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  Subjects -> ELECTRONICS (Total: 179 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 7)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 5)
Advances in Electronics     Open Access   (Followers: 78)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Microelectronic Engineering     Open Access   (Followers: 13)
Advances in Power Electronics     Open Access   (Followers: 33)
Advancing Microelectronics     Hybrid Journal  
Aerospace and Electronic Systems, IEEE Transactions on     Hybrid Journal   (Followers: 315)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 24)
Annals of Telecommunications     Hybrid Journal   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 13)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 28)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 19)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 36)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 1)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 8)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 269)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 105)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 86)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 92)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elkha : Jurnal Teknik Elektro     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 51)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage Materials     Full-text available via subscription   (Followers: 3)
EPJ Quantum Technology     Open Access  
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 10)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 191)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
IACR Transactions on Symmetric Cryptology     Open Access  
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 97)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 77)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 46)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 66)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 70)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 56)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 19)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 40)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 26)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 71)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 35)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 46)
IET Smart Grid     Open Access  
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 58)
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 24)
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 13)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 10)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 5)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 6)
International Journal of Control     Hybrid Journal   (Followers: 12)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 2)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 14)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 8)
International Journal of Nano Devices, Sensors and Systems     Open Access   (Followers: 12)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 24)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 3)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 10)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 24)
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 7)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 8)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronics (China)     Hybrid Journal   (Followers: 4)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access  
Journal of Field Robotics     Hybrid Journal   (Followers: 2)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 168)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 7)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 9)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal  
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal  
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 10)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 28)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 26)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Learning Technologies, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Magnetics Letters, IEEE     Hybrid Journal   (Followers: 7)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 5)
Microelectronics and Solid State Electronics     Open Access   (Followers: 18)
Nanotechnology Magazine, IEEE     Full-text available via subscription   (Followers: 33)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal  
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 8)
Optical Communications and Networking, IEEE/OSA Journal of     Full-text available via subscription   (Followers: 15)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 1)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Pulse     Full-text available via subscription   (Followers: 5)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 9)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 5)
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 53)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Services Computing, IEEE Transactions on     Hybrid Journal   (Followers: 4)
Software Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 75)
Solid-State Circuits Magazine, IEEE     Hybrid Journal   (Followers: 13)
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 2)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 6)
Visión Electrónica : algo más que un estado sólido     Open Access   (Followers: 1)
Wireless and Mobile Technologies     Open Access   (Followers: 6)
Wireless Power Transfer     Full-text available via subscription   (Followers: 4)
Women in Engineering Magazine, IEEE     Full-text available via subscription   (Followers: 11)
Електротехніка і Електромеханіка     Open Access  

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Similar Journals
Journal Cover
Biomedical Engineering, IEEE Transactions on
Journal Prestige (SJR): 1.267
Citation Impact (citeScore): 5
Number of Followers: 36  
 
  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: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • 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: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • 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 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • IEEE Transactions on Biomedical Engineering Handling Editors
