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  Subjects -> COMPUTER SCIENCE (Total: 2072 journals)
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COMPUTER SCIENCE (1202 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 20)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 28)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 14)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 9)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 15)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 6)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 5)
ACM Transactions on Economics and Computation     Hybrid Journal   (Followers: 1)
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 31)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 28)
Advanced Science Letters     Full-text available via subscription   (Followers: 10)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 4)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Computer Science : an International Journal     Open Access   (Followers: 14)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 54)
Advances in Engineering Software     Hybrid Journal   (Followers: 28)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 14)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Human-Computer Interaction     Open Access   (Followers: 20)
Advances in Materials Science     Open Access   (Followers: 14)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 49)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 6)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 9)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal  
Air, Soil & Water Research     Open Access   (Followers: 12)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 5)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 12)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 3)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 8)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 12)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 10)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 144)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 8)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal   (Followers: 1)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 5)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 12)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Big Data and Cognitive Computing     Open Access   (Followers: 2)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 304)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 21)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 37)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 49)
British Journal of Educational Technology     Hybrid Journal   (Followers: 143)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 15)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 22)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 2)
Communications in Information Science and Management Engineering     Open Access   (Followers: 4)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 51)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 17)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 30)
Computer     Full-text available via subscription   (Followers: 98)
Computer Aided Surgery     Open Access   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 16)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 24)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)

        1 2 3 4 5 6 7 | Last

Journal Cover
Biomedical Engineering, IEEE Transactions on
Journal Prestige (SJR): 1.267
Citation Impact (citeScore): 5
Number of Followers: 37  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9294
Published by IEEE Homepage  [191 journals]
  • Frontcover
    • Abstract: Presents the front cover for this issue of the publication.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • 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: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • IEEE Transactions on Biomedical Engineering (T-BME)
    • PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • 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: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Monitoring Acute Stroke in Mouse Model Using Laser Speckle Imaging-Guided
           Visible-Light Optical Coherence Tomography
    • Authors: Qi Liu;Siyu Chen;Brian Soetikno;Wenzhong Liu;Shanbao Tong;Hao F. Zhang;
      Pages: 2136 - 2142
      Abstract: Objective: Monitoring hemodynamic and vascular changes in the acute stages of mouse stroke models is invaluable in studying ischemic stroke pathophysiology. However, there lacks a tool to simultaneously and dynamically investigate these changes. Methods: We integrated laser speckle imaging (LSI) and visible-light optical coherence tomography (Vis-OCT) to reveal dynamic vascular responses in acute stages in the distal middle cerebral artery occlusion (dMCAO) model in rodents. LSI provides full-field, real-time imaging to guide Vis-OCT imaging and monitor the dynamic cerebral blood flow (CBF). Vis-OCT offers depth-resolved angiography and oxygen saturation (sO2) measurements. Results: Our results showed detailed CBF and vasculature changes before, during, and after dMCAO. After dMCAO, we observed insignificant sO2 variation in arteries and arterioles and location–dependent sO2 drop in veins and venules. We observed that higher branch-order veins had larger drops in sO2 at the reperfusion stage after dMCAO. Conclusion: This work suggests that integrated LSI and Vis-OCT is a promising tool for investigating ischemic stroke in mouse models. Significance: For the first time, LSI and Vis-OCT are integrated to investigate ischemic strokes in rodent models.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Methods for Improved Discrimination Between Ventricular Fibrillation and
    • Authors: Yaqub Alwan;Zoran Cvetković;Michael J. Curtis;
      Pages: 2143 - 2151
