A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

        1 2 | Last   [Sort by number of followers]   [Restore default list]

  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advanced Materials Technologies     Hybrid Journal   (Followers: 1)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 8)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 9)
Advances in Electronics     Open Access   (Followers: 100)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Microelectronic Engineering     Open Access   (Followers: 13)
Advances in Power Electronics     Open Access   (Followers: 41)
Advancing Microelectronics     Hybrid Journal  
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 28)
Annals of Telecommunications     Hybrid Journal   (Followers: 8)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 16)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal  
Batteries     Open Access   (Followers: 9)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 31)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 2)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 9)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 308)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 2)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 124)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 109)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 103)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elektronika ir Elektortechnika     Open Access   (Followers: 4)
Elkha : Jurnal Teknik Elektro     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access   (Followers: 5)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage     Hybrid Journal   (Followers: 1)
Energy Storage Materials     Full-text available via subscription   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal  
EPJ Quantum Technology     Open Access   (Followers: 1)
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 9)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
IACR Transactions on Symmetric Cryptology     Open Access   (Followers: 1)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 102)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 81)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 57)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 3)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 52)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 4)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 42)
IEEE Open Journal of Circuits and Systems     Open Access   (Followers: 3)
IEEE Open Journal of Industry Applications     Open Access   (Followers: 3)
IEEE Open Journal of the Industrial Electronics Society     Open Access   (Followers: 3)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 77)
IEEE Pulse     Hybrid Journal   (Followers: 5)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 23)
IEEE Solid-State Circuits Letters     Hybrid Journal   (Followers: 3)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 369)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 74)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 64)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 39)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 13)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 46)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 227)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 5)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 75)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 40)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 27)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 80)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 4)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 13)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 79)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 11)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 16)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 36)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 61)
IET Smart Grid     Open Access   (Followers: 1)
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 14)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 12)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
International Journal of Control     Hybrid Journal   (Followers: 11)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Hybrid Intelligence     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 16)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 10)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 25)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 12)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 38)
Journal of Electrical Bioimpedance     Open Access  
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 9)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronic Science and Technology     Open Access   (Followers: 1)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access   (Followers: 2)
Journal of Field Robotics     Hybrid Journal   (Followers: 4)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 189)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 10)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 1)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 3)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 11)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
Journal of Power Electronics     Hybrid Journal   (Followers: 2)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 27)
Journal of Signal and Information Processing     Open Access   (Followers: 8)
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microelectronics and Solid State Electronics     Open Access   (Followers: 28)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal   (Followers: 1)
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 8)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 2)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 11)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
Revue Méditerranéenne des Télécommunications     Open Access  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 57)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Solid State Electronics Letters     Open Access  
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Transactions on Cryptographic Hardware and Embedded Systems     Open Access   (Followers: 4)

        1 2 | Last   [Sort by number of followers]   [Restore default list]

Similar Journals
Journal Cover
IEEE Transactions on Biomedical Engineering
Journal Prestige (SJR): 1.267
Citation Impact (citeScore): 5
Number of Followers: 39  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9294
Published by IEEE Homepage  [229 journals]
  • Frontcover
    • Abstract: Presents the front cover for this issue of the publication.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • IEEE Engineering in Medicine and Biology Society
    • 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: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • IEEE Transactions on Biomedical Engineering (T-BME)
    • Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • IEEE Transactions on Biomedical Engineering Handling Editors
    • 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: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • In Vivo Wireless Sensors for Gut Microbiome Redox
           Monitoring
    • Authors: Spyridon Baltsavias;Will Van Treuren;Marcus J. Weber;Jayant Charthad;Sam Baker;Justin L. Sonnenburg;Amin Arbabian;
      Pages: 1821 - 1830