    • Abstract: Presents a listing of the handling editors for this issue of the publication.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Joint Classification and Regression via Deep Multi-Task Multi-Channel
           Learning for Alzheimer's Disease Diagnosis
    • Authors: Mingxia Liu;Jun Zhang;Ehsan Adeli;Dinggang Shen;
      Pages: 1195 - 1206
      Abstract: In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic resonance imaging (MRI) have attracted increasing attention since these two tasks are highly correlated. Most of existing joint learning approaches require hand-crafted feature representations for MR images. Since hand-crafted features of MRI and classification/regression models may not coordinate well with each other, conventional methods may lead to sub-optimal learning performance. Also, demographic information (e.g., age, gender, and education) of subjects may also be related to brain status, and thus can help improve the diagnostic performance. However, conventional joint learning methods seldom incorporate such demographic information into the learning models. To this end, we propose a deep multi-task multi-channel learning (DM$^2$L) framework for simultaneous brain disease classification and clinical score regression, using MRI data and demographic information of subjects. Specifically, we first identify the discriminative anatomical landmarks from MR images in a data-driven manner, and then extract multiple image patches around these detected landmarks. We then propose a deep multi-task multi-channel convolutional neural network for joint classification and regression. Our DM$^2$L framework can not only automatically learn discriminative features for MR images, but also explicitly incorporate the demographic information of subjects into the learning process. We evaluate the proposed method on four large multi-center cohorts with 1984 subjects, and the experimental results demonstrate that DM$^2$L is superior to several state-of-the-art joint learning methods in both -he tasks of disease classification and clinical score regression.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Evaluation of Haptic Feedback on Bimanually Teleoperated Laparoscopy for
           Endometriosis Surgery
    • Authors: Sergio Portolés Díez;Gianni Borghesan;Luc Joyeux;Christel Meuleman;Jan Deprest;Danail Stoyanov;Sebastien Ourselin;Tom Vercauteren;Dominiek Reynaerts;Emmanuel B. Vander Poorten;
      Pages: 1207 - 1221
      Abstract: Robotic minimal invasive surgery is gaining acceptance in surgical care. In contrast with the appreciated three-dimensional vision and enhanced dexterity, haptic feedback is not offered. For this reason, robotics is not considered beneficial for delicate interventions such as the endometriosis. Overall, haptic feedback remains debatable and yet unproven except for some simple scenarios such as fundamentals of laparoscopic surgery exercises. Objective: This work investigates the benefits of haptic feedback on more complex surgical gestures, manipulating delicate tissue through coordination between multiple instruments. Methods: A new training exercise, “endometriosis surgery exercise” (ESE) has been devised approximating the setting for monocular robotic endometriosis treatment. A bimanual bilateral teleoperation setup was designed for laparoscopic laser surgery. Haptic guidance and haptic feedback are, respectively, offered to the operator. User experiments have been conducted to assess the validity of ESE and examine possible advantages of haptic technology during execution of bimanual surgery. Results: Content and face validity of ESE were established by participating surgeons. Surgeons suggested ESE also as a mean to train lasering skills, and interaction forces on endometriotic tissue were found to be significantly lower when a bilateral controller is used. Collisions between instruments and the environment were less frequent and so were situations marked as potentially dangerous. Conclusion: This study provides some promising results suggesting that haptics may offer a distinct advantage in complex robotic interventions were fragile tissue is manipulated. Significance: Patients need to know whether it should be incorporated. Improved understanding of the value of haptics is important as current commercial surgical robots are widely used bu- do not offer haptics.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • New Similarity Metric for Registration of MRI to Histology: Golden
           Retriever Muscular Dystrophy Imaging
    • Authors: Aydin Eresen;Sharla M. Birch;Lejla Alic;John F. Griffin IV;Joe N. Kornegay;Jim Xiuquan Ji;
      Pages: 1222 - 1230
      Abstract: Objective: Histology is often used as a gold standard to evaluate noninvasive imaging modalities such as a magnetic resonance imaging (MRI). Spatial correspondence between histology and MRI is a critical step in quantitative evaluation of skeletal muscle in golden retriever muscular dystrophy (GRMD). Registration becomes technically challenging due to nonorthogonal histology section orientation, section distortion, and the different image contrast and resolution. Methods: This study describes a three-step procedure to register histology images with multiparametric MRI, i.e., interactive slice localization controlled by a three-dimensional mouse, followed by an affine transformation refinement, and a B-spline deformable registration using a new similarity metric. This metric combines mutual information and gradient information. Results: The methodology was verified using ex vivo high-resolution multiparametric MRI with a resolution of 117.19 μm (i.e., T1-weighted and T2-weighted MRI images) and trichrome stained histology images acquired from the pectineus muscles of ten dogs (nine GRMD and one healthy control). The proposed registration method yielded a root mean squares (RMS) error of 148.83 ± 34.96 μm averaged for ten muscle samples based on landmark points validated by five observers. The best RMS error averaged for ten muscles, was 128.48 ± 25.39 μm. Conclusion: The established correspondence between histology and in vivo MRI enables accurate extraction of MRI characteristics for histologically confirmed regions (e.g., muscle, fibrosis, and fat). Significance: The proposed methodology allows creation of a database of spatially registered multiparametric MRI and histology. This database will facilitate accurate monitoring of disease progression and-assess treatment effects noninvasively.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Epilepsy-on-a-Chip System for Antiepileptic Drug Discovery