      Abstract: Differentiating between ventricular tachycardia and ventricular fibrillation in clinical and preclinical research is based on subjective definitions that have yet to be validated using objective criteria. This is partly due to shortcomings in the discrimination ability of current objective approaches, typified by the algorithms that perform cardiac rhythm classification using low-dimensional feature representations of electrocardiogram (ECG) signals. These identify ventricular tachyarrhythmias, but do not discriminate between ventricular tachycardia and ventricular fibrillation. In order to address this limitation, we have tested the utility of high-dimensional feature vectors, in particular, magnitude spectra and classifier ensembles that take into account local context information from ECG signals. Using these approaches, we categorized rhythms into three classes: ventricular tachycardia, ventricular fibrillation, and any other possible rhythm, defined here as “nonventricular rhythms.” The high-dimensional spectral features achieved a substantial improvement in the discrimination between ventricular tachycardia and ventricular fibrillation, but exhibited a decreased sensitivity to nonventricular rhythms. In order to deal with the reduced sensitivity for the detection of nonventricular rhythms, methods were elaborated for combining the strengths of different feature spaces, and this substantially improved the identification sensitivities of all three classes.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Modeling, Detecting, and Tracking Freezing of Gait in Parkinson Disease
           Using Inertial Sensors
    • Authors: G. V. Prateek;Isaac Skog;Marie E. McNeely;Ryan P. Duncan;Gammon M. Earhart;Arye Nehorai;
      Pages: 2152 - 2161
      Abstract: In this paper, we develop new methods to automatically detect the onset and duration of freezing of gait (FOG) in people with Parkinson disease (PD) in real time, using inertial sensors. We first build a physical model that describes the trembling motion during the FOG events. Then, we design a generalized likelihood ratio test framework to develop a two-stage detector for determining the zero-velocity and trembling events during gait. Thereafter, to filter out falsely detected FOG events, we develop a point-process filter that combines the output of the detectors with information about the speed of the foot, provided by a foot-mounted inertial navigation system. We computed the probability of FOG by using the point-process filter to determine the onset and duration of the FOG event. Finally, we validate the performance of the proposed system design using real data obtained from people with PD who performed a set of gait tasks. We compare our FOG detection results with an existing method that only uses accelerometer data. The results indicate that our method yields 81.03% accuracy in detecting FOG events and a threefold decrease in the false-alarm rate relative to the existing method.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Visual Limit-Push Training Alters Movement Variability
    • Authors: Eyad Hajissa;Amit Shah;James L. Patton;
      Pages: 2162 - 2167
      Abstract: In both movement training and neurorehabilitation, there have been numerous examples of how average performance can be manipulated through practice using enhanced visual feedback. Objective: Rather than just influencing the mean, our objective was to use a novel feedback technique called limit-push to influence the trial-to-trial variability of motion by distorting vision. Method : Limit-push was previously done using robotic forces; the present study employed only visual distortions that imitated the limit-push approach. Results: Like the robotic force treatment, our results showed how subjects significantly shifted the distributions of their motions. This effect was even greater than that of the original limit-push experiment that used robotic forces. Significance : Such visual distortion interventions do not require a robot for enhanced training. Conclusion: The visual limit-push technique appears to be able to selectively alter both the central tendency and variability in performance training applications.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Multiclass Classification of Word Imagination Speech With Hybrid
           Connectivity Features
    • Authors: Muhammad Naveed Iqbal Qureshi;Beomjun Min;Hyeong-jun Park;Dongrae Cho;Woosu Choi;Boreom Lee;
      Pages: 2168 - 2177
      Abstract: Objective: In this study, electroencephalography data of imagined words were classified using four different feature extraction approaches. Eight subjects were recruited for the recording of imagination with five different words, namely; “go,” “back,” “left,” “right,” and “stop.” Methods: One hundred trials for each word were recorded for both imagination and perception, although this study utilized only imagination data. Two different connectivity methods were applied, namely; a covariance-based and a maximum linear cross-correlation-based connectivity measure. These connectivity measures were further computed to extract the phase-only data as an additional method of feature extraction. In addition, four different channel selections were used. The final connectivity matrix from each of the four methods was vectorized and used as the feature vector for the classifier. To classify EEG data, a sigmoid activation function-based linear extreme learning machine was used. Result and Significance: We achieved a maximum classification rate of 40.30% (p $
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Magnet-Assisted Hydraulic Bougienage for Correction of Long-Gap Esophageal
    • Authors: Minkyun Noh;David P. Mooney;David L. Trumper;
      Pages: 2178 - 2189