      Abstract: A perturbed gut microbiome has recently been linked with multiple disease processes, yet researchers currently lack tools that can provide in vivo, quantitative, and real-time insight into these processes and associated host-microbe interactions. We propose an in vivo wireless implant for monitoring gastrointestinal tract redox states using oxidation-reduction potentials (ORP). The implant is powered and conveniently interrogated via ultrasonic waves. We engineer the sensor electronics, electrodes, and encapsulation materials for robustness in vivo, and integrate them into an implant that endures autoclave sterilization and measures ORP for 12 days implanted in the cecum of a live rat. The presented implant platform paves the way for long-term experimental testing of biological hypotheses, offering new opportunities for understanding gut redox pathophysiology mechanisms, and facilitating translation to disease diagnosis and treatment applications.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Neuromorphic Dynamical Synapses With Reconfigurable Voltage-Gated Kinetics
    • Authors: Jun Wang;Gert Cauwenberghs;Frédéric D. Broccard;
      Pages: 1831 - 1840
      Abstract: Objective: Although biological synapses express a large variety of receptors in neuronal membranes, the current hardware implementation of neuromorphic synapses often rely on simple models ignoring the heterogeneity of synaptic transmission. Our objective is to emulate different types of synapses with distinct properties. Methods: Conductance-based chemical and electrical synapses were implemented between silicon neurons on a fully programmable and reconfigurable, biophysically realistic neuromorphic VLSI chip. Different synaptic properties were achieved by configuring on-chip digital parameters for the conductances, reversal potentials, and voltage dependence of the channel kinetics. The measured I-V characteristics of the artificial synapses were compared with biological data. Results: We reproduced the response properties of five different types of chemical synapses, including both excitatory ($AMPA$, $NMDA$) and inhibitory ($GABA_A$, $GABA_C$, $glycine$) ionotropic receptors. In addition, electrical synapses were implemented in a small network of four silicon neurons. Conclusion: Our work extends the repertoire of synapse types between silicon neurons, providing greater flexibility for the design and implementation of biologically realistic neural networks on neuromorphic chips. Significance: A higher synaptic heterogeneity in neuromorphic chips is relevant for the hardware implementation of energy-efficient population codes as well as for dynamic clamp applications where neural models are implemented in neuromorphic VLSI hardwar-.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Spatiotemporal Hemodynamic Complexity in Carotid Arteries: An Integrated
           Computational Hemodynamics and Complex Networks-Based Approach
    • Authors: Karol Calò;Diego Gallo;David A. Steinman;Valentina Mazzi;Stefania Scarsoglio;Luca Ridolfi;Umberto Morbiducci;
      Pages: 1841 - 1853
      Abstract: Objective: The study of the arterial hemodynamics is essential for a better understanding of the risks associated with the onset/progression of vascular disease. However, conventional quantification and visualization paradigms are not sufficient to fully capture the spatiotemporal evolution of correlated blood flow patterns and their “sphere of influence” in complex vascular geometries. In the attempt to bridge this knowledge gap, an integrated computational hemodynamics and complex networks-based approach is proposed to unveil organization principles of cardiovascular flows. Methods: The approach is applied to ten patient-specific hemodynamic models of carotid bifurcation, a vascular bed characterized by a complex hemodynamics and clinically-relevant disease. Correlation-based networks are built starting from time-histories of two fluid mechanics quantities of physiological significance, respectively (1) the blood velocity vector axial component locally aligned with the main flow direction, and (2) the kinetic helicity density. Results: Unlike conventional hemodynamic analyses, here the spatiotemporal similarity of dynamic intravascular flow structures is encoded in a distance function. In the case of the carotid bifurcation, this study measures for the first time to what extent flow similarity is disrupted by vascular geometric features. Conclusion: It emerges that a larger bifurcation expansion, a hallmark of vascular disease, significantly disrupts the network topological connections between axial flow structures, reducing also their anatomical persistence length. On the contrary, connections in helical flow patterns are overall less geometry-sensitive. Significance: The integrated approach proposed here, by exploiting the connections of hemodynamic patterns undergoing similar dynamical evolution, opens avenues for furthe- comprehension of vascular physiopathology.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Thermal Therapy With a Fully Electronically Steerable HIFU Phased Array
           Using Ultrasound Guidance and Local Harmonic Motion Monitoring
    • Authors: Pegah Aslani;Leah Drost;Yuexi Huang;Benjamin B. C. Lucht;Erin Wong;Gregory Czarnota;Caitlin Yee;Bo Angela Wan;Vithusha Ganesh;Samuel T. Gunaseelan;Elizabeth David;Edward Chow;Kullervo Hynynen;
      Pages: 1854 - 1862
      Abstract: The method of localized harmonic motion (LHM) monitoring has been proposed as an ultrasound-based monitoring technique for in vivo real-time ultrasound-guidance during thermal surgery. Objective: The focus of this paper is to study the performance of LHM monitoring in vivo in order to assess the tissue coagulation during ultrasound surgery of bone metastases. This is done through a pre-clinical study on large scale animals (pigs) as well as a first-in-human pilot study, using a hand held ultrasound-guided HIFU phased array. Methods: A flat, fully steerable HIFU phased array system (1024 elements, 100 mm diameter, 516 kHz), in combination with a co-aligned 64 element imaging system, is used to perform thermal surgery and monitor tissue coagulation using the LHM technique. The in vivo experiments are conducted using thirteen animals, followed by a first-in-human pilot study in which nine patients are enrolled. Results: The pre-clinical results show that the LHM monitoring method is able to detect about 80% of the observed coagulated tissue volumes visible in dissection. In the pilot study, six out of nine patients have durable pain reduction with good correlation observed from LHM detections. Conclusion: In general, the results suggest that the LHM monitoring performance is promising in detecting thermal tissue coagulation during focused ultrasound surgery in tissues close to the bone. Significance: The LHM technique can offer a very accessible and cost-efficient monitoring solution during ultrasound surgery within a clinical setting.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Noninvasive Cardiorespiratory Signals Analysis for Asthma Evolution
           Monitoring in Preschool Children
    • Authors: Javier Milagro;Javier Gracia-Tabuenca;Ville-Pekka Seppä;Jussi Karjalainen;Marita Paassilta;Michele Orini;Raquel Bailón;Eduardo Gil;Jari Viik;
      Pages: 1863 - 1871
      Abstract: Objective: Despite its increasing prevalence, diagnosis of asthma in children remains problematic due to their difficulties in producing repeatable spirometric maneuvers. Moreover, low adherence to inhaled corticosteroids (ICS) treatment could result in permanent airway remodeling. The growing interest in a noninvasive and objective way for monitoring asthma, together with the apparent role of autonomic nervous system (ANS) in its pathogenesis, have attracted interest towards heart rate variability (HRV) and cardiorespiratory coupling (CRC) analyses. Methods: HRV and CRC were analyzed in 68 children who were prescribed ICS treatment due to recurrent obstructive bronchitis. They underwent three different electrocardiogram and respiratory signals recordings, during and after treatment period. After treatment completion, they were followed up during 6 months and classified attending to their current asthma status. Results: Vagal activity, as measured from HRV, and CRC, were reduced after treatment in those children at lower risk of asthma, whereas it kept unchanged in those with a worse prognosis. Conclusion: Results suggest that HRV analysis could be useful for the continuous monitoring of ANS anomalies present in asthma, thus contributing to evaluate the evolution of the disease, which is especially challenging in young children. Significance: Noninvasive ANS assessment using HRV analysis could be useful in the continuous monitoring of asthma in children.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Monocular 3D Probe Tracking for Generating Sub-Surface Optical Property
