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ENGINEERING (1195 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 7)
3D Research     Hybrid Journal   (Followers: 19)
AAPG Bulletin     Full-text available via subscription   (Followers: 5)
AASRI Procedia     Open Access   (Followers: 15)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
ACS Nano     Full-text available via subscription   (Followers: 216)
Acta Geotechnica     Hybrid Journal   (Followers: 6)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 1)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 7)
Adaptive Behavior     Hybrid Journal   (Followers: 10)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 4)
Advanced Science     Open Access   (Followers: 5)
Advanced Science Focus     Free   (Followers: 3)
Advanced Science Letters     Full-text available via subscription   (Followers: 5)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 6)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 18)
Advances in Artificial Neural Systems     Open Access   (Followers: 3)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Engineering Software     Hybrid Journal   (Followers: 25)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 14)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 9)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 18)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 28)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in OptoElectronics     Open Access   (Followers: 5)
Advances in Physics Theories and Applications     Open Access   (Followers: 13)
Advances in Polymer Science     Hybrid Journal   (Followers: 40)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 35)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 1)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 4)
AIChE Journal     Hybrid Journal   (Followers: 29)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access  
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 28)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 11)
American Journal of Engineering Education     Open Access   (Followers: 9)
American Journal of Environmental Engineering     Open Access   (Followers: 16)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
Analele Universitatii Ovidius Constanta - Seria Chimie     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Regional Science     Hybrid Journal   (Followers: 7)
Annals of Science     Hybrid Journal   (Followers: 7)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 5)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 6)
Applied Clay Science     Hybrid Journal   (Followers: 4)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 3)
Applied Nanoscience     Open Access   (Followers: 7)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 4)
Applied Sciences     Open Access   (Followers: 3)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 8)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ASEE Prism     Full-text available via subscription   (Followers: 2)
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 1)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 7)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Current Engineering & Maths     Open Access  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 7)
Avances en Ciencias e Ingeniería     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 3)
Batteries     Open Access   (Followers: 3)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 23)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 3)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 3)
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Biofuels Engineering     Open Access  
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 9)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 16)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 31)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 8)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomedizinische Technik - Biomedical Engineering     Hybrid Journal  
Biomicrofluidics     Open Access   (Followers: 4)
BioNanoMaterials     Hybrid Journal   (Followers: 1)
Biotechnology Progress     Hybrid Journal   (Followers: 39)
Boletin Cientifico Tecnico INIMET     Open Access  
Botswana Journal of Technology     Full-text available via subscription  
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 14)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 3)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Full-text available via subscription   (Followers: 13)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 40)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 7)
Case Studies in Thermal Engineering     Open Access   (Followers: 4)
Catalysis Communications     Hybrid Journal   (Followers: 6)
Catalysis Letters     Hybrid Journal   (Followers: 2)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 8)
Catalysis Science and Technology     Free   (Followers: 6)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 5)
CEAS Space Journal     Hybrid Journal  
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal   (Followers: 1)
CFD Letters     Open Access   (Followers: 6)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencias Holguin     Open Access   (Followers: 1)