      Abstract: Objective: An infant born with long-gap esophageal atresia has its esophagus separated into two pouches, and typically undergoes multiple open-chest surgeries for esophageal reconstruction. In this paper, we study a possible approach for less invasive correction of long-gap esophageal atresia. Methods: Our technique utilizes a magnet-tipped catheter with a piston on the end to push the esophageal pouch from the inside. The attractive magnetic force helps the catheter stretch the esophageal pouches, while the hydraulic piston prevents the magnet from applying too large force. The piston also enables estimation of the esophageal tension based on the hydraulic pressure measurement. Results: We have built a prototype system and performed bench-level tests on an esophageal mock-up. A hydraulic dither is applied to the piston to average out seal friction, thereby improving the tension estimation performance. Conclusion: The bench-level tests demonstrate that the prototype bougienage system gives a reliable low-frequency estimate of the esophageal tension in real-time, and also enables longitudinal bougienage by a desired amount of load, e.g., 2N, for various gap sizes. Significance : This study provides a foundation for the next step of designing a system for use on actual patients.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Characterization of Nonlinearity and Dispersion in Tissue Impedance During
           High-Frequency Electroporation
    • Authors: Suyashree Bhonsle;Melvin F. Lorenzo;Ahmad Safaai-Jazi;Rafael V. Davalos;
      Pages: 2190 - 2201
      Abstract: Objective: The use of high-voltage, high-frequency bipolar pulses (HFBPs) is an emerging electroporation-based therapy for the treatment of solid tumors. In this study, we quantify the extent of nonlinearity and dispersion during the HFBP treatment. Methods: We utilize flat-plate electrodes to capture the impedance of the porcine liver tissue during the delivery of a burst of HFBPs of widths 1 and 2  $mu$s at different pulse amplitudes. Next, we fit the impedance data to a frequency-dependent parallel RC network to determine the conductivity and permittivity of the tissue as a function of frequency, for different applied electric fields. Finally, we present a simple model to approximate the field distribution in the tissue using the conductivity function at a frequency that could minimize the errors due to approximation with a nondispersive model. Results: The conductivity/permittivity of the tissue was plotted as a function of frequency for different electric fields. It was found that the extent of dispersion reduces with higher applied electric field magnitudes. Conclusion: This is the first study to quantify dispersion and nonlinearity in the tissue during the HFBP treatment. The data have been used to predict the field distribution in a numerical model of the liver tissue utilizing two needle electrodes. Significance : The data and technique developed in this study to monitor the electrical properties of tissue during treatment can be used to generate treatment-planning models for future high-frequency electroporation therapies as well as provide insights regarding treatment effect.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Effects of Ablation (Radio Frequency, Cryo, Microwave) on Physiologic
           Properties of the Human Vastus Lateralis
    • Authors: Ashish Singal;Lars M. Mattison;Charles L. Soule;Paul Anthony Iaizzo;
      Pages: 2202 - 2209
      Abstract: Objective: Ablative treatments can sometimes cause collateral injury to surrounding muscular tissue, with important clinical implications. In this study, we investigated the changes in muscle physiology of the human vastus lateralis when exposed to three different ablation modalities: radiofrequency ablation, cryoablation, and microwave ablation. Methods: We obtained fresh vastus lateralis tissue biopsy specimens from nine patients (age range: 29–73 years) who were undergoing in vitro contracture testing for malignant hyperthermia. Using leftover waste tissue, we prepared 46 muscle bundles that were utilized in tissue baths before and after ablation. Results: After ablation with all the three modalities, we noted dose-dependent sustained reductions in peak force (strength of contraction), as well as transient increases in baseline force (resting muscle tension). But, over the subsequent 3-h recovery period, peak force improved and the baseline force consistently recovered to below its preablation levels. Conclusion: The novel in vitro methodologies we developed to investigate changes in muscle physiology after ablation can be used to study a spectrum of ablation modalities and also to make head-to-head comparisons of different ablation modalities. Significance: As the role of ablative treatments continues to expand, our findings provide unique insights into the resulting changes in muscle physiology. These insights could enhance the safety and efficacy of ablations and help individuals design and develop novel medical devices.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Sparse Ultrasound Image Reconstruction From a Shape-Sensing Single-Element
           Forward-Looking Catheter
    • Authors: Jovana Janjic;Frits Mastik;Merel D. Leistikow;Johan G. Bosch;Geert Springeling;Antonius F. W. van der Steen;Gijs van Soest;
      Pages: 2210 - 2218