           Maps From Diffuse Optical Spectroscopic Imaging
    • Authors: Robert Amelard;Jesse H. Lam;Brian Hill;Amanda Durkin;Kyle Cutler;Bruce J. Tromberg;
      Pages: 1872 - 1881
      Abstract: Objective: Diffuse optical spectroscopic imaging (DOSI) is a promising biophotonic technology for clinical tissue assessment, but is currently hampered by difficult wide area assessment. A co-integrative optical imaging system is proposed for dense sub-surface optical property spatial assessment. Methods: The proposed system fuses a co-aligned set of camera frames and diffuse optical spectroscopy measurements to generate spatial sub-surface optical property maps. A 3D rigid body motion estimation model was developed by fitting automatically detected target features to an a priori geometric model using a single overhead camera. Point-wise optical properties were measured across the tissue using frequency domain photon migration DOSI. The 3D probe trajectory and temporal optical property data were fused to generate 2D spatial optical property maps, which were projected onto the tissue image using pre-calibrated camera parameters. Results: The system demonstrated sub-millimeter positional accuracy (error 0.24 $ pm $ 0.35 mm) across different probe speeds (1.0–3.8 cm/s), and displacement accuracy in overhead ($-text{0.42}pm text{0.33}$ mm) and tilted (0.51 $pm $ 0.51 mm) camera orientations. Unstructured scans on a tumor inclusion phantom showed strong contrast under different probe paths, and significant ($p< 0.001$) changes in optical properties in an in vivo leg cuff occlusion protocol with spatial anatomy localization. Conclusion: The proposed co-integrative optical imaging-system generated dense sub-surface optical property distributions across wide tissue areas with sub-millimeter accuracy at different probe speeds and trajectories, and does not require pre-planned probe route for tissue assessment. Significance: This system provides a valuable tool for real-time non-invasive tissue health and cancer screening, and enables longitudinal disease progression assessment through unstructured probe-based optical tissue assessment.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Wavelet Analysis of the Temporal Dynamics of the Laser Speckle Contrast in
           Human Skin
    • Authors: Irina Mizeva;Viktor Dremin;Elena Potapova;Evgeny Zherebtsov;Igor Kozlov;Andrey Dunaev;
      Pages: 1882 - 1889
      Abstract: Objective: Spectral analysis of laser Doppler flowmetry (LDF) signals has been widely used in studies of physiological vascular function regulation. An alternative to LDF is the laser speckle contrast imaging method (LSCI), which is based on the same physical principle. In contrast to LDF, LSCI provides non-scanning full-field imaging of a relatively wide skin area and offers high spatial and temporal resolutions, which allows visualization of microvascular structure. This circumstance, together with a large number of works which had shown the effectiveness of temporal LSCI analysis, gave impetus to experimental studies of the relation between LDF and LSCI used to monitor the temporal dynamics of blood flow. Methods: Continuous wavelet transform was applied to construct a time-frequency representation of a signal. Results: Analysis of 10 minute LDF and LSCI output signals recorded simultaneously revealed rather high correlation between oscillating components. It was demonstrated for the first time that the spectral energy of oscillations in the 0.01–2 Hz frequency range of temporal LSCI recordings carries the same information as the conventional LDF recordings and hence it reflects the same physiological vascular tone regulation mechanisms. Conclusion: The approach proposed can be used to investigate speckle pattern dynamics by LSCI in both normal and pathological conditions. Significance: The results of research on the influence of spatial binning and averaging on the spectral characteristics of perfusion monitored by LSCI are of considerable interest for the development of LSCI systems optimized to evaluate temporal dynamics.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Real-Time Radiofrequency Ablation Lesion Depth Estimation Using
           Multi-frequency Impedance With a Deep Neural Network and Tree-Based
           Ensembles
    • Authors: Emre Besler;Yearnchee Curtis Wang;Alan V. Sahakian;
      Pages: 1890 - 1899
      Abstract: Objective: Design and optimization of statistical models for use in methods for estimating radiofrequency ablation (RFA) lesion depths in soft real-time performance. Methods: Using tissue multi-frequency complex electrical impedance data collected from a low-cost embedded system, a deep neural network (NN) and tree-based ensembles (TEs) were trained for estimating the RFA lesion depth via regression. Results: Addition of frequency sweep data, previous depth data, and previous RF power state data boosted accuracy of the statistical models. The root mean square errors were 2 mm for NN and 0.5 mm for TEs for previous statistical models and the root mean square errors were 0.4 mm for NN and 0.04 mm for TEs for the statistical models presented in this paper. Simulation ablation performance showed a mean difference against physical measurements of $0.5 pm 0.2$ mm for the NN-based depth estimation method and $0.7 pm 0.4$ mm for the TE-based depth estimation method. Conclusion: The results show that multi-frequency data significantly improves the depth estimation performance of the statistical models. Significance: The RFA lesion depth estimation methods presented in this work achieve millimeter-resolution accuracy with soft real-time performance on an ARMv7-based embedded system for potential translation to clinical RFA technologies.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Computational Studies on the Effects of Applied Apical Torsion for Cardiac
           Assist on Regional Wall Mechanics
    • Authors: Elaine Soohoo;Lewis K. Waldman;Dennis R. Trumble;
      Pages: 1900 - 1911
      Abstract: Objective: Here we report the results of parametric computational simulations evaluating the biomechanical effects of applied apical torsion (AAT) on a patient-specific bi-ventricular failing heart model. Methods: We examined the resulting effects on cardiac biomechanics with varying device coverage areas and applied rotation angles to determine the practical working limits of AAT on a dilated cardiomyopathy heart model. Results: The largest maximum principal stresses and strains observed in the heart failure model were 80.21 kPa (at the basal node of the left ventricular epicardium) and 0.56 (at the node of the device base of the left ventricular free wall). Results show that increasing levels of AAT beyond 45 degrees produce supra-physiologic levels of stress and strain in the myocardium. Conclusion: Maximum principal stresses greater than 100 kPa were observed at multiple nodes along the epicardium and endocardium of the ventricular base and in the endocardium at the device base. Maximum principal strains greater than 0.60 were observed at multiple nodes along the epicardium and endocardium of the ventricular base. Significance: This suggests that while AAT has the potential to provide meaningful returns to hemodynamic function in failing hearts, the large deformations produced by this approach with the upper bounds of applied rotation angle realistically excludes supra-physiological rotations as a means for cardiac support. However, lower AAT angles – closer to that of the native left-ventricular torsion – coupled with another means of external cardiac compression may prove to be a viable method of cardiac assist.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Estimating Functional Connectivity Networks via Low-Rank Tensor