CienciaUAT     Open Access  
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Full-text available via subscription   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Full-text available via subscription   (Followers: 14)
City, Culture and Society     Hybrid Journal   (Followers: 21)
Clay Minerals     Full-text available via subscription   (Followers: 9)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
Coal Science and Technology     Full-text available via subscription   (Followers: 4)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 4)
Coatings     Open Access   (Followers: 2)
Cogent Engineering     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 1)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 13)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 23)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 252)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 177)
Composites Part B : Engineering     Hybrid Journal   (Followers: 223)
Composites Science and Technology     Hybrid Journal   (Followers: 164)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 12)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Science and Engineering     Open Access   (Followers: 17)
Computers & Geosciences     Hybrid Journal   (Followers: 25)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 5)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 4)
Computers and Geotechnics     Hybrid Journal   (Followers: 8)
Computing and Visualization in Science     Hybrid Journal   (Followers: 6)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 25)
Conciencia Tecnologica     Open Access  
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 6)
Control and Dynamic Systems     Full-text available via subscription   (Followers: 7)
Control Engineering Practice     Hybrid Journal   (Followers: 40)
Control Theory and Informatics     Open Access   (Followers: 7)
Corrosion Science     Hybrid Journal   (Followers: 24)
CT&F Ciencia, Tecnologia y Futuro     Open Access  
CTheory     Open Access  
Current Applied Physics     Full-text available via subscription   (Followers: 4)

        1 2 3 4 5 6 | Last

Journal Cover Biomedical Engineering, IEEE Transactions on
  [SJR: 1.201]   [H-I: 138]   [31 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0018-9294
   Published by IEEE Homepage  [191 journals]
  • IEEE Engineering in Medicine and Biology Society
    • PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • 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: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • IEEE Transactions on Biomedical Engineering Handling Editors
    • PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • A Feasibility Study of Nonlinear Spectroscopic Measurement of Magnetic
           Nanoparticles Targeted to Cancer Cells
    • Authors: Bradley W. Ficko;Christian NDong;Paolo Giacometti;Karl E. Griswold;Solomon G. Diamond;
      Pages: 972 - 979
      Abstract: Objective: Magnetic nanoparticles (MNPs) are an emerging platform for targeted diagnostics in cancer. An important component needed for translation of MNPs is the detection and quantification of targeted MNPs bound to tumor cells. Method: This study explores the feasibility of a multifrequency nonlinear magnetic spectroscopic method that uses excitation and pickup coils and is capable of discriminating between quantities of bound and unbound MNPs in 0.5 ml samples of KB and Igrov human cancer cell lines. The method is tested over a range of five concentrations of MNPs from 0 to 80 μg/ml and five concentrations of cells from 50 to 400 000 count per ml. Results: A linear model applied to the magnetic spectroscopy data was able to simultaneously measure bound and unbound MNPs with agreement between the model-fit and lab assay measurements (p < 0.001). The detectable iron of the presented method to bound and unbound MNPs was < 2 μg in a 0.5 ml sample. The linear model parameters used to determine the quantities of bound and unbound nanoparticles in KB cells were also used to measure the bound and unbound MNP in the Igrov cell line and vice versa. Conclusion: Nonlinear spectroscopic measurement of MNPs may be a useful method for studying targeted MNPs in oncology. Significance: Determining the quantity of bound and unbound MNP in an unknown sample using a linear model represents an exciting opportunity to translate multifrequency nonlinear spectroscopy methods to in vivo applications where MNPs could be targeted to cancer cells.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Radiotherapy Planning Using an Improved Search Strategy in Particle Swarm
    • Authors: Arezoo Modiri;Xuejun Gu;Aaron M. Hagan;Amit Sawant;
      Pages: 980 - 989