      Abstract: Objective: Minimally invasive procedures, such as intravascular and intracardiac interventions, may benefit from guidance with forward-looking (FL) ultrasound. In this work, we investigate FL ultrasound imaging using a single-element transducer integrated in a steerable catheter, together with an optical shape sensing (OSS) system. Methods: We tested the feasibility of the proposed device by imaging the surface of a tissue-mimicking (TM) phantom and an ex vivo human carotid plaque. While manually steering the catheter tip, ultrasound A-lines are acquired at 60 Hz together with the catheter shape from the OSS system, resulting in a two-dimensional sparse and irregularly sampled data set. We implemented an adaptive Normalized Convolution (NC) algorithm to interpolate the sparse data set by applying an anisotropic Gaussian kernel that is rotated according to the local direction of the catheter scanning pattern. To choose the Gaussian widths tangential ( ${sigma _t}$) and normal ( ${sigma _n}$) to the scanning pattern, an exhaustive search was implemented based on RMSE computation on simulated data. Results: Simulations showed that the sparse data set contains only 5% of the original information. The chosen widths, ${sigma _n} = text{250};mu {textrm{m}}$ and ${sigma _t} = text{100};mu{textrm{m}}$, are used to successfully reconstruct the surface of the phantom with a contrast ratio of 0.9. The same kernel is applied successfully to the carotid plaque data. Conclusion: The proposed approach enables FL imaging with a single ultrasound element, mounted o- a steerable device. Significance: This principle may find application in a variety of image-guided interventions, such as chronic total occlusion (CTO) recanalization.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Accelerated Cardiac Diffusion Tensor Imaging Using Joint Low-Rank and
           Sparsity Constraints
    • Authors: Sen Ma;Christopher T. Nguyen;Anthony G. Christodoulou;Daniel Luthringer;Jon Kobashigawa;Sang-Eun Lee;Hyuk-Jae Chang;Debiao Li;
      Pages: 2219 - 2230
      Abstract: Objective: The purpose of this paper is to accelerate cardiac diffusion tensor imaging (CDTI) by integrating low-rankness and compressed sensing. Methods: Diffusion-weighted images exhibit both transform sparsity and low-rankness. These properties can jointly be exploited to accelerate CDTI, especially when a phase map is applied to correct for the phase inconsistency across diffusion directions, thereby enhancing low-rankness. The proposed method is evaluated both ex vivo and in vivo, and is compared to methods using either a low-rank or sparsity constraint alone. Results: Compared to using a low-rank or sparsity constraint alone, the proposed method preserves more accurate helix angle features, the transmural continuum across the myocardium wall, and mean diffusivity at higher acceleration, while yielding significantly lower bias and higher intraclass correlation coefficient. Conclusion: Low-rankness and compressed sensing together facilitate acceleration for both ex vivo and in vivo CDTI, improving reconstruction accuracy compared to employing either constraint alone. Significance: Compared to previous methods for accelerating CDTI, the proposed method has the potential to reach higher acceleration while preserving myofiber architecture features, which may allow more spatial coverage, higher spatial resolution, and shorter temporal footprint in the future.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Closed-Loop Control for Precision Antimicrobial Delivery: An In Silico
    • Authors: Pau Herrero;Timothy M. Rawson;Akash Philip;Luke Stephen Prockter Moore;Alison Helen Holmes;Pantelis Georgiou;
      Pages: 2231 - 2236
      Abstract: Objective: Inappropriate dosing of patients with antibiotics is a driver of antimicrobial resistance, toxicity, and poor outcomes of therapy. In this paper, we investigate, in silico, the hypothesis that the use of a closed-loop control system could improve the attainment of pharmacokinetic–pharmacodynamic targets for antimicrobial therapy, where wide variations in target attainment have been reported. This includes patients in critical care, patients with renal disease, and patients with obesity. Methods: The presented in silico study focuses on vancomycin delivery, a first line therapy for Methicillin-resistant Staphylococcus aureus (MRSA) that has serious side effects, including nephrotoxicity. For this purpose, an in silico platform for the simulation of pharmacokinetics of vancomycin agents was developed including 24 virtual noncritically ill-adult subjects obtained from routinely collected data from two prospective audits of vancomycin therapy. Intraday variability on renal clearance, sensor error, and infusion constraints were taken into account. Proportional integral derivative (PID) controller was chosen because of its simplicity of implementation and satisfactory performance. Results: Even though significant intraday variability and sensor error were considered in the simulations, by assuming a minimum inhibitory concentration of 1 mg/l for MRSA, the proposed controller was able to reach the well-established therapeutic target of 24-h area under curve to minimum inhibitory concentration ratio equal to 400 $text{mg} cdot text{h}text{/}text{l}$ for all the studied subjects, while staying significantly below toxic levels. Conclusion: A PID controller has the potential to precisely deliver a vancomycin therapy in a noncritically ill-adult populatio-. Significance: Closed-loop control for precision Vancomycin delivery can potentially reduce toxicity and poor therapeutic outcomes, as well as reduce antimicrobial resistance.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Automated In Vivo Sub-Hertz Analysis of Viscoelasticity (SAVE) for
           Evaluation of Breast Lesions
    • Authors: Mahdi Bayat;Alireza Nabavizadeh;Viksit Kumar;Adriana Gregory;Michael Insana;Azra Alizad;Mostafa Fatemi;
      Pages: 2237 - 2247
      Abstract: We present an automated method for acquiring images and contrast parameters based on mechanical properties of breast lesions and surrounding tissue at load frequencies less than 1 Hz. The method called sub-Hertz analysis of viscoelasticity (SAVE) uses a compression device integrated with ultrasound imaging to perform in vivo ramp-and-hold uniaxial creep-like test on human breast in vivo. It models the internal deformations of tissues under constant surface stress as a linear viscoelastic response. We first discuss different aspects of our unique measurement approach and the expected variability of the viscoelastic parameters estimated based on a simplified one-dimensional reconstruction model. Finite-element numerical analysis is used to justify the advantages of using imaging contrast over viscoelasticity values. We then present the results of SAVE applied to a group of patients with breast masses undergoing biopsy.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Robust Methods for Automated Selection of Cardiac Signals After Blind
