;Zhen Cheng;Zhenhua Hu;Jie Tian;Nan Ji;
      Pages: 1889 - 1900
      Abstract: Objective: This translational study aims to investigate the clinical benefits of indocyanine green (ICG) based near-infrared window II (NIR-II) fluorescence image-guided surgery (FGS) on high-grade glioma (HGG) patients. Methods: Patients were randomly assigned to receive FGS or traditional white light image-guided surgery (WLS). The detection rate of NIR-II fluorescence was observed. Complete resection rate, progression-free survival (PFS), overall survival (OS), and neurological status were compared. Tissue samples were obtained from the FGS group, with the diagnosis based on the surgeons and the fluorescence recorded for comparison of diagnostic capability. Patients with WHO grade III gliomas or glioblastomas (GBM) were analyzed separately. Results: 15 GBM and 4 WHO grade III glioma patients in the FGS group and 18 GBM and 4 WHO grade III glioma patients in the WLS group were enrolled. The detection rate of NIR-II fluorescence was 100% for GBM. The complete resection rate was significantly increased by the FGS for GBM (FGS, 100% [95% CI 73.41-100] vs. WLS, 50% [95% CI 29.03-70.97], P = 0.0036). The PFS and OS of the FGS group were also significantly prolonged (Median PFS: FGS, 9.0 months vs. WLS, 7.0 months, P < 0.0001; Median OS: FGS, 19.0 months vs. WLS, 15.5 months, P = 0.0002). No recurrence was observed in WHO grade III glioma patients. Conclusions: NIR-II FGS achieves a much better complete resection rate of GBM than conventional WLS, leading to greatly improved survival of GBM patients. Significance: NIR-II FGS is a highly promising technique worthy of exploring more clinical applications.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Performance Evaluation of Magnetic Resonance Coupling Method for
           Intra-Body Network (IBNet)

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      Authors: Sayemul Islam;Rajpreet Kaur Gulati;Michael Domic;Amitangshu Pal;Krishna Kant;Albert Kim;
      Pages: 1901 - 1908
      Abstract: Effective management of emerging medical devices can lead to new insights in healthcare. Thus, human body communication (HBC) is becoming increasingly important. In this paper, we present magnetic resonance (MR) coupling as a promising method for the intra-body network (IBNet). The study reveals that MR coupling can effectively send or receive signals in biological tissue, with a maximum path loss of $PL$ $le$ 33 dB (i.e. at 13.56 MHz), which is lower than other methods (e.g., galvanic, capacitive, or RF) for the same distance (d = 100 cm). The angular orientation of the transmitter and receiver coils at short and long distances also show a minor variation of the path loss (0.19 $leq Delta PLle$ 0.62 dB), but more dependency on the distance (0.0547 dB/cm). Additionally, different postures during the MR coupling essentially does not affect path loss ($Delta PLle$ $pm$ 0.21 dB). In the multi-nodal transmission scenario, the MR coupling demonstrates that two nodes can simultaneously receive signals with -16.77 dBm loss at 60 cm and 100 cm distances, respectively. Such multi-node MR transmission can be utilized for communication, sensing, and powering wearable and implantable devices.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Towards Estimation of Tidal Volume and Respiratory Timings via
           Wearable-Patch-Based Impedance Pneumography in Ambulatory Settings

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      Authors: John A. Berkebile;Samer A. Mabrouk;Venu G. Ganti;Adith V. Srivatsa;Jesus Antonio Sanchez-Perez;Omer T. Inan;
      Pages: 1909 - 1919
      Abstract: Objective: Evaluating convenient, wearable multi-frequency impedance pneumography (IP)-based respiratory monitoring in ambulatory persons with novel electrode positioning. Methods: A wearable multi-frequency IP system was utilized to estimate tidal volume (TV) and respiratory timings in 14 healthy subjects. A 5.1 cm × 5.1 cm tetrapolar electrode array, affixed to the sternum, and a conventional thoracic electrode configuration were employed to measure the respective IP signals, patch and thoracic IP. Data collected during static postures—sitting and supine—and activities—walking and stair-stepping—were evaluated against a simultaneously-obtained spirometer (SP) volume signal. Results: Across all measurements, estimated TV obtained from the patch and thoracic IP maintained a Pearson correlation coefficient (r) of 0.93 $ pm $ 0.05 and 0.95 $ pm $ 0.05 to the ground truth TV, respectively, with an associated root-mean-square error (RMSE) of 0.177 L and 0.129 L, respectively. Average respiration rates (RRs) were extracted from 30-second segments with mean-absolute-percentage errors (MAPEs) of 0.93% and 0.74% for patch and thoracic IP, respectively. Likewise, average inspiratory and expiratory timings were identified with MAPEs less than 6% and 4.5% for patch and thoracic IP, respectively. Conclusion: We demonstrated that patch IP performs comparably to traditional, cumbersome IP configurations. We also present for the first time, to the best of our knowledge, that IP can robustly estimate breath-by-breath TV and respiratory timings during ambulation. Significance: This work represents a notable step towards pervasive wearable ambulatory respiratory monitoring via the fusion of a compact chest-worn form factor and multi-frequency IP that can be readily adapted for holistic cardiopulmonary monitoring.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • A Human-Centered Machine-Learning Approach for Muscle-Tendon Junction
           Tracking in Ultrasound Images