      Abstract: Objective: Evolutionary stochastic global optimization algorithms are widely used in large-scale, nonconvex problems. However, enhancing the search efficiency and repeatability of these techniques often requires well-customized approaches. This study investigates one such approach. Methods: We use particle swarm optimization (PSO) algorithm to solve a 4D radiation therapy (RT) inverse planning problem, where the key idea is to use respiratory motion as an additional degree of freedom in lung cancer RT. The primary goal is to administer a lethal dose to the tumor target while sparing surrounding healthy tissue. Our optimization iteratively adjusts radiation fluence-weights for all beam apertures across all respiratory phases. We implement three PSO-based approaches: conventionally used unconstrained, hard-constrained, and our proposed virtual search. As proof of concept, five lung cancer patient cases are optimized over ten runs using each PSO approach. For comparison, a dynamically penalized likelihood (DPL) algorithm—a popular RT optimization technique is also implemented and used. Results: The proposed technique significantly improves the robustness to random initialization while requiring fewer iteration cycles to converge across all cases. DPL manages to find the global optimum in 2 out of 5 RT cases over significantly more iterations. Conclusion: The proposed virtual search approach boosts the swarm search efficiency, and consequently, improves the optimization convergence rate and robustness for PSO. Significance: RT planning is a large-scale, nonconvex optimization problem, where finding optimal solutions in a clinically practical time is critical. Our proposed approach can potentially improve the optimization efficiency in similar time-sensitive problems.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Localizing Microaneurysms in Fundus Images Through Singular Spectrum
    • Authors: Su Wang;Hongying Lilian Tang;Lutfiah Ismail Al turk;Yin Hu;Saeid Sanei;George Michael Saleh;Tunde Peto;
      Pages: 990 - 1002
      Abstract: Goal: Reliable recognition of microaneurysms (MAs) is an essential task when developing an automated analysis system for diabetic retinopathy (DR) detection. In this study, we propose an integrated approach for automated MA detection with high accuracy. Methods: Candidate objects are first located by applying a dark object filtering process. Their cross-section profiles along multiple directions are processed through singular spectrum analysis. The correlation coefficient between each processed profile and a typical MA profile is measured and used as a scale factor to adjust the shape of the candidate profile. This is to increase the difference in their profiles between true MAs and other non-MA candidates. A set of statistical features of those profiles is then extracted for a K-nearest neighbor classifier. Results: Experiments show that by applying this process, MAs can be separated well from the retinal background, the most common interfering objects and artifacts. Conclusion: The results have demonstrated the robustness of the approach when testing on large scale datasets with clinically acceptable sensitivity and specificity. Significance: The approach proposed in the evaluated system has great potential when used in an automated DR screening tool or for large scale eye epidemiology studies.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • SVM-Based System for Prediction of Epileptic Seizures From iEEG Signal
    • Authors: Han-Tai Shiao;Vladimir Cherkassky;Jieun Lee;Brandon Veber;Edward E. Patterson;Benjamin H. Brinkmann;Gregory A. Worrell;
      Pages: 1011 - 1022
      Abstract: Objective: This paper describes a data-analytic modeling approach for the prediction of epileptic seizures from intracranial electroencephalogram (iEEG) recording of brain activity. Even though it is widely accepted that statistical characteristics of iEEG signal change prior to seizures, robust seizure prediction remains a challenging problem due to subject-specific nature of data-analytic modeling. Methods: Our work emphasizes the understanding of clinical considerations important for iEEG-based seizure prediction, and proper translation of these clinical considerations into data-analytic modeling assumptions. Several design choices during preprocessing and postprocessing are considered and investigated for their effect on seizure prediction accuracy. Results: Our empirical results show that the proposed support vector machine-based seizure prediction system can achieve robust prediction of preictal and interictal iEEG segments from dogs with epilepsy. The sensitivity is about 90–100%, and the false-positive rate is about 0–0.3 times per day. The results also suggest that good prediction is subject specific (dog or human), in agreement with earlier studies. Conclusion : Good prediction performance is possible only if the training data contain sufficiently many seizure episodes, i.e., at least 5–7 seizures. Significance: The proposed system uses subject-specific modeling and unbalanced training data. This system also utilizes three different time scales during training and testing stages.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Observer-Based Human Knee Stiffness Estimation
    • Authors: Berno J. E. Misgeld;Markus Lüken;Robert Riener;Steffen Leonhardt;
      Pages: 1033 - 1044