           Source Separation
    • Authors: Daniel Wedekind;Denis Kleyko;Evgeny Osipov;Hagen Malberg;Sebastian Zaunseder;Urban Wiklund;
      Pages: 2248 - 2258
      Abstract: Objective: Novel minimum-contact vital signs monitoring techniques like textile or capacitive electrocardiogram (ECG) provide new opportunities for health monitoring. These techniques are sensitive to artifacts and require handling of unstable signal quality. Spatio-temporal blind source separation (BSS) is capable of processing suchlike multichannel signals. However, BSS's permutation indeterminacy requires the selection of the cardiac signal (i.e., the component resembling the electric cardiac activity) after its separation from artifacts. This study evaluates different concepts for solving permutation indeterminacy. Methods: Novel automated component selection routines based on heartbeat detections are compared with standard concepts, as using higher order moments or frequency-domain features, for solving permutation indeterminacy in spatio-temporal BSS. BSS was applied to a textile and a capacitive ECG dataset of healthy subjects performing a motion protocol, and to the MIT-BIH Arrhythmia Database. The performance of the subsequent component selection was evaluated by means of the heartbeat detection accuracy (ACC) using an automatically selected single component. Results: The proposed heartbeat-detection-based selection routines significantly outperformed the standard selectors based on Skewness, Kurtosis, and frequency-domain features, especially for datasets containing motion artifacts. For arrhythmia data, beat analysis by sparse coding outperformed simple periodicity tests of the detected heartbeats. Conclusion: Component selection routines based on heartbeat detections are capable of reliably selecting cardiac signals after spatio-temporal BSS in case of severe motion artifacts and arrhythmia. Significance : The availability of robust cardiac component selectors for solving permutation indeterminacy facilitates the usage of spatio-temporal BSS to extra-t cardiac signals in artifact-sensitive minimum-contact vital signs monitoring techniques.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • An Adjustable-Length Dipole Using Forced-Current Excitation for 7T MR
    • Authors: Jiaming Cui;Ivan E. Dimitrov;Sergey Cheshkov;Minyu Gu;Craig R. Malloy;Steven M. Wright;
      Pages: 2259 - 2266
      Abstract: Ultrahigh field imaging of the body and the spine is challenging due to the large field-of-view (FOV) required. It is especially difficult for RF transmission due to its requirement on both the length and the depth of the ${rm{B}}_{1}^{{rm + }}$ field. One solution is to use a long dipole to provide continuous current distribution. The drawback is the natural falloff of the ${rm{B}}_{1}$ field toward the ends of the dipole, therefore the ${rm{B}}_{1}^{{rm + }}$ per unit square root of maximum specific absorption rate ${rm{(B}}_{1}^{{rm + }}{rm{/ surd SAR}}_{{rm{max}}})$ performance is particularly poor toward the end of the dipole. In this study, a segmented element design using forced-current excitation and a switching circuit is presented. The design provides long FOV when desired and allows flexible FOV switching and power distribution without additional power amplifiers. Different element types and arrangements were explored and a segmented dipole design was chosen as the best design. The segmented dipole was implemented and tested on the bench and with a phantom on a 7T whole body scanner. The switchable mode dipole enabled a large FOV in the long mode and improved ${rm{B}}_{1}^{{rm + }}{rm{/ surd SAR}}_{{rm{max}}}$ efficiency in a smaller FOV in the short mode.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Representing Medical Images With Encoded Local Projections
    • Authors: Hamid R. Tizhoosh;Morteza Babaie;
      Pages: 2267 - 2277
      Abstract: This paper introduces the “encoded local projections” (ELP) as a new dense-sampling image descriptor for search and classification problems. The gradient changes of multiple projections in local windows of gray-level images are encoded to build a histogram that captures spatial projection patterns. Using projections is a conventional technique in both medical imaging and computer vision. Furthermore, powerful dense-sampling methods, such as local binary patterns and the histogram of oriented gradients, are widely used for image classification and recognition. Inspired by many achievements of such existing descriptors, we explore the design of a new class of histogram-based descriptors with particular applications in medical imaging. We experiment with three public datasets (IRMA, Kimia Path24, and CT Emphysema) to comparatively evaluate the performance of ELP histograms. In light of the tremendous success of deep architectures, we also compare the results with deep features generated by pretrained networks. The results are quite encouraging as the ELP descriptor can surpass both conventional and deep descriptors in performance in several experimental settings.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Model-Based Analysis of Electrode Placement and Pulse Amplitude for
           Hippocampal Stimulation
    • Authors: Clayton S. Bingham;Kyle Loizos;Gene J. Yu;Andrew Gilbert;Jean-Marie C. Bouteiller;Dong Song;Gianluca Lazzi;Theodore W. Berger;
      Pages: 2278 - 2289