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      Authors: Christoph Leitner;Robert Jarolim;Bernhard Englmair;Annika Kruse;Karen Andrea Lara Hernandez;Andreas Konrad;Eric Yung-Sheng Su;Jörg Schröttner;Luke A. Kelly;Glen A. Lichtwark;Markus Tilp;Christian Baumgartner;
      Pages: 1920 - 1930
      Abstract: Biomechanical and clinical gait research observes muscles and tendons in limbs to study their functions and behaviour. Therefore, movements of distinct anatomical landmarks, such as muscle-tendon junctions, are frequently measured. We propose a reliable and time efficient machine-learning approach to track these junctions in ultrasound videos and support clinical biomechanists in gait analysis. In order to facilitate this process, a method based on deep-learning was introduced. We gathered an extensive dataset, covering 3 functional movements, 2 muscles, collected on 123 healthy and 38 impaired subjects with 3 different ultrasound systems, and providing a total of 66864 annotated ultrasound images in our network training. Furthermore, we used data collected across independent laboratories and curated by researchers with varying levels of experience. For the evaluation of our method a diverse test-set was selected that is independently verified by four specialists. We show that our model achieves similar performance scores to the four human specialists in identifying the muscle-tendon junction position. Our method provides time-efficient tracking of muscle-tendon junctions, with prediction times of up to 0.078 seconds per frame (approx. 100 times faster than manual labeling). All our codes, trained models and test-set were made publicly available and our model is provided as a free-to-use online service on https://deepmtj.org/.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Phase Preservation Neural Network for Electroencephalography
           Classification in Rapid Serial Visual Presentation Task

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      Authors: Fu Li;Chong Wang;Yang Li;Hao Wu;Boxun Fu;Youshuo Ji;Yi Niu;Guangming Shi;
      Pages: 1931 - 1942
      Abstract: Neuroscience studies have demonstrated the phase-locked characteristics of some early event-related potential (ERP) components evoked by stimuli. In this study, we propose a phase preservation neural network (PPNN) to learn phase information to improve the Electroencephalography (EEG) classification in a rapid serial visual presentation (RSVP) task. The PPNN consists of three major modules that can produce spatial and temporal representations with the high discriminative ability of the EEG features for classification. We first adopt a stack of dilated temporal convolution layers to extract temporal dynamics while avoiding the loss of phase information. Considering the intrinsic channel dependence of the EEG data, a spatial convolution layer is then applied to obtain the spatial-temporal representation of the input EEG signal. Finally, a fully connected layer is adopted to extract higher-level features for the final classification. The experiments are conducted on two public and one collected EEG datasets from the RSVP task, in which we evaluated the performance and explored the capability of phase preservation of our PPNN model and visualized the extracted features. The experimental results indicate the superiority of the proposed PPNN when compared with previous methods, suggesting the PPNN is a robust model for EEG classification in RSVP task.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Diffuse Correlation Spectroscopy Beyond the Water Peak Enabled by
           Cross-Correlation of the Signals From InGaAs/InP Single Photon Detectors

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      Authors: Mitchell B. Robinson;Marco Renna;Nisan N. Ozana;Adriano Peruch;Sava Sakadžić;Megan L. Blackwell;Jonathan M. Richardson;Brian F. Aull;Stefan A. Carp;Maria Angela Franceschini;
      Pages: 1943 - 1953
      Abstract: Objective: Diffuse correlation spectroscopy (DCS) is an optical technique that allows for the non-invasive measurement of blood flow. Recent work has shown that utilizing longer wavelengths beyond the traditional NIR range provides a significant improvement to signal-to-noise ratio (SNR). However, current detectors both sensitive to longer wavelengths and suitable for clinical applications (InGaAs/InP SPADs) suffer from suboptimal afterpulsing and dark noise characteristics. To overcome these barriers, we introduce a cross correlation method to more accurately recover blood flow information using InGaAs/InP SPADs. Methods: Two InGaAs/InP SPAD detectors were used for during in vitro and in vivo DCS measurements. Cross correlation of the photon streams from each detector was performed to calculate the correlation function. Detector operating parameters were varied to determine parameters which maximized measurement SNR.State-space modeling was performed to determine the detector characteristics at each operating point. Results: Evaluation of detector characteristics was performed across the range of operating conditions. Modeling the effects of the detector noise on the correlation function provided a method to correct the distortion of the correlation curve, yielding accurate recovery of flow information as confirmed by a reference detector. Conclusion: Through a combination of cross-correlation of the signals from two detectors, model-based characterization of detector response, and optimization of detector operating parameters, the method allows for the accurate estimation of the true blood flow index. Significance: This work presents a method by which DCS can be performed at longer NIR wavelengths with existing detector technology, taking advantage of the increased SNR.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • An Approximate Electromagnetic Model for Optimizing Wireless Charging of
           Biomedical Implants