           Approximation With Applications to MCI Identification
    • Authors: Xiao Jiang;Limei Zhang;Lishan Qiao;Dinggang Shen;
      Pages: 1912 - 1920
      Abstract: Functional connectivity network (FCN) has become an increasingly important approach to gain a better understanding of the brain, as well as discover informative biomarkers for diagnosis of neurodegenerative diseases. Due to its importance, many FCN estimation methods have been developed in the past decades, including methods based on the classical Pearson's correlation, (regularized) partial correlation, and some higher-order variants. However, most of the existing methods estimate one FCN at a time, thus ignoring the possibly shared structure among FCNs from different subjects. Recently, researchers introduce group constraints (or population priors) into FCN estimation by assuming that FCNs are topologically identical across subjects. Obviously, such a constraint/prior is too strong to be satisfied in practice, especially when both patients and healthy subjects are involved simultaneously in the group. To address this problem, we propose a novel FCN estimation approach based on an assumption that the involved FCNs have similar but not necessarily identical topology. More specifically, we implement this idea under a two-step learning framework. First, we independently estimate FCNs based on traditional methods, such as Pearson's correltion and sparse representation, making sure that each FCN captures the specific properties of the corresponding subject. Then, we stack the estimated FCNs (in fact, their adjacency matrices) into a tensor, and refine the stacked FCNs via low-rank tensor approximation. Finally, we apply the improved FCNs to identify subjects with mild cognitive impairment (MCI) from healthy controls, and achieve a higher classification accuracy.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Stimulation Pattern Efficiency in Percutaneous Auricular Vagus Nerve
           Stimulation: Experimental Versus Numerical Data
    • Authors: Eugenijus Kaniusas;Amine Mohammed Samoudi;Stefan Kampusch;Katarzyna Bald;Emmeric Tanghe;Luc Martens;Wout Joseph;Jozsef Constantin Széles;
      Pages: 1921 - 1935
      Abstract: Objective: Percutaneous electrical stimulation of the auricular vagus nerve (pVNS) is an electroceutical technology. The selection of stimulation patterns is empirical, which may lead to under-stimulation or over-stimulation. The objective is to assess the efficiency of different stimulation patterns with respect to individual perception and to compare it with numerical data based on in-silico ear models. Methods: Monophasic (MS), biphasic (BS) and triphasic stimulation (TS) patterns were tested in volunteers. Different clinically-relevant perception levels were assessed. In-silico models of the human ear were created with embedded fibers and vessels to assess different excitation levels. Results: TS indicates experimental superiority over BS which is superior to MS while reaching different perception levels. TS requires about 57% and 35% of BS and MS magnitude, respectively, to reach the comfortable perception. Experimental thresholds decrease from non-bursted to bursted stimulation. Numerical results indicate a slight superiority of BS and TS over MS while reaching different excitation levels, whereas the burst length has no influence. TS yields the highest number of asynchronous action impulses per stimulation symbol for the used tripolar electrode set-up. Conclusion: The comparison of experimental and numerical data favors the novel TS pattern. The analysis separates excitatory pVNS effects in the auricular periphery, as accounted by in-silico data, from the combination of peripheral and central pVNS effects in the brain, as accounted by experimental data. Significance: The proposed approach moves from an empirical selection of stimulation patterns towards efficient and optimized pVNS settings.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Segmentation-Based Blood Flow Parameter Refinement in Cerebrovascular
           Structures Using 4-D Arterial Spin Labeling MRA
    • Authors: Renzo Phellan;Thomas Lindner;Michael Helle;Alexandre X. Falcão;Clarissa L. Yasuda;Magdalena Sokolska;Rolf H. Jäger;Nils Daniel Forkert;
      Pages: 1936 - 1946
      Abstract: Objective: Cerebrovascular diseases are one of the main global causes of death and disability in the adult population. The preferred imaging modality for the diagnostic routine is digital subtraction angiography, an invasive modality. Time-resolved three-dimensional arterial spin labeling magnetic resonance angiography (4D ASL MRA) is an alternative non-invasive modality, which captures morphological and blood flow data of the cerebrovascular system, with high spatial and temporal resolution. This work proposes advanced medical image processing methods that extract the anatomical and hemodynamic information contained in 4D ASL MRA datasets. Methods: A previously published segmentation method, which uses blood flow data to improve its accuracy, is extended to estimate blood flow parameters by fitting a mathematical model to the measured vascular signal. The estimated values are then refined using regression techniques within the cerebrovascular segmentation. The proposed method was evaluated using fifteen 4D ASL MRA phantoms, with ground-truth morphological and hemodynamic data, fifteen 4D ASL MRA datasets acquired from healthy volunteers, and two 4D ASL MRA datasets from patients with a stenosis. Results: The proposed method reached an average Dice similarity coefficient of 0.957 and 0.938 in the phantom and real dataset segmentation evaluations, respectively. The estimated blood flow parameter values are more similar to the ground-truth values after the refinement step, when using phantoms. A qualitative analysis showed that the refined blood flow estimation is more realistic compared to the raw hemodynamic parameters. Conclusion: The proposed method can provide accurate segmentations and blood flow parameter estimations in the cerebrovascular system using 4D ASL MRA datasets. Significance: The information obtained with the proposed method can help clinicians an- researchers to study the cerebrovascular system non-invasively.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Adaptive Calibration of Electrode Array Shifts Enables Robust Myoelectric
           Control
    • Authors: Xu Zhang;Le Wu;Bin Yu;Xiang Chen;Xun Chen;
      Pages: 1947 - 1957