      Abstract: Objective: The ideal form of a neural-interfacing device is highly dependent upon the anatomy of the region with which it is meant to interface. Multiple-electrode arrays provide a system that can be adapted to various neural geometries. Computational models of stimulating systems have proven useful for evaluating electrode placement and stimulation protocols, but have yet to be adequately adapted to the unique features of the hippocampus. Methods: As an approach to understanding potential memory restorative devices, an admittance method-NEURON model was constructed to predict the direct and synaptic response of a region of the rat dentate gyrus to electrical stimulation of the perforant path. Results: A validation of estimated local field potentials against experimental recordings is performed and results of a bilinear electrode placement and stimulation amplitude parameter search are presented. Conclusion: The parametric analysis presented herein suggests that stimulating electrodes placed between the lateral and medial perforant path, near the crest of the dentate gyrus, yield a larger relative population response to given stimuli. Significance: Beyond deepening understanding of the hippocampal tissue system, establishment of this model provides a method to evaluate candidate stimulating devices and protocols.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Automatic Early-Onset Free Flap Failure Detection for Implantable
           Biomedical Devices
    • Authors: Michael A. Rothfuss;Nicholas G. Franconi;Alexander Star;Murat Akcakaya;Michael L. Gimbel;Ervin Sejdić;
      Pages: 2290 - 2297
      Abstract: Objective: Up to 10% of free flap cases are compromised, and without prompt intervention, amputation and even death can occur. Hourly monitoring improves salvage rates, but the gold standard for monitoring requires experienced personnel to operate and suffers from high false-positive rates as high as 31% that result in costly and unnecessary surgeries. In this paper, we investigate free flap patency monitoring using automatic hardware-only classification systems that eliminate the need for experienced personnel. The expected flow ranges of the antegrade and retrograde veins for breast reconstruction are studied using a syringe pump to create the laminar flow seen in veins. Methods: Feature data extracted from the Doppler blood flow signals are analyzed for sensitivity, specificity, and false-positive rates. Hardware is built to perform the classification automatically in real-time and output a decision at the end of the observation period. Results: Experimental results using the hardware-only classifier for a 50 ms window size show high sensitivity (96.75%), specificity (90.20%), and low false-positive rate (9.803%). The experimental and theoretical classification results show close agreement. Conclusion: This work indicates that automatic hardware-only classifiers can eliminate the need for experienced personnel to monitor free flap patency. Significance: The hardware-only classification is amenable to a monolithic implementation and future studies should study a totally implantable wirelessly-powered blood flow classifier. The high classifier performance in a short window period indicates that duty-cycled powering can be used to extend the safe operational depth of an implant. This is particularly relevant for the difficult buried free flap applications.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Reducing the Computational Complexity of EEG Source Localization With
           Cortical Patch Decomposition and Optimal Electrode Selection
    • Authors: Seyede Mahya Safavi;Beth Lopour;Pai H. Chou;
      Pages: 2298 - 2310
      Abstract: Objective: Real-time implementation of EEG source localization can be employed in a broad area of applications such as clinical diagnosis of neurologic diseases and brain–computer interface. However, a power-efficient, low-complexity, and real-time implementation of EEG source localization is still challenging due to extensive iterations in the solutions. In this study, two techniques are introduced to reduce the computational burden of the subspace-based MUltiple SIgnal Classification (MUSIC) algorithm. Methods: To shrink the exhaustive search inherent in MUSIC, the cortex is parsed into cortical regions. A novel nomination procedure involving a dictionary learning step will pick a number of regions to be searched for the active sources. In addition, a new electrode selection algorithm based on the Cramer–Rao bound of the errors is introduced to pick the best set of an arbitrary number of electrodes out of the total. Results: The performance of the proposed techniques were evaluated using simulated EEG signal under variation of different parameters such as the number of nominated regions, the signal to noise ratio, and the number of electrodes. The proposed techniques can reduce the computational complexity by up to $90%$. Furthermore, the proposed techniques were tested on EEG data from an auditory oddball experiment. Conclusion: A good concordance was observed in the comparison of the topographies and the localization errors derived from the proposed technique and regular MUSIC. Significance: Such reduction can be exploited in the real-time, long-run, and mobile monitoring of cortical activity for clinical diagnosis and research purposes.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Closed-Loop Lumped Parameter Modeling of Hemodynamics During Cirrhogenesis
           in Rats
    • Authors: Chloe Audebert;Geert Peeters;Patrick Segers;Wim Laleman;Diethard Monbaliu;Hannelie Korf;Jonel Trebicka;Irene E. Vignon-Clementel;Charlotte Debbaut;
      Pages: 2311 - 2322