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      Authors: Kyle van Oosterhout;Maarten Paulides;Hans Pflug;Steven Beumer;Rob Mestrom;
      Pages: 1954 - 1963
      Abstract: Objective: Computational modeling is increasingly used to design charging systems for implanted medical devices. The design of these systems must often satisfy conflicting requirements, such as charging speed, specific absorption rate (SAR) and coil size. Fast electromagnetic solvers are pivotal for enabling multi-criteria optimization. In this paper, we present an analytical model based on the quasi-static approximation as a fast, yet sufficiently accurate tool for optimizing inductive charging systems. Methods: The approximate model was benchmarked against full-wave simulations to validate accuracy and improvement in computation time. The coupling factor of two test coils was measured for lateral and axial displacements and the SAR was measured experimentally in a PAA phantom. Results: The approximate model takes only 11 seconds to compute a single iteration, while the full-wave model takes 5 hours to compute the same case. The maximum difference with full-wave simulations was less than 24% and the mean difference less than 2%. Adding a novel figure of merit into the multi-criterion optimization resulted in a 16% higher charging speed. The measured results of the SAR and coupling factor are within a 5 mm coil offset margin. Conclusion: The proposed approximate model succeeds as a rapid prototyping tool, enabling fast and sufficiently accurate optimization for wireless charging systems. Significance: The approximate model is the first of its kind to compute both the coupling factor and the SAR near conducting structures fast enough to enable optimization of charging speed.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Multi-Channel Trans-Impedance Leadforming for Cardiopulmonary Monitoring:
           Algorithm Development and Feasibility Assessment Using In Vivo Animal Data
           

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      Authors: Kyounghun Lee;Geuk Young Jang;Yongmin Kim;Eung Je Woo;
      Pages: 1964 - 1974
      Abstract: Objective: The objectives of this study were to develop a multi-channel trans-impedance leadforming method for beat-to-beat stroke volume (SV) and breath-by-breath tidal volume (TV) measurements and assess its feasibility on an existing in vivo animal dataset. Methods: A deterministic leadforming algorithm was developed to extract a cardiac volume signal (CVS) and a respiratory volume signal (RVS) from 208-channel trans-impedance data acquired every 20 ms by an electrical impedance tomography (EIT) device. SVEIT and TVEIT values were computed as a valley-to-peak value in the CVS and RVS, respectively. The method was applied to the existing dataset from five mechanically-ventilated pigs undergoing ten mini-fluid challenges. An invasive hemodynamic monitor was used in the arterial pressure-based cardiac output (APCO) mode to simultaneously measure SVAPCO values while a mechanical ventilator provided TVVent values. Results: The leadforming method could reliably extract the CVS and RVS from the 208-channel trans-impedance data measured with the EIT device, from which SVEIT and TVEIT were computed. The SVEIT and TVEIT values were comparable to those from the invasive hemodynamic monitor and mechanical ventilator. Using the data from 5 pigs and a simple calibration method to remove bias, the error in SVEIT and TVEIT was 9.5% and 5.4%, respectively. Conclusion: We developed a new leadforming method for the EIT device to robustly extract both SV and TV values in a deterministic fashion. Future animal and clinical studies are needed to validate this leadforming method in various subject populations. Significance: The leadforming method could be an integral component for a new cardiopulmonary monitor in the future to simultaneous-y measure SV and TV noninvasively, which would be beneficial to patients.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Assessing the Feasibility of Dynamic 31P Spectroscopy for Metabolic
           Studies With a 1.0T Extremity Scanner