    • Authors: Jing Liu;Anna R. Sternberg;Shabnam Ghiasvand;Yevgeny Berdichevsky;
      Pages: 1231 - 1241
      Abstract: Objective: Hippocampal slice cultures spontaneously develop chronic epilepsy several days after slicing and are used as an in vitro model of post-traumatic epilepsy. Here, we describe a hybrid microfluidic-microelectrode array (μflow-MEA) technology that incorporates a microfluidic perfusion network and electrodes into a miniaturized device for hippocampal slice culture based antiepileptic drug discovery. Methods: Field potential simulation was conducted to help optimize the electrode design to detect a seizure-like population activity. Epilepsy-on-a-chip model was validated by chronic electrical recording, neuronal survival quantification, and anticonvulsant test. To demonstrate the application of μflow-MEA in drug discovery, we utilized a two-stage screening platform to identify potential targets for antiepileptic drugs. In Stage I, lactate and lactate dehydrogenase biomarker assays were performed to identify potential drug candidates. In Stage II, candidate compounds were retested with μflow-MEA-based chronic electrical assay to provide electrophysiological confirmation of biomarker results. Results and Conclusion: We screened 12 receptor tyrosine kinases inhibitors, and EGFR/ErbB-2 and cFMS inhibitors were identified as novel antiepileptic compounds. Significance: This epilepsy-on-a-chip system provides the means for rapid dissection of complex signaling pathways in epileptogenesis, paving the way for high-throughput antiepileptic drug discovery.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Wearable Devices for Precision Medicine and Health State Monitoring
    • Authors: In cheol Jeong;David Bychkov;Peter C. Searson;
      Pages: 1242 - 1258
      Abstract: Wearable technologies will play an important role in advancing precision medicine by enabling measurement of clinically-relevant parameters describing an individual's health state. The lifestyle and fitness markets have provided the driving force for the development of a broad range of wearable technologies that can be adapted for use in healthcare. Here we review existing technologies currently used for measurement of the four primary vital signs: temperature, heart rate, respiration rate, and blood pressure, along with physical activity, sweat, and emotion. We review the relevant physiology that defines the measurement needs and evaluate the different methods of signal transduction and measurement modalities for the use of wearables in healthcare.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Conceptual Intra-Cardiac Electrode Configurations That Facilitate
           Directional Cardiac Stimulation for Optimal Electrotherapy
    • Authors: Adam Connolly;Steven Williams;Kawal Rhode;Christopher A. Rinaldi;Martin J. Bishop;
      Pages: 1259 - 1268
      Abstract: Objective: Electrotherapy remains the most effective direct therapy against lethal cardiac arrhythmias. When an arrhythmic event is sensed, either strong electric shocks or controlled rapid pacing is automatically applied directly to the heart via an implanted cardioverter defibrillator (ICDs). Despite their success, ICDs remain a highly non-optimal therapy: the strong shocks required for defibrillation cause significant extra-cardiac stimulation, resulting in pain and long-term tissue damage, and can also limit battery life. When used in anti-tachycardia pacing mode, ICDs are also often ineffective, as the pacing electrode can be far away from the centre of the arrhythmia, making it hard for the paced wave to interrupt and terminate it. Methods: In this paper, we present two conceptual intra-cardiac directional electrode configurations in silico based on novel arrangements of pairs of positive-negative electrodes. Both configurations have the potential to cause preferential excitation on specific regions of the heart. Results: We demonstrate how the properties of the induced field varies spatially around the electrodes and how it depends upon the specific arrangements of dipole electrode pairs. The results show that when tested within anatomically-realistic rabbit ventricular models, both electrode configurations produce strong virtual electrodes on the targeted endocardial surfaces, with weaker virtual electrodes produced elsewhere. Conclusions: The proposed electrode configurations may facilitate targeted far-field anti-tachycardia pacing and/or defibrillation, which may be useful in cases where conventional anti-tachycardia pacing fails. In addition, the conceptual electrode designs intrinsically confine the electric field to the immediate vicinity of the electrodes, and may, thus, minimize pain due to unnecessary extra-cardiac stimulation.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Reduced-Order Unscented Kalman Filter With Observations in the Frequency
           Domain: Application to Computational Hemodynamics
    • Authors: Lucas O. Müller;Alfonso Caiazzo;Pablo Javier Blanco;
      Pages: 1269 - 1276
      Abstract: Objective: The aim of this paper is to assess the potential of the reduced-order unscented Kalman's filter (ROUKF) in the context of computational hemodynamics, in order to estimate cardiovascular model parameters when employing real patient-specific data. Methods: The approach combines an efficient blood flow solver for one-dimensional networks (for the forward problem) with the parameter estimation problem cast in the frequency space. Namely, the ROUKF is used to correct model parameters after each cardiac cycle, depending on the discrepancies of model outputs with respect to available observations properly mapped into the frequency space. Results: First we validate the filter in frequency domain applying it in the context of a set of experimental measurements for an in vitro model. Second, we perform different numerical experiments aiming at parameter estimation using patient-specific data. Conclusion: Our results demonstrate that the filter in frequency domain allows a faster and more robust parameter estimation, when compared to its time-domain counterpart. Moreover, the proposed approach allows to estimate parameters that are not directly related to the network, but are crucial for targeting inter-individual parameter variability (e.g., parameters that characterize the cardiac output). Significance: The ROUKF in frequency domain provides a robust and flexible tool for estimating parameters related to cardiovascular mathematical models using in vivo data.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Wrist and Finger Gesture Recognition With Single-Element Ultrasound