      Abstract: Objective: We consider the problem of stiffness estimation for the human knee joint during motion in the sagittal plane. Methods: The new stiffness estimator uses a nonlinear reduced-order biomechanical model and a body sensor network (BSN). The developed model is based on a two-dimensional knee kinematics approach to calculate the angle-dependent lever arms and the torques of the muscle-tendon-complex. To minimize errors in the knee stiffness estimation procedure that result from model uncertainties, a nonlinear observer is developed. The observer uses the electromyogram (EMG) of involved muscles as input signals and the segmental orientation as the output signal to correct the observer-internal states. Because of dominating model nonlinearities and nonsmoothness of the corresponding nonlinear functions, an unscented Kalman filter is designed to compute and update the observer feedback (Kalman) gain matrix. Results: The observer-based stiffness estimation algorithm is subsequently evaluated in simulations and in a test bench, specifically designed to provide robotic movement support for the human knee joint. Conclusion: In silico and experimental validation underline the good performance of the knee stiffness estimation even in the cases of a knee stiffening due to antagonistic coactivation. Significance: We have shown the principle function of an observer-based approach to knee stiffness estimation that employs EMG signals and segmental orientation provided by our own IPANEMA BSN. The presented approach makes realtime, model-based estimation of knee stiffness with minimal instrumentation possible.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • EEG-Informed Attended Speaker Extraction From Recorded Speech Mixtures
           With Application in Neuro-Steered Hearing Prostheses
    • Authors: Simon Van Eyndhoven;Tom Francart;Alexander Bertrand;
      Pages: 1045 - 1056
      Abstract: Objective: We aim to extract and denoise the attended speaker in a noisy two-speaker acoustic scenario, relying on microphone array recordings from a binaural hearing aid, which are complemented with electroencephalography (EEG) recordings to infer the speaker of interest. Methods: In this study, we propose a modular processing flow that first extracts the two speech envelopes from the microphone recordings, then selects the attended speech envelope based on the EEG, and finally uses this envelope to inform a multichannel speech separation and denoising algorithm. Results: Strong suppression of interfering (unattended) speech and background noise is achieved, while the attended speech is preserved. Furthermore, EEG-based auditory attention detection (AAD) is shown to be robust to the use of noisy speech signals. Conclusions: Our results show that AAD-based speaker extraction from microphone array recordings is feasible and robust, even in noisy acoustic environments, and without access to the clean speech signals to perform EEG-based AAD. Significance: Current research on AAD always assumes the availability of the clean speech signals, which limits the applicability in real settings. We have extended this research to detect the attended speaker even when only microphone recordings with noisy speech mixtures are available. This is an enabling ingredient for new brain–computer interfaces and effective filtering schemes in neuro-steered hearing prostheses. Here, we provide a first proof of concept for EEG-informed attended speaker extraction and denoising.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Patient-Specific Finite-Element Simulation of the Insertion of Guidewire
           During an EVAR Procedure: Guidewire Position Prediction Validation on 28
    • Authors: J. Gindre;A. Bel-Brunon;M. Rochette;A. Lucas;A. Kaladji;P. Haigron;A. Combescure;
      Pages: 1057 - 1066
      Abstract: Objective: Validation of a numerical method to compute arterial deformations under the insertion of an “extra-siff” guidewire during Endovascular Repair of Abdominal Aortic Aneurysm. Methods: We propose the validation of a previously developed simulation method. The model is calibrated using anatomical hypothesis and intraoperative observations. Simulation results are blindly evaluated against 3-D imaging data acquired during the surgical procedure on 28 patients, based on the predicted position of the intraoperative guidewire. Results: Simulation was successfully conducted on the 28 patients. The mean position error given by the Modified Hausdorff Distance for the 28 cases was 3.8 ± 1.9 mm, which demonstrates very good results for most of the cases. Conclusion: The work reported here shows that numerical simulation can predict some rather large variations in the vascular geometry due to tools insertion, for a wide variety of aorto-iliac morphologies. This is a new step toward clinically applicable mechanical simulation. Significance: Validation on 3-D intraoperative data on a large number of cases—robustness on adverse anatomies.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Orientation-Independent Catheter-Based Characterization of Myocardial
    • Authors: Don Curtis Deno;Ram Balachandran;Dennis Morgan;Faiz Ahmad;Stéphane Massé;Kumaraswamy Nanthakumar;
      Pages: 1067 - 1077