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      Authors: Travis Carrell;Minyu Gu;John C. Bosshard;Chenhao Sun;Mary P. McDougall;Steven M. Wright;
      Pages: 1975 - 1982
      Abstract: Objective: The feasibility of conducting in vivo non-localized 31P Magnetic Resonance Spectroscopy (MRS) with a 1.0T extremity scanner and the potential to increase accessibility of this important diagnostic tool for low cost applications is revisited. Methods: This work presents a custom transmit-only quadrature birdcage, four-element receive coil array, and spectrometer interfaced to a commercial ONI 1.0T magnet for enabling multi-channel, non-1H frequency capabilities. A custom, magnetic resonance compatible plantar flexion-extension exercise device was also developed to enable exercise protocols. The coils were assessed with bench measurements and 31P phantom studies before an in vivo demonstration. Results: In pulse and acquire spectroscopy of a phantom, the array was found to improve the signal-to-noise ratio (SNR) by a factor of 1.31 and reduce the linewidth by 13.9% when compared to a large loop coil of the same overall size. In vivo testing results show that two averages and a four second repetition time for a temporal resolution of eight seconds was sufficient to obtain phosphocreatine recovery values and baseline pH levels aligned with expected literature values. Conclusion: Initial in vivo human skeletal muscle 31P MRS allowed successful monitoring of metabolic changes during an 18-minute exercise protocol. Significance: Adding an array coil and multinuclear capability to a commercial low-cost 1.0T extremity scanner enabled the observation of characteristic 31P metabolic information, such as the phosphocreatinerecovery rate and underlying baseline pH.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • A Bimodal Deep Learning Architecture for EEG-fNIRS Decoding of Overt and
           Imagined Speech

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      Authors: Ciaran Cooney;Raffaella Folli;Damien Coyle;
      Pages: 1983 - 1994
      Abstract: Objective: Brain-computer interfaces (BCI) studies are increasingly leveraging different attributes of multiple signal modalities simultaneously. Bimodal data acquisition protocols combining the temporal resolution of electroencephalography (EEG) with the spatial resolution of functional near-infrared spectroscopy (fNIRS) require novel approaches to decoding. Methods: We present an EEG-fNIRS Hybrid BCI that employs a new bimodal deep neural network architecture consisting of two convolutional sub-networks (subnets) to decode overt and imagined speech. Features from each subnet are fused before further feature extraction and classification. Nineteen participants performed overt and imagined speech in a novel cue-based paradigm enabling investigation of stimulus and linguistic effects on decoding. Results: Using the hybrid approach, classification accuracies (46.31% and 34.29% for overt and imagined speech, respectively (chance: 25%)) indicated a significant improvement on EEG used independently for imagined speech (p = 0.020) while tending towards significance for overt speech (p = 0.098). In comparison with fNIRS, significant improvements for both speech-types were achieved with bimodal decoding (p
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Inverse Reinforcement Learning Intra-Operative Path Planning for Steerable
           Needle

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      Authors: Alice Segato;Marco Di Marzo;Sara Zucchelli;Stefano Galvan;Riccardo Secoli;Elena De Momi;
      Pages: 1995 - 2005
      Abstract: Objective: This paper presentsa safe and effective keyhole neurosurgery intra-operative planning framework for flexible neurosurgical robots. The framework is intended to support neurosurgeons during the intra-operative procedure to react to a dynamic environment. Methods: The proposed system integrates inverse reinforcement learning path planning algorithm combined with 1) a pre-operative path planning framework for fast and intuitive user interaction, 2) a realistic, time-bounded simulator based on Position-based Dynamics (PBD) simulation that mocks brain deformations due to catheter insertion and 3) a simulated robotic system. Results: Simulation results performed on a human brain dataset show that the inverse reinforcement learning intra-operative planning method can guide a steerable needle with bounded curvature to a predefined target pose with an average targeting error of 1.34 $pm$ 0.52 (25$^{th}$ = 1.02, 75$^{th}$ = 1.36) mm in position and 3.16 $pm$ 1.06 (25$^{th}$ = 2, 75$^{th}$ = 4.94) degrees in orientation under a deformable simulated environment, with a re-planning time of 0.02 sec and a success rate of 100%. Conclusion: With this work, we demonstrate that the presented intra-operative steerable needle path planner is able to avoid anatomical obstacles while optimising surgical criteria. Significance: The results demonstrate that the proposed method is fast and can securely steer flexible needles with high accuracy and robustness.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Synergy Analysis of Back Muscle Activities in Patients With Adolescent
           Idiopathic Scoliosis Based on High-Density Electromyogram