           Signals: A Comparison With Single-Channel Surface Electromyogram
    • Authors: Jiayuan He;Henry Luo;Jie Jia;John T. W. Yeow;Ning Jiang;
      Pages: 1277 - 1284
      Abstract: With the ability to detect volumetric changes of contracting muscles, ultrasound (US) was a potential technique in the field of human–machine interface. Compared to the US imaging (B-mode US), the signal from a static single-element US transducer, A-mode US, was a more cost-effective and convenient way toward the real-world application, particularly the wearables. This study compared the performance of the single-channel A-mode US with single-channel surface electromyogram (sEMG) signals, one of the most popular signal modalities for wrist and finger gesture recognition. We demonstrated that A-mode US outperformed sEMG in six out of nine gestures recognition, while sEMG was superior to A-mode US on the detection of the rest state. We also demonstrated that, through feature space analysis, the advantage of A-mode US over sEMG for gesture recognition was due to its superior ability in detecting information from deep musculature. This study presented the clear complementary advantages between A-mode US and sEMG, indicating the possibility of fusing two signal modalities for the gesture recognition applications.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Joint Classification and Prediction CNN Framework for Automatic Sleep
           Stage Classification
    • Authors: Huy Phan;Fernando Andreotti;Navin Cooray;Oliver Y. Chén;Maarten De Vos;
      Pages: 1285 - 1296
      Abstract: Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This paper proposes a joint classification-and-prediction framework based on convolutional neural networks (CNNs) for automatic sleep staging, and, subsequently, introduces a simple yet efficient CNN architecture to power the framework. Given a single input epoch, the novel framework jointly determines its label (classification) and its neighboring epochs’ labels (prediction) in the contextual output. While the proposed framework is orthogonal to the widely adopted classification schemes, which take one or multiple epochs as contextual inputs and produce a single classification decision on the target epoch, we demonstrate its advantages in several ways. First, it leverages the dependency among consecutive sleep epochs while surpassing the problems experienced with the common classification schemes. Second, even with a single model, the framework has the capacity to produce multiple decisions, which are essential in obtaining a good performance as in ensemble-of-models methods, with very little induced computational overhead. Probabilistic aggregation techniques are then proposed to leverage the availability of multiple decisions. To illustrate the efficacy of the proposed framework, we conducted experiments on two public datasets: Sleep-EDF Expanded (Sleep-EDF), which consists of 20 subjects, and Montreal Archive of Sleep Studies (MASS) dataset, which consists of 200 subjects. The proposed framework yields an overall classification accuracy of 82.3% and 83.6%, respectively. We also show that the proposed framework not only is superior to the baselines based on the common classification schemes but also outperforms existing deep-learning approaches. To our knowledge, this is the first work going beyond the standard single-output classification to consider multitask neural networks for automatic sleep staging. This frame-ork provides avenues for further studies of different neural-network architectures for automatic sleep staging.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Deep Learning Models Unveiled Functional Difference Between Cortical Gyri
           and Sulci
    • Authors: Shu Zhang;Huan Liu;Heng Huang;Yu Zhao;Xi Jiang;Brook Bowers;Lei Guo;Xiaoping Hu;Mar Sanchez;Tianming Liu;
      Pages: 1297 - 1308
      Abstract: It is largely unknown whether there is functional role difference between cortical gyral and sulcal regions. Recent advancements in neuroimaging studies demonstrate clear difference of structural connection profiles in gyral and sulcal areas, suggesting possible functional role difference in these convex and concave cortical regions. To explore and confirm such possible functional difference, we design and apply a powerful deep learning model of convolutional neural networks (CNN) that has been proven to be superior in learning discriminative and meaningful patterns on fMRI. By using the CNN model, gyral and sulcal fMRI signals are learned and predicted, and the prediction performance is adopted to demonstrate the functional difference between gyri and sulci. By using the Human Connectome Project (HCP) fMRI data and macaque brain fMRI data, an average of 83% and 90% classification accuracy has been achieved to separate gyral/sulcal HCP task fMRI signals at the population and individual subject level, respectively; 81% and 86% classification accuracy for resting state fMRI signals at the group and individual subject level, respectively. In addition, 78% classification accuracy has been achieved to separate gyral/sulcal resting state fMRI signals in macaque brains. Importantly, further analysis reveals that the discriminative features that are learned by CNNs to differentiate gyral/sulcal fMRI signals can be meaningfully interpreted, thus unveiling the fundamental functional difference between cortical gyri and sulci. That is, gyri are more global functional integration centers with simpler lower frequency signal components, while sulci are more local processing units with more complex higher frequency signal components.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Sensitivity of Shoulder Musculoskeletal Model Predictions to
           Muscle–Tendon Properties
    • Authors: Y. Blache;B. Michaud;I. Rogowski;K. Monteil;M. Begon;
      Pages: 1309 - 1317