      Abstract: Objective: The objective of this work is to develop a novel method for adaptive calibration of the electrode array shifts toward achieving robust myoelectric pattern-recognition control. Methods: This work is inspired by the idea of image object detection when high-density surface electromyogram signals recorded from a two-dimensional electrode array carry rich spatial information and can serve as a muscular activation image. A convolutional neural network involving transfer learning (from a network for image recognition) is used to learn muscular activity patterns at an original/baseline position of an electrode array. The shift of an electrode array can be estimated by identifying and matching partially overlapped regions between the training images of muscular activation and the testing images at any other position, in an unsupervised manner. Given the calibration of an electrode array shift, the identification of muscular activity patterns is implemented accordingly. The performance of the proposed method was evaluated with data recorded by a 10 × 10 electrode array placed over the forearm extensors of 10 subjects performing 6 wrist and finger extension tasks. Results: The proposed method achieved high task classification accuracies around 95% and outperformed five traditional methods under conditions with multiple designated shifts in offline experiments and a random shift in online testing. Conclusion: The proposed method is demonstrated to be a promising solution for the automatic and adaptive calibration of electrode array shifts. Significance: This work will enhance the robustness of myoelectric control systems.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Establishment and Experiment of Utility Archwire Dynamic Orthodontic
           Moment Prediction Model
    • Authors: Jingang Jiang;Zhiyuan Huang;Xuefeng Ma;Yongde Zhang;Tianhua He;Yi Liu;
      Pages: 1958 - 1968
      Abstract: Objective: This study investigated the performance of a dynamic orthodontic moment prediction model by analyzing orthodontic treatment processes with different utility archwires. Method: The prediction model was based on a wax resistance model, the combined load theory of beams and the lateral buckling theory of prisms. The experimental samples used herein comprised 12 different archwire configurations (3 different materials and 4 different diameters). The utility archwire was ligated to the 11th tooth of the wax mold, which was immersed in a constant temperature water environment at 75 °C for 2 min. Result: As the archwire diameter increased, increasing the elastic modulus of the archwire produced greater increases in the change rate of the orthodontic moment with respect to the lateral arc length. A comparison of the orthodontic moment values from three common orthodontic archwire materials revealed the following trend: stainless steel wire> Australian wire> Ni-Ti wire. Conclusion: The accuracy of the utility archwire dynamic orthodontic moment prediction model was verified through a comparison of the experimental measurements and theoretical calculations. Significance: The presented model can help make timely adjustments to orthodontic treatment schemes, improve the orthodontic effect, shorten the treatment cycle, and provide reference and guidance that enables orthodontists to carry out orthodontic treatment safely and efficiently.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Joint, Partially-Joint, and Individual Independent Component Analysis in
           Multi-Subject fMRI Data
    • Authors: Mansooreh Pakravan;Mohammad Bagher Shamsollahi;
      Pages: 1969 - 1981
      Abstract: Objective: Joint analysis of multi-subject brain imaging datasets has wide applications in biomedical engineering. In these datasets, some sources belong to all subjects (joint), a subset of subjects (partially-joint), or a single subject (individual). In this paper, this source model is referred to as joint/partially-joint/individual multiple datasets unidimensional (JpJI-MDU), and accordingly, a source extraction method is developed. Method: We present a deflation-based algorithm utilizing higher order cumulants to analyze the JpJI-MDU source model. The algorithm maximizes a cost function which leads to an eigenvalue problem solved with thin-SVD (singular value decomposition) factorization. Furthermore, we introduce the JpJI-feature which indicates the spatial shape of each source and the amount of its jointness with other subjects. We use this feature to determine the type of sources. Results: We evaluate our algorithm by analyzing simulated data and two real functional magnetic resonance imaging (fMRI) datasets. In our simulation study, we will show that the proposed algorithm determines the type of sources with the accuracy of 95% and 100% for 2-class and 3-class clustering scenarios, respectively. Furthermore, our algorithm extracts meaningful joint and partially-joint sources from the two real datasets, which are consistent with the existing neuroscience studies. Conclusion: Our results in analyzing the real datasets reveal that both datasets follow the JpJI-MDU source model. This source model improves the accuracy of source extraction methods developed for multi-subject datasets. Significance: The proposed joint blind source separation algorithm is robust and avoids parameters which are difficult to fine-tune.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Development of Multi-Layer Lateral-Mode Ultrasound Needle Transducer for
           Brain Stimulation in Mice
    • Authors: Yao Jin;Yongchuan Li;Yang Ye;Junjie Zou;Tianxu Guo;Tianyuan Bian;Congzhi Wang;Yang Xiao;Lili Niu;Teng Ma;Hairong Zheng;
      Pages: 1982 - 1988
      Abstract: Ultrasound, a non-invasive stimulation method, has proved effective in neurostimulation. Previous studies have demonstrated that low-frequency ultrasound (less than 1 MHz) is preferable owing to better penetrability through tissue and skull. However, the large size of low-frequency transducers, which are used in ultrasound neurostimulation studies, makes it difficult to perform multiple-target neurostimulation, especially in small animals such as mice. In this paper, a proposed low-frequency ultrasound needle transducer based on the multi-layer lateral-mode coupling method with a miniature aperture of 0.6 mm × 0.6 mm and a thickness of 1.65 mm was designed and fabricated. The measured electrical impedance of the fabricated 8-layer lateral-mode PZT-5H ceramic was 50.76 Ω at a resonant frequency of 866 kHz. The −6 dB bandwidth of 8-layer lateral-mode transducer was 29% at a center frequency of 876 kHz. The maximum ultrasound peak pressure amplitude at 820 kHz reached approximately 300 kPa, 4–5 times higher than that of the single-layer thickness-mode transducer with 200 V input voltage. The ultrasound beam showed no attenuation and low shift through mouse skull. To verify the feasibility of using the needle transducer to perform multiple-target nerve stimulation in mice brains, we constructed an ultrasound stimulus system to simultaneously stimulate two areas (M2 and V1) of the mouse brain in vivo and detected the c-Fos expression by immunofluorescence to evaluate the effect of stimulation. The results showed that a high ultrasound peak pressure amplitude with this transducer configuration is useful for ultrasound neurostimulation and multiple-target stimulation in mice.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • A Review of Wearable Sensor Systems to Monitor Plantar Loading in the
           Assessment of Diabetic Foot Ulcers
    • Authors: Lefan Wang;Dominic Jones;Graham J Chapman;Heidi J. Siddle;David A Russell;Ali Alazmani;Peter Culmer;
      Pages: 1989 - 2004
      Abstract: Diabetes is highly prevalent throughout the world and imposes a high economic cost on countries at all income levels. Foot ulceration is one devastating consequence of diabetes, which can lead to amputation and mortality. Clinical assessment of diabetic foot ulcer (DFU) is currently subjective and limited, impeding effective diagnosis, treatment and prevention. Studies have shown that pressure and shear stress at the plantar surface of the foot plays an important role in the development of DFUs. Quantification of these could provide an improved means of assessment of the risk of developing DFUs. However, commercially-available sensing technology can only measure plantar pressures, neglecting shear stresses and thus limiting their clinical utility. Research into new sensor systems which can measure both plantar pressure and shear stresses are thus critical. Our aim in this paper is to provide the reader with an overview of recent advances in plantar pressure and stress sensing and offer insights into future needs in this critical area of healthcare. Firstly, we use current clinical understanding as the basis to define requirements for wearable sensor systems capable of assessing DFU. Secondly, we review the fundamental sensing technologies employed in this field and investigate the capabilities of the resultant wearable systems, including both commercial and research-grade equipment. Finally, we discuss research trends, ongoing challenges and future opportunities for improved sensing technologies to monitor plantar loading in the diabetic foot.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Simulation of Motor Unit Action Potential Recordings From Intramuscular