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      Authors: Wei Wang;Naifu Jiang;Lijun Teng;Minghong Sui;ChunZhen Li;Lin Wang;Guanglin Li;
      Pages: 2006 - 2017
      Abstract: Objective: Adolescent idiopathic scoliosis (AIS) is a common structural spinal deformity and is typically associated with altered muscle properties. However, it is still unclear how muscle activities and the underlying neuromuscular control are changed in the entire scoliotic zone, restricting the corresponding pathology investigation and treatment enhancements. Methods: High-density electromyogram (HD-EMG) was utilized to explore the neuromuscular synergy of back muscle activities. For each of ten AIS patients and ten healthy subjects for comparison, an HD-EMG array was placed on their back from T8 to L4 to record EMG signals when performing five spinal motions (flexion/extension, lateral bending, axial rotation, siting, and standing). From the HD-EMG recordings, muscle synergies were extracted using the non-negative matrix factorization method and the topographical maps of EMG root-mean-square were constructed. Results: For both the AIS and healthy subjects, the experimental results indicated that two muscle synergy groups could explain over 90% of recorded muscle activities for all five motions. During flexion/extension, the patients presented statistically significant higher activations on the convex side in the entire root-mean-square maps and synergy vector maps (p < 0.05). During lateral bending and axial rotation, the patients exhibited less activated muscles on the dominant actuating side relative to the contralateral side and their synergy vector maps showed a less homogenous and more diffuse distribution of muscle contraction with statistically different centers of gravity. Conclusion: The findings suggest a scoliotic spine might adopt an altered modular muscular coordination strategy to actuate different dominant muscles as adapted compensations for the deformation.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Online Adaptation Boosts SSVEP-Based BCI Performance

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      Authors: Chi Man Wong;Ze Wang;Masaki Nakanishi;Boyu Wang;Agostinho Rosa;C. L. Philip Chen;Tzyy-Ping Jung;Feng Wan;
      Pages: 2018 - 2028
      Abstract: Objective: A user-friendly steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) prefers no calibration for its target recognition algorithm, however, the existing calibration-free schemes perform still far behind their calibration-based counterparts. To tackle this issue, learning online from the subject’s unlabeled data is investigated as a potential approach to boost the performance of the calibration-free SSVEP-based BCIs. Methods: An online adaptation scheme is developed to tune the spatial filters using the online unlabeled data from previous trials, and then developing the online adaptive canonical correlation analysis (OACCA) method. Results: A simulation study on two public SSVEP datasets (Dataset I and II) with a total of 105 subjects demonstrated that the proposed online adaptation scheme can boost the CCA’s averaged information transfer rate (ITR) from 94.60 to 158.87 bits/min in Dataset I and from 85.80 to 123.91 bits/min in Dataset II. Furthermore, in our online experiment it boosted the CCA’s ITR from 55.81 bits/min to 95.73 bits/min. More importantly, this online adaptation scheme can be easily combined with any spatial filtering-based algorithms to achieve online learning. Conclusion: By online adaptation, the proposed OACCA performed much better than the calibration-free CCA, and comparable to the calibration-based algorithms. Significance: This work provides a general way for the SSVEP-based BCIs to learn online from unlabeled data and thus avoid calibration.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Influence of Magnetic Scaffold Loading Patterns on Their Hyperthermic
           Potential Against Bone Tumors

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      Authors: Matteo B. Lodi;Nicola Curreli;Sonia Zappia;Luca Pilia;Maria Francesca Casula;Sergio Fiorito;Ilaria Catapano;Francesco Desogus;Teresa Pellegrino;Ilka Kriegel;Lorenzo Crocco;Giuseppe Mazzarella;Alessandro Fanti;
      Pages: 2029 - 2040
      Abstract: Magnetic scaffolds have been investigated as promising tools for the interstitial hyperthermia treatment of bone cancers, to control local recurrence by enhancing radio- and chemotherapy effectiveness. The potential of magnetic scaffolds motivates the development of production strategies enabling tunability of the resulting magnetic properties. Within this framework, deposition and drop-casting of magnetic nanoparticles on suitable scaffolds offer advantages such as ease of production and high loading, although these approaches are often associated with a non-uniform final spatial distribution of nanoparticles in the biomaterial. The implications and the influences of nanoparticle distribution on the final therapeutic application have not yet been investigated thoroughly. In this work, poly-caprolactone scaffolds are magnetized by loading them with synthetic magnetic nanoparticles through a drop-casting deposition and tuned to obtain different distributions of magnetic nanoparticles in the biomaterial. The physicochemical properties of the magnetic scaffolds are analyzed. The microstructure and the morphological alterations due to the reworked drop-casting process are evaluated and correlated to static magnetic measurements. THz tomography is used as an innovative investigation technique to derive the spatial distribution of nanoparticles. Finally, multiphysics simulations are used to investigate the influence on the loading patterns on the interstitial bone tumor hyperthermia treatment.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Reducing Line-of-Block Artifacts in Cardiac Activation Maps Estimated
           Using ECG Imaging: A Comparison of Source Models and Estimation Methods