      Abstract: Objective: While the sensitivity of estimated muscle forces to muscle–tendon properties is well documented for the lower limbs, little is known about the shoulder and upper limbs. The purpose of this study was to assess the sensitivity of estimated shoulder muscle forces and scapulohumeral joint force to muscle–tendon properties. Methods: One healthy male participant performed arm flexions and simulated throwing maneuvers. Kinematics were recorded using intra-cortical pins. Muscle forces were estimated using static optimization with the generic delft shoulder and elbow in OpenSim, and scapulohumeral joint forces were calculated from the estimated forces. Then, variations from –25% to +25% of the nominal values of the tendon slack length, the optimal fiber length, the maximal isometric force, and the pennation angle were applied to the musculoskeletal model to compute affected muscle forces and scapulohumeral joint force. Results: The variations in muscle–tendon properties led to changes up to 9.6 N or 174% in the muscle nominal forces. The more sensitive muscles were those that produced the greatest force: the rotator cuff muscles and the prime movers specific to the task. Among the four muscle–tendon properties, the maximal isometric force and the optimal fiber length had the greatest influence on the muscle force variability. Glenohumeral force was slightly influenced by muscle–tendon properties (
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Non-Contact Monitoring of Temporal Volume Changes of a Hematoma in the
           Head by a Single Inductive Coil: A Numerical Study
    • Authors: Moshe Oziel;Rafi Korenstein;Boris Rubinsky;
      Pages: 1328 - 1336
      Abstract: Objective: This numerical study was designed to evaluate the feasibility of using an inductive coil for monitoring the changes in the volume of a hematoma in the head in situ and to compare the inductive coil performance to that of a spiral antenna based on the radar principle. Methods: Numerical analysis was used to solve the complete set of Maxwell's equations in full three-dimensional anatomical model of a head and brain with data on clinical occurrence of hematomas from the clinical literature, for frequencies of 100 MHz, 500 MHz, and 1 GHz. Results: 1) The analysis shows that the spiral radar antenna provides a better resolution when the antenna can be placed exactly facing the center of the volume of blood. Under any other circumstance, the inductive coil has a better resolution at both 500 MHz and 1 GHz. 2) The induction coil is more sensitive to rotation artifacts than the spiral antenna. 3) Single frequency measurements do not provide conclusive results. Conclusion: The inductive coil has the ability to monitor small changes in the volume of a hematoma in the head. However, multifrequency measurements are required for correct diagnostic. Significance: This study provides a new, low-cost alternative to the conventional medical imaging for monitoring the hematoma increase.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Flexible Platform for In Situ Impedimetric Detection and Bioelectric
           Effect Treatment of Escherichia Coli Biofilms
    • Authors: Ryan C. Huiszoon;Sowmya Subramanian;Pradeep Ramiah Rajasekaran;Luke A. Beardslee;William E. Bentley;Reza Ghodssi;
      Pages: 1337 - 1345
      Abstract: Goal: This paper reports a platform for real-time monitoring and treatment of biofilm formation on three-dimensional biomedical device surfaces. Methods: We utilize a flexible platform consisting of gold interdigitated electrodes patterned on a polyimide substrate. The device was integrated onto the interior of a urinary catheter and characterization was performed in a custom-developed flow system. Biofilm growth was monitored via impedance change at 100 Hz ac with a 50 mV signal amplitude. Results: A 30% impedance decrease over 24 h corresponded to Escherichia coli biofilm formation. The platform also enabled removal of the biofilm through the bioelectric effect; a low concentration of antibiotic combined with the applied ac voltage signal led to a synergistic reduction in biofilm resulting in a 12% increase in impedance. Biomass characterization via crystal violet staining confirmed that the impedance detection results correlate with changes in the amount of biofilm biomass on the sensor. We also demonstrated integration with a chip-based impedance converter to enable miniaturization and allow in situ wireless implementation. A 5% impedance decrease measured with the impedance converter corresponded to biofilm growth, replicating the trend measured with the potentiostat. Conclusion: This platform represents a promising solution for biofilm infection management in diverse vulnerable environments. Significance: Biofilms are the dominant mode of growth for microorganisms, where bacterial cells colonize hydrated surfaces and lead to recurring infections. Due to the inaccessible nature of the environments where biofilms grow and their increased tolerance of antimicrobials, identification, and removal on medical devices poses a -hallenge.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Lung Ultrasound Surface Wave Elastography for Assessing Interstitial Lung
           Disease
    • Authors: Xiaoming Zhang;Boran Zhou;Thomas Osborn;Brian Bartholmai;Sanjay Kalra;
      Pages: 1346 - 1352
      Abstract: Objective: Our goal is to translate lung ultrasound surface wave elastography (LUSWE) for assessing patients with interstitial lung disease (ILD) and various connective tissue diseases including systemic sclerosis (SSc). Methods: LUSWE was used to measure the surface wave speed of lung at 100, 150, and 200 Hz through six intercostal lung spaces for 91 patients with ILD and 30 healthy control subjects. In addition, skin viscoelasticity was measured on both forearms and upper arms for patients and controls. Results: The surface wave speeds of patients’ lungs were significantly higher than those of control subjects. Patient skin elasticity and viscosity were significantly higher than those of control subjects. In dividing ILD patients into two groups, ILD with SSc patients and ILD without SSc patients, significant differences between each patient group with the control group were found for both the lung and skin. No significant differences were found between the two patient groups, although there were some differences at a few locations and at 100 Hz for skin viscoelasticity. Conclusion: Significant differences of surface wave speed were found between ILD patients and healthy control subjects for both the lung and skin. Significance: LUSWE may be useful for assessing ILD and SSc and screening early stage patients.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Comparison of Bipolar and Unipolar Pulses in Cell Electrofusion:
           Simulation and Experimental Research
    • Authors: Chengxiang Li;Qiang Ke;Cheng Yao;Chenguo Yao;Yan Mi;Meng Wu;Liangpeng Ge;
      Pages: 1353 - 1360
      Abstract: Objective: Unipolar pulses have been used in cell electrofusion over the last decades. However, the problem of high mortality with unipolar pulses has not been solved effectively. The cell fusion rate is restricted by cell mortality. By using the advantages of bipolar pulses which cause less cell damage, this paper attempts to use bipolar pulses to increase the cell fusion rate. Methods: the transmembrane voltage and pore density of cells subjected to unipolar/bipolar pulses were simulated in COMSOL software. In an experiment, two 40 μs unipolar and two 20–20 μs bipolar pulses with electric fields of 2, 2.5, and 3 kV/cm were applied to SP2/0 murine myeloma cells. To determine the cell fusion rate and cell mortality, cells were stained with Hoechst 33342 and propidium iodide. Results: the simulation in this paper showed that a high transmembrane voltage and a high pores density were concentrated only at the contact area of cells when bipolar pulses were used. The results of the cell staining experiment verified the simulation analysis. When bipolar pulses were applied, the cell mortality was significantly reduced. In addition, the cell fusion rate with bipolar pulses was almost two times higher than that with unipolar pulses. Conclusion: for cell electrofusion, compared with unipolar pulses, bipolar pulses can not only reduce the cell mortality remarkably but also improve the cell fusion rate obviously. Significance: this paper introduces a novel way to increase the fusion rate of cells.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Reconstruction of Fluorescence Molecular Tomography via a Fused LASSO
           Method Based on Group Sparsity Prior
    • Authors: Shixin Jiang;Jie Liu;Guanglei Zhang;Yu An;Hui Meng;Yuan Gao;Kun Wang;Jie Tian;
      Pages: 1361 - 1371
      Abstract: Objective: The aim of this paper is to improve the reconstruction accuracy in both position and source region of fluorescence molecular tomography (FMT). Methods: The reconstruction of the FMT is challenging due to its serious ill-posedness and ill-condition. Currently, to obtain the fluorescent sources accurately, more a priori information of the fluorescent sources is utilized and more efficient and practical methods are proposed. In this paper, we took the group sparsity of the fluorescent sources as a new type of priori information in the FMT, and proposed the fused LASSO method (FLM) for FMT. The FLM based on group sparsity prior not only takes advantage of the sparsity of the fluorescent sources, but also utilizes the structure of the sources, thus making the reconstruction results more accuracy and morphologically similar to the sources. To further improve the reconstruction efficiency, we adopt Nesterov's method to solve the FLM. Results: Both heterogeneous numerical simulation experiments and in vivo mouse experiments were carried out to verify the property of the FLM. The results have verified the superiority of the FLM over conventional methods in tumor detection and tumor morphological reconstruction. Furthermore, the in vivo experiments had demonstrated that the FLM has great potential in preclinical application of the FMT. Significance: The reconstruction method based on group sparsity prior has a great potential in the FMT study, it can further improve the reconstruction quality, which has practical significance in preclinical research.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Optogenetic Excitation of Ipsilesional Sensorimotor Neurons is Protective
           in Acute Ischemic Stroke: A Laser Speckle Imaging Study
    • Authors: Bin Bo;Yao Li;Wanlu Li;Yongting Wang;Shanbao Tong;
      Pages: 1372 - 1379
      Abstract: Objective: Directly modulating targeted cortical function, brain stimulation provides promising techniques for stroke intervention. However, the cellular level mechanisms underlying preserved neurovascular function remains unclear. Optogenetics provides a cell-specific approach to modulate the neuronal activity. This study aims to investigate whether the exclusive excitation of sensorimotor neurons using optogenetics in an acute stroke can protect neurovascular function and reduce infarct size. Methods: Sensorimotor neurons were transfected with channelrhodopsin-2 and excited by a 473-nm laser. The photothrombotic stroke was induced in the ipsilateral parietal cortex and the targeted area for modulation remained intact. Optogenetic stimulation was carried out within 2 h after stroke in the modulation group. Using a laser speckle contrast imaging technique, we measured the cerebral blood flow at baseline, 0, 2, and 24 h after stroke, and analyzed the hemodynamic changes in both modulation (n = 12) and control (n = 9) groups. Also, the neurovascular response was measured 24 h after stroke. Results: We found that neuronal-specific excitation of an ipsilesional sensorimotor cortex at an acute stage could reduce the expansion of an ischemic area and promote the neurovascular response at 24 h after stroke. The histological and behavioral results consolidate the protective effects of optogenetic-guided neuronal modulation in acute stroke. Conclusion: Excitatory stimulation of ipsilesional sensorimotor neurons in an acute stroke could protect neurovascular function and reduces the expansion of ischemic area. Significance: For the first time, this work demonstrates that specific neuronal modulation in the acute stroke is neuroprotective and reduces the infarct size.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Localization of Activation Origin on Patient-Specific Epicardial Surface
           by Empirical Bayesian Method
    • Authors: Shijie Zhou;John L. Sapp;Fady Dawoud;B. Milan Horáček;
      Pages: 1380 - 1389