      Abstract: Cardiac electrogram (EGM) signals and electrophysiologic (EP) characteristics derived from them such as amplitude and timing are central to the diagnosis and therapeutic management of arrhythmias. Bipolar EGMs are often used but possess polarity and shape dependence on catheter orientation contributing to uncertainty. Objective: We describe a novel method to map cardiac activation that resolves signals into meaningful directions and is insensitive to electrode directional effects. Methods: Multielectrode catheters that span 2- and 3-D space are used to derive local electric field (E-field) signals. A traveling wave model of local EGM propagation motivates a new “omnipolar” reference frame in which to understand EGM E-field signals and provide bipolar component EGMs aligned with these anatomic and physiologic directions. We validate the basis of this technology and determine its accuracy using a saline tank in which we simulate physiologic propagation. Results: Omnipole signals from healthy tissue are nearly free of catheter orientation effects and are constrained by biophysics to consistent morphologies and thus consistent measured amplitudes and timings. Using a 3-D EP mapping system, traveling wave treatment, and omnipolar technology (OT) E-field loops, we derived a new and nearly instantaneous means to determine conduction velocity and activation direction. Conclusion: We describe the basis of OT and validate it with ablation and mapping catheters in a saline tank. Finally, we illustrate OT with signals from live subjects. Significance: OT's novel approach with signal processing and real-time visualization allows for a newly detailed characterization of myocardial activation that is insensitive to catheter orientation.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Nonlinear
    • Authors: Brandon Christian Henley;Dae C. Shin;Rong Zhang;Vasilis Z. Marmarelis;
      Pages: 1078 - 1088
      Abstract: Objective: As an extension to our study comparing a putative compartmental and data-based model of linear dynamic cerebral autoregulation (CA) and CO2-vasomotor reactivity (VR), we study the CA–VR process in a nonlinear context. Methods: We use the concept of principal dynamic modes (PDM) in order to obtain a compact and more easily interpretable input–output model. This in silico study permits the use of input data with a dynamic range large enough to simulate the classic homeostatic CA and VR curves using a putative structural model of the regulatory control of the cerebral circulation. The PDM model obtained using theoretical and experimental data are compared. Results: It was found that the PDM model was able to reflect accurately both the simulated static CA and VR curves in the associated nonlinear functions (ANFs). Similar to experimental observations, the PDM model essentially separates the pressure-flow relationship into a linear component with fast dynamics and nonlinear components with slow dynamics. In addition, we found good qualitative agreement between the PDMs representing the dynamic theoretical and experimental CO2-flow relationship. Conclusion: Under the modeling assumption and in light of other experimental findings, we hypothesize that PDMs obtained from experimental data correspond with passive fluid dynamical and active regulatory mechanisms. Significance: Both hypothesis-based and data-based modeling approaches can be combined to offer some insight into the physiological basis of PDM model obtained from human experimental data. The PDM modeling approach potentially offers a practical way to quantify the status of specific regulatory mechanisms in the CA–VR process.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Autofocusing and Polar Body Detection in Automated Cell Manipulation
    • Authors: Zenan Wang;Chen Feng;Wei Tech Ang;Steven Yih Min Tan;Win Tun Latt;
      Pages: 1099 - 1105
      Abstract: Autofocusing and feature detection are two essential processes for performing automated biological cell manipulation tasks. In this paper, we have introduced a technique capable of focusing on a holding pipette and a mammalian cell under a bright-field microscope automatically, and a technique that can detect and track the presence and orientation of the polar body of an oocyte that is rotated at the tip of a micropipette. Both algorithms were evaluated by using mouse oocytes. Experimental results show that both algorithms achieve very high success rates: 100% and 96%. As robust and accurate image processing methods, they can be widely applied to perform various automated biological cell manipulations.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • A Therapeutic Wireless Capsule for Treatment of Gastrointestinal
           Haemorrhage by Balloon Tamponade Effect
    • Authors: Billy H. K. Leung;Carmen C. Y. Poon;Ruikai Zhang;Yali Zheng;Cecilia K. W. Chan;Philip W. Y. Chiu;James Y. W. Lau;Joseph J. Y. Sung;
      Pages: 1106 - 1114