      Abstract: Objective: Cirrhosis is the common end stage of any given chronic liver disease, developing after persistent destruction and regeneration of parenchymal liver cells. The associated architectural distortion increases the intrahepatic vascular resistance, leading to portal hypertension and systemic circulatory disorders. This study investigates the impact of the changing vascular resistances on the hepatic and global circulation hemodynamics during cirrhogenesis. Methods: Cirrhogenesis was revisited using the thioacetamide rat model (N = 20). Rats were sacrificed at weeks 0, 6, 12, and 18. For each time-point, three-dimensional vascular geometries were created by combining hepatic vascular corrosion casting with μCT imaging. Morphological quantification of the trees branching topology provided the input for a lobe-specific lumped parameter model of the liver that was coupled to a closed-loop model of the entire circulation of the rat. Hemodynamics was simulated in physiological and pathological circumstances. Results: The simulations showed the effect of the liver vascular resistances (driven by the hepatic venous resistance increase) on liver hemodynamics with portal hypertension observed after 12 weeks. The closed-loop model was further adapted to account for systemic circulatory compensation mechanisms and disorders frequently observed in cirrhosis and simulated their impact on the hepatic, systemic, and pulmonary hemodynamics. Conclusion: The simulations explain how vascular changes due to cirrhosis severely disrupt both hepatic and global hemodynamics. Significance: This study is a priori the first to model the rat's entire blood circulation during cirrhogenesis. Since it is able to simulate cirrhosis main characteristics, the model may be translated to humans for the assessment of liver-interventions.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Topological Properties of the Structural Brain Network in Autism via
           ϵ-Neighbor Method
    • Authors: Min-Hee Lee;Dong Youn Kim;Moo K. Chung;Andrew L. Alexander;Richard J. Davidson;
      Pages: 2323 - 2333
      Abstract: Objective: Topological characteristics of the brain can be analyzed using structural brain networks constructed by diffusion tensor imaging (DTI). When a brain network is constructed by the existing parcellation method, the structure of the network changes depending on the scale of parcellation and arbitrary thresholding. To overcome these issues, we propose to construct brain networks using the improved $varepsilon $-neighbor construction, which is a parcellation free network construction technique. Methods: We acquired DTI from 14 control subjects and 15 subjects with autism. We examined the differences in topological properties of the brain networks constructed using the proposed method and the existing parcellation between the two groups. Results: As the number of nodes increased, the connectedness of the network decreased in the parcellation method. However, for brain networks constructed using the proposed method, connectedness remained at a high level even with an increase in the number of nodes. We found significant differences in several topological properties of brain networks constructed using the proposed method, whereas topological properties were not significantly different for the parcellation method. Conclusion: The brain networks constructed using the proposed method are considered as more realistic than a parcellation method with respect to the stability of connectedness. We found that subjects with autism showed the abnormal characteristics in the brain networks. These results demonstrate that the proposed method may provide new insights to analysis in the structural brain network. Significance: We proposed the novel brain network construction method to overcome the shortcoming in the existing parcellation method.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Automatic Identification of Reentry Mechanisms and Critical Sites During
           Atrial Tachycardia by Analyzing Areas of Activity
    • Authors: Tobias G. Oesterlein;Axel Loewe;Gustavo Lenis;Armin Luik;Claus Schmitt;Olaf Dössel;
      Pages: 2334 - 2344
      Abstract: Objective: Atrial tachycardia (AT) still poses a major challenge in catheter ablation. Although state-of-the-art electroanatomical mapping systems allow to acquire several thousand intracardiac electrograms (EGMs), algorithms for diagnostic analysis are mainly limited to the amplitude of the signal (voltage map) and the local activation time (LAT map). We applied spatio-temporal analysis of EGM activity to generate maps indicating reentries and diastolic potentials, thus identifying and localizing the driving mechanism of AT. Methods: First, the time course of active surface area ASA is determined during one basic cycle length (BCL). The chamber cycle length coverage cCLC reflects the relative duration within one BCL for which activity was present in each individual atrium. A local cycle length coverage lCLC is computed for circular subareas with 20 mm diameter. The simultaneous active surface area sASA is determined to indicate the spatial extent of depolarizing tissue. Results: Combined analysis of these spatial scales allowed to correctly identify and localize the driving mechanism: cCLC values of 100% were indicative for atria harbouring a reentrant driver. lCLC could detect micro reentries within an area of 1.65 $pm$ 1.28 cm $^2$ in simulated data and differentiate them against focal sources. Middiastolic potentials, being potential targets for catheter ablation, were identified as areas showing confined activity based on sASA values. Conc-usion: The concept of spatio-temporal activity analysis proved successful and correctly indicated the tachycardia mechanism in 20 simulated AT scenarios and three clinical data sets. Significance: Automatic interpretation of intracardiac mapping data could help to improve the treatment strategy in complex cases of AT.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Mortality Prediction in Severe Congestive Heart Failure Patients With
           Multifractal Point-Process Modeling of Heartbeat Dynamics
    • Authors: Gaetano Valenza;Herwig Wendt;Ken Kiyono;Junichro Hayano;Eiichi Watanabe;Yoshiharu Yamamoto;Patrice Abry;Riccardo Barbieri;
      Pages: 2345 - 2354