           Multichannel Scanning Electrodes
    • Authors: Akhmadeev Konstantin;Tianyi Yu;Eric Le Carpentier;Yannick Aoustin;Dario Farina;
      Pages: 2005 - 2014
      Abstract: Multi-channel intramuscular EMG (iEMG) provides information on motor neuron behavior, muscle fiber (MF) innervation geometry and, recently, has been proposed as a means to establish a human-machine interface. Objective: to provide a reliable benchmark for computational methods applied to such recordings, we propose a simulation model for iEMG signals acquired by intramuscular multi-channel electrodes. Methods: we propose several modifications to the existing motor unit action potentials (MUAPs) simulation methods, such as farthest point sampling (FPS) for the distribution of motor unit territory centers in the muscle cross-section, accurate fiber-neuron assignment algorithm, modeling of motor neuron action potential propagation delay, and a model of multi-channel scanning electrode. Results: we provide representative applications of this model to the estimation of motor unit territories and the iEMG decomposition evaluation. Also, we extend it to a full multi-channel iEMG simulator using classic linear EMG modeling. Conclusions: altogether, the proposed models provide accurate MUAPs across the entire motor unit territories and for various electrode configurations. Significance: they can be used for the development and evaluation of mathematical methods for multi-channel iEMG processing and analysis.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Bidimensional Multiscale Fuzzy Entropy and Its Application to
           Pseudoxanthoma Elasticum
    • Authors: Mirvana Hilal;Clémence Berthin;Ludovic Martin;Hamed Azami;Anne Humeau-Heurtier;
      Pages: 2015 - 2022
      Abstract: Objective: We propose a new bidimensional entropy measure and its multiscale form and evaluate their behavior using various synthetic and real images. The bidimensional multiscale measure finds application in helping clinicians for pseudoxanthoma elasticum (PXE) detection in dermoscopic images. Method: We developed bidimensional fuzzy entropy ($FuzEn_{2D}$) and its multiscale extension ($MSF_{2D}$) and then evaluated them on a set of synthetic images and texture datasets. Afterwards, we applied $ MSF_{2D}$ to dermoscopic PXE images and compared the results to those obtained by bidimensional multiscale sample entropy ($MSE_{2D}$). Results: The results for the synthetic images illustrate that $FuzEn_{2D}$ has the ability to quantify images irregularity. Moreover, $FuzEn_{2D}$, compared with bidimensional sample entropy ($SampEn_{2D}$), leads to more stable results. The tests with the multiscale version show that $ MSF_{2D}$ is a proper image complexity measure. When applied to the dermoscopic PXE images, the paired t-test illustrates a significant statistical difference between $ MSF_{2D}$ of neck images with papules and normal skin images at a couple of scale factors. Conclusion: T-e results for the synthetic data illustrate that $FuzEn_{2D}$ is an image irregularity measure that overcomes $SampEn_{2D}$ in terms of reliability, especially for small-sized images, and stability of results. The results for the PXE dermoscopic images demonstrate the ability of $MSF_{2D}$ to recognize dermoscopic images of normal zones from PXE papules zones with a large effect size. Significance: This work introduces new image irregularity and complexity measures and shows the potential for $ MSF_{2D}$ to serve as a possible tool helping medical doctors in PXE diagnosis.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor
           Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence
           Tomography
    • Authors: Lin Yin;Kun Wang;Tong Tong;Yu An;Hui Meng;Xin Yang;Jie Tian;
      Pages: 2023 - 2032
      Abstract: Objective: Bioluminescence tomography (BLT) is a non-invasive technique designed to enable three-dimensional (3D) visualization and quantification of viable tumor cells in living organisms. However, despite the excellent sensitivity and specificity of bioluminescence imaging (BLI), BLT is limited by the photon scattering effect and ill-posed inverse problem. If the complete structural information of a light source is considered when solving the inverse problem, reconstruction accuracy will be improved. Methods: This article proposed a block sparse Bayesian learning method based on K-nearest neighbor strategy (KNN-BSBL), which incorporated several types of a priori information including sparsity, spatial correlations among neighboring points, and anatomical information to balance over-sparsity and morphology preservation in BLT. Furthermore, we considered the Gaussian weighted distance prior in a light source and proposed a KNN-GBSBL method to further improve the performance of KNN-BSBL. Results: The results of numerical simulations and in vivo glioma-bearing mouse experiments demonstrated that KNN-BSBL and KNN-GBSBL achieved superior accuracy for tumor spatial positioning and morphology reconstruction. Conclusion: The proposed method KNN-BSBL incorporated several types of a priori information is an efficient and robust reconstruction method for BLT.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • In Vivo Photoacoustic Sentinel Lymph Node Imaging Using
           Clinically-Approved Carbon Nanoparticles
    • Authors: Songde Liu;Hang Wang;Chenxi Zhang;Jiangning Dong;Shengchun Liu;Ronald Xu;Chao Tian;
      Pages: 2033 - 2042
      Abstract: Objective: Breast cancer is the most common type of invasive cancer and one of the leading causes of cancer death in women worldwide. Correct staging of breast cancer is critical to the survival rate of the patients. Sentinel lymph node (SLN) biopsy (SLNB), currently the gold standard technique for breast cancer staging, requires preoperative and intraoperative image guidance for noninvasive SLN identification and minimal surgical invasion. However, existing image guidance techniques suffer from a variety of limitations, such as ionizing radiation, high cost, and poor imaging depth. To address the clinical challenges, new methodology has to be developed. Methods: We developed a photoacoustic (PA) imaging procedure for noninvasive and nonradioactive SLN identification and biopsy guidance enhanced with a clinically-approved lymphatic tracer, i.e., carbon nanoparticles (CNPs) suspension injection. Results: In vivo experiments show that the proposed procedure could sensitively identify the SLN and provide high-contrast image guidance for fine-needle aspiration simulation. In addition, we demonstrated that CNPs have significantly better performance than other commonly-used contrast agents, such as methylene blue and indocyanine green. Conclusion: PA imaging technique using clinically-approved CNPs as the contrast agent is capable for noninvasive and nonradioactive SLN identification and high-contrast biopsy guidance, and should be considered as a new tool for assisting SLNB in breast cancer staging. Significance: The proposed CNPs-enhanced PA imaging technique provides a practical way for SLN identification and biopsy guidance for breast cancer patients and paves the way for clinical translation of PA SLN imaging.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Simplified Non-Thermal Tissue Ablation With a Single Insertion Device