      Abstract: Objective: Wireless capsule endoscope (WCE) is a revolutionary approach to diagnose small bowel pathologies. Currently available WCEs are mostly passive devices with image capturing function only, while on-going efforts have been placed on robotizing WCEs or to enhance them with therapeutic functions. In this paper, the authors present a novel inflatable WCE for haemostasis in the gastrointestinal (GI) tracts by balloon tamponade effect. Methods: The proposed wireless capsule consists of a balloon that can be inflated using the endothermic reaction of acid and base. When the balloon reached a precalculated pressure level, it is able to stop at a bleeding site in the bowel, and achieve haemostasis by tamponade effect. The prototype is 14 mm in diameter, with three sections of 13, 35, and 12 mm in length, respectively. The three sections are linked together with flexible joints and enclosed in a silicone balloon. The prototypes were tested in ex vivo porcine intestine models. Results: In the ten ex vivo trials conducted, the inflatable wireless capsule achieved average balloon pressure of 46.0 mmHg and withstood average maximum longitudinal pulling force at 1.46 N. An in vivo study was carried out as a proof-of-concept for treating bleeding in a porcine model. The proposed inflatable WCE succeeded in the animal test by controlling haemostasis within 5 min. No rebleeding was observed in the next 20 min. Conclusion: The results suggested that the inflatable capsule with a real-time bleeding detection algorithm can be implemented. Moreover, the proposed inflatable WCE prototype can achieve haemorrhage control in the lower GI. Significance: To our best knowledge, this is the first study that demonstrated the potential to treat GI haemorrhage by an inflatable WCE. The proposed capsule enables the development of a closed-loop system based on a body sensor network to provi-e early treatment of GI bleeding for p-medicine.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Selection of Reference Channels Based on Mutual Information for
           Frequency-Dependent Subtraction Method Applied to Fetal Biomagnetic
    • Authors: D. Escalona-Vargas;E. R. Siegel;P. Murphy;C. L. Lowery;H. Eswaran;
      Pages: 1115 - 1122
      Abstract: Objective: We propose a method that uses minimal redundancy and maximal relevance (mRMR) based on mutual information as criteria to automatically select references for the frequency-dependent subtraction (SUBTR) method to attenuate maternal (mMCG) and fetal (fMCG) magnetocardiograms of fetal magnetoencephalography recordings. Methods: mRMR is calculated between all channels and mMCG/fMCG target channels and the most promising sensors are used as references to perform SUBTR. We measured the performance of SUBTR at removing interferences in two steps for different number of references in 38 real datasets. The evaluation was based on the MCG amplitude reduction. We compared the performance of the mRMR approach with random selection of references. Results: Significant differences in interference removal were found when a distinct number of references were chosen by mRMR compared to random selection. Conclusion: mRMR provides an effective tool to automatically select a set of featured references. Significance: Although we show the utility of the mRMR method to biomagnetic signals, the approach can easily be adapted to sensor array data from other applications.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Classification and Prediction of Clinical Improvement in Deep Brain
           Stimulation From Intraoperative Microelectrode Recordings
    • Authors: Kyriaki Kostoglou;Konstantinos P. Michmizos;Pantelis Stathis;Damianos Sakas;Konstantina S. Nikita;Georgios D. Mitsis;
      Pages: 1123 - 1130
      Abstract: We present a random forest (RF) classification and regression technique to predict, intraoperatively, the unified Parkinson's disease rating scale (UPDRS) improvement after deep brain stimulation (DBS). We hypothesized that a data-informed combination of features extracted from intraoperative microelectrode recordings (MERs) can predict the motor improvement of Parkinson's disease patients undergoing DBS surgery. We modified the employed RFs to account for unbalanced datasets and multiple observations per patient, and showed, for the first time, that only five neurophysiologically interpretable MER signal features are sufficient for predicting UPDRS improvement. This finding suggests that subthalamic nucleus (STN) electrophysiological signal characteristics are strongly correlated to the extent of motor behavior improvement observed in STN-DBS.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Advanced Volume-Compensation Method for Indirect Finger Arterial Pressure
           Determination: Comparison with Brachial Sphygmomanometry
    • Authors: Kenta Matsumura;Takehiro Yamakoshi;Peter Rolfe;Ken-ichi Yamakoshi;
      Pages: 1131 - 1137