      Abstract: Objective: Ablation treatment of ventricular arrhythmias can be facilitated by pre-procedure planning aided by electrocardiographic inverse solution, which can help to localize the origin of arrhythmia. Our aim was to improve localization accuracy of the inverse solution by using a novel Bayesian approach. Methods: The inverse problem of electrocardiography was solved by reconstructing epicardial potentials from 120 body-surface electrocardiograms and from patient-specific geometry of the heart and torso for four patients suffering from scar-related ventricular tachycardia who underwent epicardial catheter mapping, which included pace-mapping. Simulations using dipole sources in patient-specific geometry were also performed. The proposed method, using dynamic spatio-temporal a priori constraints of the solution, was compared with classical Tikhonov methods based on fixed constraints. Results: The mean localization error of the proposed method for all available pacing sites $(n=78)$ was significantly smaller than that achieved by Tikhonov methods; specifically, the localization accuracy for pacing in the normal tissue $(n=17)$ was $text{8} pm text{6}$ mm (mean $pm$ SD) versus $text{13} pm text{9}$ mm $(P < 0.00001)$ reported in the previous study using the same clinical data and Tikhonov regularization. Simulation experiments further supported these clinical findings.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Roll-Off Displacement in Ex Vivo Experiments of RF Ablation With
           Refrigerated Saline Solution and Refrigerated Deionized Water
    • Authors: Ronei Delfino da Fonseca;Melissa Silva Monteiro;Marina Pinheiro Marques;Bruno Costa Motta;Guilherme dos Anjos Guimarães;Paulo Roberto do Santos;Ricardo Perzuol Jacobi;Suélia de Siqueira Rodrigues Fleury Rosa;
      Pages: 1390 - 1401
      Abstract: Objective: The recurrence rate in the treatment of liver tumors using radio frequency ablation (RFA) is often related to incomplete tissue necrosis and consequently the limitation in the ablation volume. This paper proposes an ablation protocol combined with the infusion of saline solution and deionized water aiming at achieving a time displacement in the roll-off occurrence and consequently increasing the volume of ablation. Methods: An infusion of saline solution and deionized water at 5 and 23 $^circ$C was performed to evaluate the influence of these liquids on the RFA procedure in ex vivo bovine liver pieces. The obtained results were used to propose a mathematical model of the roll-off phenomenon by means of the system identification techniques. Results: The RFA combined with the infusion of saline solution 0.9% at 5 $^circ$C presented optimal results, with a time delay of the roll-off occurrence in 27.8% compared to pure RFA ($p$ = 0.002) and an increase in the necrotic volume of 51.2% ($p$ = 0.0002). Two Box–Jenkins models were obtained to describe the roll-off phenomenon: 1) pure RFA; and 2) RFA combined with the saline solution 0.9% at 5 $^circ$C. Conclusion: The RFA therapy combined with the saline solution 0.9% at 5 $^circ$C increases the time range to the roll-off occurrence, leading to higher necrosis volumes in ex vivo bovin- liver samples. The development of a mathematical model to describe the roll-off behavior demonstrated that the transient response is improved by the infusion of the saline solution 0.9% at 5 $^circ$C.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Multi-Source Ensemble Learning for the Remote Prediction of
           Parkinson's Disease in the Presence of Source-Wise Missing Data
    • Authors: John Prince;Fernando Andreotti;Maarten De Vos;
      Pages: 1402 - 1411
      Abstract: As the collection of mobile health data becomes pervasive, missing data can make large portions of datasets inaccessible for analysis. Missing data has shown particularly problematic for remotely diagnosing and monitoring Parkinson's disease (PD) using smartphones. This contribution presents multi-source ensemble learning, a methodology which combines dataset deconstruction with ensemble learning and enables participants with incomplete data (i.e., where not all sensor data is available) to be included in the training of machine learning models and achieves a 100% participant retention rate. We demonstrate the proposed method on a cohort of 1513 participants, 91.2% of which contributed incomplete data in tapping, gait, voice, and/or memory tests. The use of multi-source ensemble learning, alongside convolutional neural networks (CNNs) capitalizing on the amount of available data, increases PD classification accuracy from 73.1% to 82.0% as compared to traditional techniques. The increase in accuracy is found to be partly caused by the use of multi-channel CNNs and partly caused by developing models using the large cohort of participants. Furthermore, through bootstrap sampling we reveal that feature selection is better performed on a large cohort of participants with incomplete data than on a small number of participants with complete data. The proposed method is applicable to a wide range of wearable/remote monitoring datasets that suffer from missing data and contributes to improving the ability to remotely monitor PD via revealing novel methods of accounting for symptom heterogeneity.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • A Wearable Multifunctional Pulse Monitor Using Thermosensation-Based
           Flexible Sensors
    • Authors: Yu Fu;Shuai Zhao;Rong Zhu;
      Pages: 1412 - 1421
      Abstract: Objective: This study proposes a novel wearable pulse monitoring system, which can realize the synchronous measurements of pulse wave, skin, temperature, and pulse wave velocity (PWV). Methods: A flexible sensor based on thermosensation is used to detect pressure and temperature stimuli simultaneously. A total of two sensors are integrated to detect pulse transit along two specific points of the artery, e.g., Cun and Chi at a wrist, the data of which are subsequently used to figure out the PWV by using a tailor-designed algorithm conducted in a microprocessor. Calibration experiments and application cases are conducted to validate the effectiveness of the monitor. Results: The developed monitor detects the physiological signals of pulse wave, PWV, and skin temperature simultaneously. In addition, the monitor can measure the pulse changes before and after exercises and track skin temperature variations when warming and cooling. Moreover, the monitor can be also used to detect the local PWV at the wrist. Conclusion: The synchronous measurements of pulse wave, skin temperature, and PWV using a wearable monitor are feasible. Significance: The monitor is small, simple-structured, with multifunction, and thus provides a promising auxiliary approach for traditional Chinese medicine pulse diagnosis.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • A Fully Automated 3D In-Vivo Delineation and Shape Parameterization of the