           Enabled by Bipolar High-Frequency Pulses
    • Authors: Matthew R. DeWitt;Eduardo L. Latouche;Jacob D. Kaufman;Christopher C. Fesmire;Jacob H. Swet;Russel C. Kirks;Erin H. Baker;Dionisios Vrochides;David A. Iannitti;Iain H. McKillop;Rafael V. Davalos;Michael B. Sano;
      Pages: 2043 - 2051
      Abstract: Objective: To demonstrate the feasibility of a single electrode and grounding pad approach for delivering high frequency irreversible electroporation treatments (H-FIRE) in in-vivo hepatic tissue. Methods: Ablations were created in porcine liver under surgical anesthesia by adminstereing high frequency bursts of 0.5–5.0 μs pulses with amplitudes between 1.1–1.7 kV in the absence of cardiac synchronization or intraoperative paralytics. Finite element simulations were used to determine the electric field strength associated with the ablation margins (ELethal) and predict the ablations feasible with next generation electronics. Results: All animals survived the procedures for the protocol duration without adverse events. ELethal of 2550, 1650, and 875 V/cm were found for treatments consisting of 100x bursts containing 0.5 μs pulses and 25, 50, and 75 μs of energized-time per burst, respectively. Treatments with 1 μs pulses consisting of 100 bursts with 100 μs energized-time per burst resulted in ELethal of 650 V/cm. Conclusion: A single electrode and grounding pad approach was successfully used to create ablations in hepatic tissue. This technique has the potential to reduce challenges associated with placing multiple electrodes in anatomically challenging environments. Significance: H-FIRE is an in situ tumor ablation approach in which electrodes are placed within or around a targeted region to deliver high voltage electrical pulses. Electric fields generated around the electrodes induce irrecoverable cell membrane damage leading to predictable cell death in the relative absence of thermal damage. The s-aring of architectural integrity means H-FIRE offers potential advantages compared to thermal ablation modalities for ablating tumors near critical structures.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Apprenticeship Learning for a Predictive State Representation of
           Anesthesia
    • Authors: Pierre Humbert;Clément Dubost;Julien Audiffren;Laurent Oudre;
      Pages: 2052 - 2063
      Abstract: Objective: In this paper, we present an original decision support algorithm to assist the anesthesiologists delivery of drugs to maintain the optimal Depth of Anesthesia (DoA). Methods: Derived from a Transform Predictive State Representation algorithm (TPSR), our model learned by observing anesthesiologists in practice. This framework, known as apprenticeship learning, is particularly useful in the medical field as it is not based on an exploratory process – a prohibitive behavior in healthcare. The model only relied on the four commonly monitored variables: Heart Rate (HR), the Mean Blood Pressure (MBP), the Respiratory Rate (RR) and the concentration of anesthetic drug (AAFi). Results: Thirty-one patients have been included. The performances of the model is analyzed with metrics derived from the Hamming distance and cross entropy. They demonstrated that low rank dynamical system had the best performances on both predictions and simulations. Then, a confrontation of our agent to a panel of six real anesthesiologists demonstrated that $boldsymbol{95.7}$% of the actions were valid. Conclusion: These results strongly support the hypothesis that TPSR based models convincingly embed the behavior of anesthesiologists including only four variables that are commonly assessed to predict the DoA. Significance: The proposed novel approach could be of great help for clinicians by improving the fine tuning of the DoA. Furthermore, the possibility to predict the evolutions of the variables would help preventing side effects such as low blood pressure. A tool that could autonomously help the anesthesiologist would thus improve safety-level in the surgical room.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Designing Phase-Sensitive Common Spatial Pattern Filter to Improve
           Brain-Computer Interfacing
    • Authors: Biswadeep Chakraborty;Lidia Ghosh;Amit Konar;
      Pages: 2064 - 2072
      Abstract: This paper addresses an interesting problem to model common spatial pattern (CSP) using an objective function employed to segregate EEG signals for a given cognitive task into two classes. The novelty of the present research is to include phase information of the EEG signal along with the amplitude for differentiating class boundaries. Two modified CSP algorithms are proposed in this paper. The first one introduces the composite effect of amplitude and phase angle of the EEG signal in CSP formulation and is solved using Lagrange’s multiplier method taking phase information of EEG into account. In the second approach, a novel CSP algorithm is proposed in this paper which has the efficacy of handling the non-linearities hidden in the brain signal, here EEG. Experiments undertaken confirm that the proposed phase-sensitive CSP yields the best performance than their non-phase sensitive counterparts by a large margin with respect to classification accuracy.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Optical Coherence Tomography Guided Robotic Needle Insertion for Deep
           Anterior Lamellar Keratoplasty
    • Authors: Mark Draelos;Gao Tang;Brenton Keller;Anthony Kuo;Kris Hauser;Joseph A. Izatt;
      Pages: 2073 - 2083
      Abstract: Objective: Deep anterior lamellar keratoplasty (DALK) significantly reduces the post-transplantation morbidity in patients eligible for partial-thickness cornea grafts. The popular “big bubble” technique for DALK is so challenging, however, that a significant fraction of corneal pneumodissection attempts fail for surgeons without extensive DALK-specific experience, even with previous-generation cross-sectional optical coherence tomography (OCT) guidance. We seek to develop robotic, volumetric OCT-guided technology capable of facilitating or automating the difficult needle insertion step in DALK. Methods: Our system provides for real-time volumetric corneal imaging, segmentation, and tracking of the needle insertion to display feedback for surgeons and to generate needle insertion plans for robotic execution. We include a non-automatic mode for cooperative needle control for stabilization and tremor attenuation, and an automatic mode in which needle insertion plans are generated based on OCT tracking results and executed under surgeon hold-to-run control by the robot arm. We evaluated and compared freehand, volumetric OCT-guided, cooperative, and automatic needle insertion approaches in terms of perforation rate and final needle depth in an ex vivo human cornea model. Results: Volumetric OCT visualization reduces cornea perforations and beneficially increases final needle depth in manual insertions by clinically significant amounts. Our automatic robotic needle insertion techniques meet or exceed surgeon performance in both needle placement and perforation rate. Conclusion: Volumetric OCT is a key enabler for surgeons, although robotic techniques can reliably replicate their performance. Significance: Robotic needle control and volumetric OCT promise to improve outcomes in DALK.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Miniaturized Intracavitary Forward-Looking Ultrasound Transducer for
           Tissue Ablation
    • Authors: Howuk Kim;Huaiyu Wu;Namwoo Cho;Pei Zhong;Kamran Mahmood;Herbert Kim Lyerly;Xiaoning Jiang;
      Pages: 2084 - 2093