      Abstract: Background: Multifractal analysis of human heartbeat dynamics has been demonstrated to provide promising markers of congestive heart failure (CHF). Yet, it crucially builds on the interpolation of RR interval series which has been generically performed with limited links to CHF pathophysiology. Objective: We devise a novel methodology estimating multifractal autonomic dynamics from heartbeat-derived series defined in the continuous time. We hypothesize that markers estimated from our novel framework are also effective for mortality prediction in severe CHF. Methods: We merge multifractal analysis within a methodological framework based on inhomogeneous point process models of heartbeat dynamics. Specifically, wavelet coefficients and wavelet leaders are computed over measures extracted from instantaneous statistics of probability density functions characterizing and predicting the time until the next heartbeat event occurs. The proposed approach is tested on data from 94 CHF patients aiming at predicting survivor and nonsurvivor individuals as determined after a four years follow up. Results and Discussion: Instantaneous markers of vagal and sympatho-vagal dynamics display power-law scaling for a large range of scales, from $simeq 0.5$ to $simeq 100$  s. Using standard support vector machine algorithms, the proposed inhomogeneous point-process representation-based multifractal analysis achieved the best CHF mortality prediction accuracy of 79.11% (sensitivity 90.48%, specificity 67.74%). Conclusion: Our results suggest that heartbeat scaling and multifractal properties in CHF patients are not generated at the sinus-node level, but rather by the i-trinsic action of vagal short-term control and of sympatho-vagal fluctuations associated with circadian cardiovascular control especially within the very low frequency band. These markers might provide critical information in devising a clinical tool for individualized prediction of survivor and nonsurvivor CHF patients.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Viscosity Prediction in a Physiologically Controlled Ventricular Assist
    • Authors: Anastasios Petrou;Menelaos Kanakis;Stefan Boës;Panagiotis Pergantis;Mirko Meboldt;Marianne Schmid Daners;
      Pages: 2355 - 2364
      Abstract: Objective: We present a novel machine learning model to accurately predict the blood-analog viscosity during support of a pathological circulation with a rotary ventricular assist device (VAD). The aim is the continuous monitoring of the hematocrit (HCT) of VAD patients with the benefit of a more reliable pump flow estimation and a possible early detection of adverse events, such as bleeding or pump thrombosis. Methods: A large dataset was generated with a blood pump connected to a hybrid mock circulation by varying the pump speed, the physiological requirements of the modeled circulation, and the viscosity of the blood-analog. The inlet pressure and the intrinsic signals of the pump were considered as inputs for the model. Gaussian process yielded models with the best performance, which were then combined using a variant of stacked generalization to derive the final model. The final model was evaluated with unseen testing data from the dataset created. Results: For these data, the model yielded a mean absolute deviation of 1.81% from the true HCT, while it proved to correctly predict the direction of the HCT change. It showed to be independent of the set speed and of the condition of the simulated cardiovascular circulation. Conclusion: The accuracy of the prediction model allows an improvement of the quality of flow estimators and the detection of adverse events at an early stage. The evaluation of this approach with blood is suggested for further validation. Significance: Its clinical application could provide the clinicians with reliable and important hemodynamic information of the patient and, thus, enhance patient monitoring and supervision.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
  • Electromagnetic Brain Source Imaging by Means of a Robust Minimum Variance
    • Authors: Seyed Amir Hossein Hosseini;Abbas Sohrabpour;Mehmet Akçakaya;Bin He;
      Pages: 2365 - 2374
      Abstract: Objective: Adaptive beamformer methods that have been extensively used for functional brain imaging using EEG/MEG (magnetoencephalography) signals are sensitive to model mismatches. We propose a robust minimum variance beamformer (RMVB) technique, which explicitly incorporates the uncertainty of the lead field matrix into the estimation of spatial-filter weights that are subsequently used to perform the imaging. Methods: The uncertainty of the lead field is modeled by ellipsoids in the RMVB method; these hyperellipsoids (ellipsoids in higher dimensions) define regions of uncertainty for a given nominal lead field vector. These ellipsoids are estimated empirically by sampling lead field vectors surrounding each point of the source space, or more generally by building several forward models for the source space. Once these uncertainty regions (ellipsoids) are estimated, they are used to perform the source-imaging task. Computer simulations are conducted to evaluate the performance of the proposed RMVB technique. Results: Our results show that robust beamformers can outperform conventional beamformers in terms of localization error, recovering source dynamics, and estimation of the underlying source extents when uncertainty in the lead field matrix is properly determined and modeled. Conclusion: The RMVB can be substituted for conventional beamformers, especially in applications where source imaging is performed off-line, and computational speed and complexity are not of major concern. Significance: A high-quality source imaging can be utilized in various applications, such as determining the epileptogenic zone in medically intractable epilepsy patients or estimating the time course of activity, which is a required step for computing the functional connectivity of brain networks.
      PubDate: Oct. 2018
      Issue No: Vol. 65, No. 10 (2018)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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