      Abstract: Objective: The so-called volume-compensation method (VCM) allows noninvasive instantaneous arterial blood pressure (BP) measurement in human fingers. The VCM is mostly carried out with photoplethysmography (PPG) to detect arterial volume pulsations. However, measurement errors may occur due to movement of the PPG sensors relative to skin and underlying vasculature. We report here the effectiveness of a new technique, “advanced VCM” (AVCM), developed by us to resolve this significant problem. Methods: The AVCM described uses a control system with procedures for adjusting system parameters derived from the pulsatile PPG signal and the finger cuff pressure. In open loop pre-operation, mean BP is estimated from a finger using the volume-oscillometric method. The control system reference is then adjusted to yield approximately equal values in mean BP and this gives optimum performance for instantaneous BP measurement. Systolic and diastolic BP values (SBP, DBP) from the instantaneous BP by the VCM and the AVCM were compared with the conventional brachial SBP/DBP measured simultaneously during 5-min baseline. SBP/DBP from the AVCM were also compared with brachial SBP/DBP during 36-min bicycle ergometer exercise. Results: Measurement errors that occurred when the BP measurement was run using the previous VCM essentially disappeared in the AVCM. Bland–Altman analysis revealed negligible fixed and proportional bias between finger SBP/DBP and brachial SBP/DBP. Conclusion: These findings suggest that the AVCM could be an effective technique to resolve the problem of measurement errors occurring with standard VCM. Significance: The newly proposed AVCM is potentially useful for all research and clinical situations where noninvasive continuous BP measurement is needed.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Riemannian Geometry Applied to Detection of Respiratory States From EEG
           Signals: The Basis for a Brain–Ventilator Interface
    • Authors: X. Navarro-Sune;A. L. Hudson;F. De Vico Fallani;J. Martinerie;A. Witon;P. Pouget;M. Raux;T. Similowski;M. Chavez;
      Pages: 1138 - 1148
      Abstract: Goal: During mechanical ventilation, patient-ventilator disharmony is frequently observed and may result in increased breathing effort, compromising the patient's comfort and recovery. This circumstance requires clinical intervention and becomes challenging when verbal communication is difficult. In this study, we propose a brain–computer interface (BCI) to automatically and noninvasively detect patient-ventilator disharmony from electroencephalographic (EEG) signals: a brain–ventilator interface (BVI). Methods: Our framework exploits the cortical activation provoked by the inspiratory compensation when the subject and the ventilator are desynchronized. Use of a one-class approach and Riemannian geometry of EEG covariance matrices allows effective classification of respiratory states. The BVI is validated on nine healthy subjects that performed different respiratory tasks that mimic a patient-ventilator disharmony. Results: Classification performances, in terms of areas under receiver operating characteristic curves, are significantly improved using EEG signals compared to detection based on air flow. Reduction in the number of electrodes that can achieve discrimination can be often desirable (e.g., for portable BCI systems). By using an iterative channel selection technique, the common highest order ranking, we find that a reduced set of electrodes ($n=6$ ) can slightly improve for an intrasubject configuration, and it still provides fairly good performances for a general intersubject setting. Conclusion: Results support the discriminant capacity of our approach to identify anomalous respiratory states, by learning from a training set containing only normal respiratory epochs. Significance: The proposed framework opens the door to BVIs for monitoring pati-nt's breathing comfort and adapting ventilator parameters to patient respiratory needs.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Spatially Coherent Activation Maps for Electrocardiographic Imaging
    • Authors: Josselin Duchateau;Mark Potse;Remi Dubois;
      Pages: 1149 - 1156
      Abstract: Objective: Cardiac mapping is an important diagnostic step in cardiac electrophysiology. One of its purposes is to generate a map of the depolarization sequence. This map is constructed in clinical routine either by directly analyzing cardiac electrograms (EGMs) recorded invasively or an estimate of these EGMs obtained by a noninvasive technique. Activation maps based on noninvasively estimated EGMs often show artefactual jumps in activation times. To overcome this problem, we present a new method to construct the activation maps from reconstructed unipolar EGMs. Methods: On top of the standard estimation of local activation time from unipolar intrinsic deflections, we propose to mutually compare the EGMs in order to estimate the delays in activation for neighboring recording locations. We then describe a workflow to construct a spatially coherent activation map from local activation times and delay estimates in order to create more accurate maps. The method is optimized using simulated data and evaluated on clinical data from 12 different activation sequences. Results: We found that the standard methodology created lines of artificially strong activation time gradient. The proposed workflow enhanced these maps significantly. Conclusion: Estimating delays between neighbors is an interesting option for activation map computation in electrocardiographic imaging.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • A Multi-Variate Predictability Framework to Assess Invasive Cardiac
           Activity and Interactions During Atrial Fibrillation