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      Authors: Steffen Schuler;Matthias Schaufelberger;Laura R. Bear;Jake A. Bergquist;Matthijs J. M. Cluitmans;Jaume Coll-Font;Önder N. Onak;Brian Zenger;Axel Loewe;Rob S. MacLeod;Dana H. Brooks;Olaf Dössel;
      Pages: 2041 - 2052
      Abstract: Objective: To investigatecardiac activation maps estimated using electrocardiographic imaging and to find methods reducing line-of-block (LoB) artifacts, while preserving real LoBs. Methods: Body surface potentials were computed for 137 simulated ventricular excitations. Subsequently, the inverse problem was solved to obtain extracellular potentials (EP) and transmembrane voltages (TMV). From these, activation times (AT) were estimated using four methods and compared to the ground truth. This process was evaluated with two cardiac mesh resolutions. Factors contributing to LoB artifacts were identified by analyzing the impact of spatial and temporal smoothing on the morphology of source signals. Results: AT estimation using a spatiotemporal derivative performed better than using a temporal derivative. Compared to deflection-based AT estimation, correlation-based methods were less prone to LoB artifacts but performed worse in identifying real LoBs. Temporal smoothing could eliminate artifacts for TMVs but not for EPs, which could be linked to their temporal morphology. TMVs led to more accurate ATs on the septum than EPs. Mesh resolution had anegligible effect on inverse reconstructions, but small distances were important for cross-correlation-based estimation of AT delays. Conclusion: LoB artifacts are mainly caused by the inherent spatial smoothing effect of the inverse reconstruction. Among the configurations evaluated, only deflection-based AT estimation in combination with TMVs and strong temporal smoothing can prevent LoB artifacts, while preserving real LoBs. Significance: Regions of slow conduction are of considerable clinical interest and LoB artifacts observed in non-invasive ATs can lead to misinterpretations. We addressed this problem by identifying factors causing such artifacts.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Noninvasive Estimation of Glycated Hemoglobin In-Vivo Based on Photon
           Diffusion Theory and Genetic Symbolic Regression Models

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      Authors: Shifat Hossain;Ki-Doo Kim;
      Pages: 2053 - 2064
      Abstract: The diagnosis and management of diabetes require frequent monitoring of blood sugar levels. Prolonged exposure of most of the monosaccharides in the bloodstream results in the glycation of hemoglobin. This glycated hemoglobin (HbA1c) based test plays an important role to avoid diabetic complications. However, noninvasive estimation of HbA1c is a very new, promising, and challenging topic in modern bioengineering scopes. The purpose of this study is to develop and verify mathematical models in order to quantify the glycated hemoglobin in-vivo percentage non-invasively. This research utilized photon diffusion theory to develop the finger models and genetic symbolic regression methods to solve the models to estimate the level of glycated hemoglobin in the blood. The validation of these models with human participants indicated a high degree of correlation (0.887 and 0.907 Pearson's r value), and high precision (2.56% and 2.96% coefficient of variation (%CV)) for transmission and reflection type noninvasive digital volume pulse-based signals. This research will be a breakthrough for the application of noninvasive HbA1c estimation.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Categorizing the Role of Respiration in Cardiovascular and Cerebrovascular
           Variability Interactions

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      Authors: Alberto Porta;Francesca Gelpi;Vlasta Bari;Beatrice Cairo;Beatrice De Maria;Davide Tonon;Gianluca Rossato;Marco Ranucci;Luca Faes;
      Pages: 2065 - 2076
      Abstract: Objective: Respiration disturbs cardiovascular and cerebrovascular controls but its role is not fully elucidated. Methods: Respiration can be classified as a confounder if its observation reduces the strength of the causal relationship from source to target. Respiration is a suppressor if the opposite situation holds. We prove that a confounding/suppression (C/S) test can be accomplished by evaluating the sign of net redundancy/synergy balance in the predictability framework based on multivariate autoregressive modelling. In addition, we suggest that, under the hypothesis of Gaussian processes, the C/S test can be given in the transfer entropy decomposition framework as well. Experimental protocols: We applied the C/S test to variability series of respiratory movements, heart period, systolic arterial pressure, mean arterial pressure, and mean cerebral blood flow recorded in 17 pathological individuals (age: 64±8 yrs; 17 males) before and after induction of propofol-based general anesthesia prior to coronary artery bypass grafting, and in 13 healthy subjects (age: 27±8 yrs; 5 males) at rest in supine position and during head-up tilt with a table inclination of 60°. Results: Respiration behaved systematically as a confounder for cardiovascular and cerebrovascular controls. In addition, its role was affected by propofol-based general anesthesia but not by a postural stimulus of limited intensity. Conclusion: The C/S test can be fruitfully exploited to categorize the role of respiration over causal variability interactions. Significance: The application of the C/S test could favor the comprehension of the role of respiration in cardiovascular and cerebrovasc-lar regulations.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • High-Resolution Spatiotemporal Quantification of Intestinal Motility With
           Free-Form Deformation