      Abstract: Objective: This paper aims to develop a miniaturized forward-looking ultrasound transducer for intracavitary tissue ablation, which can be used through an endoscopic device. The internal ultrasound (US) delivery is capable of directly interacting with the target tumor, resolving adverse issues of currently available US devices, such as unintended tissue damage and insufficient delivery of acoustic power. Methods: To transmit a high acoustic pressure from a small aperture (
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Signal Modeling and Simulation of Temporal Dispersion and Conduction Block
           in Motor Nerves
    • Authors: Eric Elzenheimer;Helmut Laufs;Wilhelm Schulte-Mattler;Gerhard Schmidt;
      Pages: 2094 - 2102
      Abstract: Objective: Electroneurography is a well-established diagnostic test for supporting the diagnosis of disorders of myelinated peripheral nerves. Neurophysiological quantities are automatically calculated and are used to determine the pathology of the nerve (axonal damage) or its sheath (myelin damage). Specific differential diagnostic criteria are derived from time-domain normative data, which result primarily from a computer simulation in the early 1990s based on animal data, namely rats. However, the rat signals studied differ significantly from those of humans because of anatomical differences. Methods: We present a model-based simulation of nerve conduction in healthy and pathological motor nerves. In contrast to earlier simulations, the present model is based on motor unit action potentials extracted from real human measurements facilitating the generation of realistic signals, starting from a conduction velocity distribution. In addition to the modeling of healthy nerves, we model a hereditary peripheral nerve disease as well as an acute and a chronic inflammatory demyelinating condition. Results: Quantitative signal differences based on standard variables in the time-domain are presented. The findings for the demyelinating conditions demonstrate amplitude reductions of 71% and 65% between the distal and proximal responses, which result from an increase in the variance of the nerve fiber conduction velocities. Conclusion: The simulation results closely match those of empirical measurements, indicating that the signal model captures relevant pathological mechanisms. An amplitude reduction of more than 50% in demyelinating conditions is in accordance with routine measurements and shows that temporal dispersion is quite well-modeled compared to previous simulation models. Significance: The simulation outcomes can serve as th- basis for an improved pathophysiological understanding of peripheral nerve disorders and should aid neurophysiologists to refine their diagnostic armamentarium resulting in a more precise differential diagnosis.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • A Dynamic Model of Brain Hemodynamics in Near-Infrared Spectroscopy
    • Authors: Rashid Ghorbani Afkhami;Frederick Rohan Walker;Saadallah Ramadan;Sarah Johnson;
      Pages: 2103 - 2109
      Abstract: Objective: Near-infrared spectroscopy (NiRS) is a noninvasive technology used in measuring oxy- and deoxy-hemoglobin changes, neural activation, functional connectivity, and vascular health assessment. In this paper, we propose a dynamic model of the NiRS signal to facilitate a better understanding of the underlying elements of this signal and as a means of validation for existing and new NiRS signal processing algorithms. Methods: The model incorporates arterial pulsations, its possible frequency drifts and the reflected waves, the hemodynamic response function (HRF), Mayer waves, respiratory waves and other very low-frequency components of the NiRS signal. Parameter selection and model fitting have been carried out using measurements from a NiRS database. Our database includes 25 participants each with 64 channels, covering all the scalp and therefore providing realistic measures of the varying parameters. Results: We compared synthetic resting-state and HRF-included model outputs with in vivo resting and task-included measurements. The results showed a significant equivalence of the in vivo and synthetic signals. Conclusion: The proposed signal model generates realistic NiRS signals. Significance: The model accepts simple physiological and physical parameters to produce realistic NiRS signals and will accelerate the growth of optical signal processing algorithms.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • Multi-Constrained Joint Non-Negative Matrix Factorization With Application
           to Imaging Genomic Study of Lung Metastasis in Soft Tissue Sarcomas
    • Authors: Jin Deng;Weiming Zeng;Wei Kong;Yuhu Shi;Xiaoyang Mou;Jian Guo;
      Pages: 2110 - 2118
      Abstract: Objective: The study of pathogenic mechanism at the genetic level by imaging genetics methods enables to effectively reveal the association of histopathology and genetics. However, there is a lack of effective and accurate tools to establish association models from macroscopic to microscopic. Methods: The multi-constrained joint non-negative matrix factorization (MCJNMF) was developed for simultaneous integration of genomic data and image data to identify common modules related to disease. Two types of data matrices were projected onto a common feature space, in which heterogeneous variables with large coefficients in the same projected direction form a common module. Meanwhile, the correlation between original data features was integrated by using regularization constraints to improve the biological relevance. Sparsity constraints and orthogonal constraints were performed on decomposition factors to minimize the redundancy between different bases and to reduce algorithm complexity. Results: This algorithm was successfully performed on the module identification of lung metastasis in soft tissue sarcomas (STSs) by integrating FDG-PET image and DNA methylation data features. Multilevel analysis on the top extracted modules revealed that these modules were closely related to the lung metastasis. Particularly, several genes with diagnostic potential for lung metastasis can be discovered from high score modules. Conclusion: This method not only can be applied for the accurate identification of patterns related to pathogenic mechanism of diseases, but also has a significant implication for discovering protein biomarkers. Significance: This method provides avenues for further studies of identifying complex association patterns of diseases according to different types of biological data.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
  • A Clinical Prototype Transrectal Diffuse Optical Tomography (TRDOT) System
           for In vivo Monitoring of Photothermal Therapy (PTT) of Focal Prostate
           Cancer
    • Authors: Jie He;Celina L. Li;Brian C. Wilson;Carl J. Fisher;Sangeet Ghai;Robert A. Weersink;
      Pages: 2119 - 2129
      Abstract: We describe the rationale, design, fabrication and performance of a clinical transrectal diffuse optical tomography (TRDOT) system for in vivo monitoring of photothermal therapy (PTT) of localized prostate cancer. The system comprises a 32-channel fiberoptic-based, MRI-compatible transrectal probe connected to a computer-controlled instrument that includes laser diode sources, an optical fiber switch and photomultiplier tube detectors. Performance tests were performed in tissue-simulating phantoms and in ex vivo muscle tissue during PTT treatment. The safety and technical feasibility of in vivo transrectal use were tested in a canine prostate model and in a first-in-human study in a patient before PTT treatment. Limitations of the system are discussed, as well as further developments to translate it into planned clinical trials for monitoring the photocoagulation boundary in the prostate during PTT.
      PubDate: July 2020
      Issue No: Vol. 67, No. 7 (2020)
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 3.236.97.49
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-