    • Authors: Alejandro Alcaine;Michela Masè;Alessandro Cristoforetti;Flavia Ravelli;Giandomenico Nollo;Pablo Laguna;Juan Pablo Martínez;Luca Faes;
      Pages: 1157 - 1168
      Abstract: Objective: This study introduces a predictability framework based on the concept of Granger causality (GC), in order to analyze the activity and interactions between different intracardiac sites during atrial fibrillation (AF). Methods: GC-based interactions were studied using a three-electrode analysis scheme with multi-variate autoregressive models of the involved preprocessed intracardiac signals. The method was evaluated in different scenarios covering simulations of complex atrial activity as well as endocardial signals acquired from patients. Results: The results illustrate the ability of the method to determine atrial rhythm complexity and to track and map propagation during AF. Conclusion: The proposed framework provides information on the underlying activation and regularity, does not require activation detection or postprocessing algorithms and is applicable for the analysis of any multielectrode catheter. Significance: The proposed framework can potentially help to guide catheter ablation interventions of AF.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Switched Fuzzy-PD Control of Contact Forces in Robotic
    • Authors: Weize Zhang;Xianke Dong;Xinyu Liu;
      Pages: 1169 - 1177
      Abstract: Force sensing and control are of paramount importance in robotic micromanipulation. A contact force regulator capable of accurately applying mechanical stimuli to a live Drosophila larva could greatly facilitate mechanobiology research on Drosophila and may eventually lead to novel discoveries in mechanotransduction mechanisms of neuronal circuitries. In this paper, we present a novel contact force control scheme implemented in an automated Drosophila larvae micromanipulation system, featuring a switched fuzzy to proportional-differential (PD) controller and a noise-insensitive extended high gain observer (EHGO). The switched fuzzy-PD control law inherits the fast convergence of fuzzy control and overcomes its drawbacks such as large overshoot and steady-state oscillation. The noise-insensitive EHGO can reliably estimate system modeling errors and is robust to force measurement noises, which is advantageous over conventional high gain observers (sensitive to signal noises). Force control experiments show that, compared to a proportional-integral-differential (PID) controller, this new force control scheme significantly enhances the system dynamic performance in terms of rising time, overshoot, and oscillation. The developed robotic system and the force control scheme will be applied to mechanical stimulation and fluorescence imaging of Drosophila larvae for identifying new mechanotransduction mechanisms.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
  • Accurate and Standardized Coronary Wave Intensity Analysis
    • Authors: Simone Rivolo;Tiffany Patterson;Kaleab N. Asrress;Michael Marber;Simon Redwood;Nicolas P. Smith;Jack Lee;
      Pages: 1187 - 1196
      Abstract: Objective: Coronary wave intensity analysis (cWIA) has increasingly been applied in the clinical research setting to distinguish between the proximal and distal mechanical influences on coronary blood flow. Recently, a cWIA-derived clinical index demonstrated prognostic value in predicting functional recovery post-myocardial infarction. Nevertheless, the known operator dependence of the cWIA metrics currently hampers its routine application in clinical practice. Specifically, it was recently demonstrated that the cWIA metrics are highly dependent on the chosen Savitzky–Golay filter parameters used to smooth the acquired traces. Therefore, a novel method to make cWIA standardized and automatic was proposed and evaluated in vivo. Methods: The novel approach combines an adaptive Savitzky–Golay filter with high-order central finite differencing after ensemble-averaging the acquired waveforms. Its accuracy was assessed using in vivo human data. The proposed approach was then modified to automatically perform beatwise cWIA. Finally, the feasibility (accuracy and robustness) of the method was evaluated. Results: The automatic cWIA algorithm provided satisfactory accuracy under a wide range of noise scenarios ($leq$ 10% and $leq$ 20% error in the estimation of wave areas and peaks, respectively). These results were confirmed when beat-by-beat cWIA was performed. Conclusion: An accurate, standardized, and automated cWIA was developed. Moreover, the feasibility of beatwise cWIA was demonstrated for the first time. Significance: The proposed algorithm provides practitioners with a standardized technique that could broaden the application of -WIA in the clinical practice as well as enabling multicenter trials. Furthermore, the demonstrated potential of beatwise cWIA opens the possibility of investigating the coronary physiology in real time.
      PubDate: May 2017
      Issue No: Vol. 64, No. 5 (2017)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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Fax: +00 44 (0)131 4513327
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