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      Authors: Sachira Kuruppu;Leo K. Cheng;Poul M.F. Nielsen;Thiranja P. Babarenda Gamage;Recep Avci;Timothy R. Angeli;Niranchan Paskaranandavadivel;
      Pages: 2077 - 2086
      Abstract: Objective: To develop a method to quantify strain fields from in vivo intestinal motility recordings that mitigate accumulation of tracking error. Methods: The deforming geometry of the intestine in video sequences was modeled by a biquadratic B-spline mesh. Green-Lagrange strain fields were computed to quantify the surface deformations. A nonlinear optimization scheme was applied to mitigate the accumulation of tracking error associated with image registration. Results: The optimization scheme maintained the RMS strain error under 1% and reduced the rate of strain error by 97% during synthetic tests. The algorithm was applied to map 64 segmental, 12 longitudinal, and 23 propagating circular contractions in the jejunum. Coordinated activity of the two muscle layers could be identified and the strain fields were able to map and quantify the anisotropic contractions of the intestine. Frequency and velocity were also quantified, from which two types of propagating circular contractions were identified: (i) $-text{0.36}pm text{0.04}$ strain contractions that originated spontaneously and propagated at $text{3} pm text{1}$ mm/s in two pigs, and (ii) cyclic propagating contractions of $-text{0.17} pm text{0.02}$ strain occurred at $text{11.0} pm text{0.6}$ cpm and propagated at $text{16} pm text{4}$ mm/s in a rabbit. Conclusion: The algorithm simultaneously mapped the circular, longitudinal activity of the intestine with high spatial resolution and quantified anisotropic contractions and -elaxations. Significance: The proposed algorithm can now be used to define the interactions of muscle layers during motility patterns. It can be integrated with high-resolution bioelectrical recordings to investigate the regulatory mechanisms of motility.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Assessment of Calibration Models for Cuff-Less Blood Pressure Measurement
           After One Year of Aging

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      Authors: Mohammad Yavarimanesh;Robert C. Block;Keerthana Natarajan;Lalit K. Mestha;Omer T. Inan;Jin-Oh Hahn;Ramakrishna Mukkamala;
      Pages: 2087 - 2093
      Abstract: Objective: Many calibration models for cuff-less blood pressure (BP) measurement must be periodically updated with cuff BP values to account for vascular aging. However, the time period required for these “cuff re-calibrations” is largely unknown. The impact of one year of aging on several calibration models was assessed. Methods: Ten humans (6 males, 57±18 years, 3 hypertensives) were studied during multiple recording sessions that occurred one year apart. In each session, electrocardiography (ECG), ear photoplethysmography (PPG), finger PPG, and toe PPG waveforms and manual cuff BP were recorded before and after slow breathing, mental arithmetic, cold pressor, and nitroglycerin. Linear models based on each PPG waveform, which were previously shown to offer value in predicting the intervention-induced BP changes in a larger subject cohort, were employed. The model coefficients were determined for each subject via one session, and the fully-defined, subject-specific calibration models were then evaluated in the corresponding subjects via the session one year later. Results: Only a linear model relating toe pulse arrival time (PAT) – time delay between ECG R-wave and toe PPG foot – to systolic BP (SBP) remained useful. After the year, this model changed little on average (root-mean-squared-error (RMSE) = 1.5 mmHg) and predicted the cuff BP values better than the average of the initial cuff BP values of the subject (RMSE = 9.6±0.8 mmHg vs. 12.7±1.0 mmHg; p < 0.05). Conclusion: These results suggest annual cuff recalibrations for the toe PAT-SBP model. Significance: Toe PAT may offer a practical recalibration period that fosters user adherence.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Automated Scoring of Respiratory Events in Sleep With a Single Effort Belt
           and Deep Neural Networks

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      Authors: Thijs E. Nassi;Wolfgang Ganglberger;Haoqi Sun;Abigail A. Bucklin;Siddharth Biswal;Michel J. A. M. van Putten;Robert J. Thomas;M. Brandon Westover;
      Pages: 2094 - 2104
      Abstract: Objective: Automatic detection and analysis of respiratory events in sleep using a single respiratoryeffort belt and deep learning. Methods: Using 9,656 polysomnography recordings from the Massachusetts General Hospital (MGH), we trained a neural network (WaveNet) to detect obstructive apnea, central apnea, hypopnea and respiratory-effort related arousals. Performance evaluation included event-based analysis and apnea-hypopnea index (AHI) stratification. The model was further evaluated on a public dataset, the Sleep-Heart-Health-Study-1, containing 8,455 polysomnographic recordings. Results: For binary apnea event detection in the MGH dataset, the neural network obtained a sensitivity of 68%, a specificity of 98%, a precision of 65%, a F1-score of 67%, and an area under the curve for the receiver operating characteristics curve and precision-recall curve of 0.93 and 0.71, respectively. AHI prediction resulted in a mean difference of 0.41 $pm$ 7.8 and a r2 of 0.90. For the multiclass task, we obtained varying performances: 84% of all labeled central apneas were correctly classified, whereas this metric was 51% for obstructive apneas, 40% for respiratory effort related arousals and 23% for hypopneas. Conclusion: Our fully automated method can detect respiratory events and assess the AHI accurately. Differentiation of event types is more difficult and may reflect in part the complexity of human respiratory output and some degree of arbitrariness in the criteria used during manual annotation. Significance: The current gold standard of diagnosing sleep-disordered breathing, using polysomnography and manual analysis, is time-consuming, expensive, and only a-plicable in dedicated clinical environments. Automated analysis using a single effort belt signal overcomes these limitations.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor
           Imagery EEG Classification

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      Authors: Phairot Autthasan;Rattanaphon Chaisaen;Thapanun Sudhawiyangkul;Phurin Rangpong;Suktipol Kiatthaveephong;Nat Dilokthanakul;Gun Bhakdisongkhram;Huy Phan;Cuntai Guan;Theerawit Wilaiprasitporn;
      Pages: 2105 - 2118
      Abstract: Objective: Advances in the motor imagery (MI)-based brain-computer interfaces (BCIs) allow control of several applications by decoding neurophysiological phenomena, which are usually recorded by electroencephalography (EEG) using a non-invasive technique. Despite significant advances in MI-based BCI, EEG rhythms are specific to a subject and various changes over time. These issues point to significant challenges to enhance the classification performance, especially in a subject-independent manner. Methods: To overcome these challenges, we propose MIN2Net, a novel end-to-end multi-task learning to tackle this task. We integrate deep metric learning into a multi-task autoencoder to learn a compact and discriminative latent representation from EEG and perform classification simultaneously. Results: This approach reduces the complexity in pre-processing, results in significant performance improvement on EEG classification. Experimental results in a subject-independent manner show that MIN2Net outperforms the state-of-the-art techniques, achieving an F1-score improvement of 6.72% and 2.23% on the SMR-BCI and OpenBMI datasets, respectively. Conclusion: We demonstrate that MIN2Net improves discriminative information in the latent representation. Significance: This study indicates the possibility and practicality of using this model to develop MI-based BCI applications for new users without calibration.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
  • Wearables Detect Malaria Early in a Controlled Human-Infection Study

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      Authors: Sidhartha Chaudhury;Chenggang Yu;Ruifeng Liu;Kamal Kumar;Samantha Hornby;Christopher Duplessis;Joel M. Sklar;Judith E. Epstein;Jaques Reifman;
      Pages: 2119 - 2129
      Abstract: Objective: Observational studies on the use of commercially available wearable devices for infection detection lack the rigor of controlled clinical studies, where time of exposure and onset of infection are exactly known. Towards that end, we carried out a feasibility study using a commercial smartwatch for monitoring heart rate, skin temperature, and body acceleration on subjects as they underwent a controlled human malaria infection (CHMI) challenge. Methods: Ten subjects underwent CHMI and were asked to wear the smartwatch for at least 12 hours/day from 2 weeks pre-challenge to 4 weeks post-challenge. Using these data, we developed 2B-Healthy, a Bayesian-based infection-prediction algorithm that estimates a probability of infection. We also collected data from eight control subjects for 4 weeks to assess the false-positive rate of 2B-Healthy. Results: Nine of 10 CHMI subjects developed parasitemia, with an average time to parasitemia of 12 days. 2B-Healthy detected infection in seven of nine subjects (78% sensitivity), where in six subjects it detected infection 6 days before parasitemia (on average). In the eight control subjects, we obtained a false-positive rate of 6%/week. Conclusion: The 2B-Healthy algorithm was able to reliably detect infection prior to the onset of symptoms using data collected from a commercial smartwatch in a controlled human infection study. Significance: Our findings demonstrate the feasibility of wearables as a screening tool to provide early warning of infection and support further research on the use of the 2B-Healthy algorithm as the basis for a wearable infection-detection platform.
      PubDate: June 2022
      Issue No: Vol. 69, No. 6 (2022)
       
 
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