           Human Lamina Cribrosa in Optical Coherence Tomography
    • Authors: Piotr Syga;Cezary Sielużycki;Patrycja Krzyżanowska-Berkowska;D. Robert Iskander;
      Pages: 1422 - 1428
      Abstract: Objective: A fully automated method for delineation of the lamina cribrosa in optical coherence tomography (OCT) is proposed. It assesses the three-dimensional (3D) shape of the lamina cribrosa in-vivo, based on a series of OCT B-scans. Methods: The algorithm has several image processing steps and it is based on active contour detection performed along three orthogonal directions of the B-scan data cuboid. Further, the delineated 3D lamina cribrosa shape is parameterized with a fourth-order polynomial of two variables $mathbb {P}left[x,,yright]$ using the least-squares method. Datasets from a total of 255 subjects from three groups were analyzed: 92 primary open angle glaucoma patients, 77 glaucoma suspects, and 86 controls. Results: Statistically significant differences $(p< 0.001)$ were found in the coefficients of monomials $x^iy^j$, with both $i$ and $j$ even, between patients and controls and between suspects and controls. Conclusions: From the data obtained, it can be concluded that the mean shape parameterization of the lamina cribrosa of glaucoma suspects has similar appearance to that of glaucoma patients but it is markedly different from that of healthy controls. Significance: The proposed algorithm enables automatically estimating, for the first time, the lamina cribrosa in 3D, further providing clinicians with a time-efficient discrimination tool supporting glaucoma diagnosis.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Source-Informed Segmentation: A Data-Driven Approach for the Temporal
           Segmentation of EEG
    • Authors: Ali E. Haddad;Laleh Najaf izadeh;
      Pages: 1429 - 1446
      Abstract: Goal: Understanding the dynamics of brain function through non-invasive monitoring techniques requires the development of computational methods that can deal with the non-stationary properties of recorded activities. As a solution to this problem, a new data-driven segmentation method for recordings obtained through electroencephalography (EEG) is presented. Methods: The proposed method utilizes singular value decomposition (SVD) to identify the time intervals in the EEG recordings during which the spatial distribution of clusters of active cortical neurons remains quasi-stationary. Theoretical analysis shows that the spatial locality features of these clusters can be, asymptotically, captured by the most significant left singular subspace of the EEG data. A reference/sliding window approach is employed to dynamically extract this feature subspace, and the running projection error is monitored for significant changes using Kolmogorov-Smirnov test. Results: Simulation results, for a wide range of possible scenarios regarding the spatial distribution of active cortical neurons, show that the algorithm is successful in accurately detecting the segmental structure of the simulated EEG data. The algorithm is also applied to experimental EEG recordings of a modified visual oddball task. Results identify a unique sequence of dynamic patterns in the event-related potential (ERP) response to each of the three involved stimuli. Conclusion: The proposed method, without using source localization methods or scalp topographical maps, is able to identify intervals of quasi-stationarity in the EEG recordings. Significance: The proposed segmentation technique can offer new insights on the dynamics of functional organization of the brain in action.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • A Unified Framework for Plasma Data Modeling in Dynamic Positron Emission
           Tomography Studies
    • Authors: Matteo Tonietto;Gaia Rizzo;Mattia Veronese;Faith Borgan;Peter S. Bloomfield;Oliver Howes;Alessandra Bertoldo;
      Pages: 1447 - 1455
      Abstract: Objective: Full quantification of dynamic positron emission tomography (PET) data requires the knowledge of tracer concentration in the arterial plasma. However, its accurate measurement is challenging due to the presence of radiolabeled metabolites and measurement noise. Mathematical models are fitted to the plasma data for both radiometabolite correction and data denoising. However, the models used are generally not physiologically informed and not consistently applied across studies even when quantifying the kinetics of the same radiotracer, introducing methodological variability affecting the results interpretation. The aim of this study was to develop and validate a unified framework for the arterial data modeling to achieve an accurate and fully automated description of the plasma tracer kinetics. Methods: The proposed pipeline employs basis pursuit techniques for estimating both radiometabolites and parent concentration models from the raw plasma measurements, allowing the resulting algorithm to be both robust and flexible to the different quality of data available. The pipeline was tested on four PET tracers ([11C]PBR28, [11C]MePPEP, [11C]WAY-100635, and [11C]PIB) with continuous and discrete blood sampling. Results: Compared to the standard procedure, the pipeline provided similar fit of the parent fraction but yielded a better description of the total plasma radioactivity, which in turn allowed a more accurate fit of the tissue PET data. Conclusion: The new method showed superior fits compared to the standard pipeline, for both continuous and discrete arterial sampling protocol, yielding to better description of PET data. Significance: The proposed pipeline has the potential to standardize the blood data modeling in dynamic PET studies given its robustness, flexibility and easiness of use.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • 3-D Measurements of Acceleration-Induced Brain Deformation via Harmonic
           Phase Analysis and Finite-Element Models
    • Authors: Arnold D. Gomez;Andrew K. Knutsen;Fangxu Xing;Yuan-Chiao Lu;Deva Chan;Dzung L. Pham;Philip Bayly;Jerry L. Prince;
      Pages: 1456 - 1467
      Abstract: Objective: To obtain dense spatiotemporal measurements of brain deformation from two distinct but complementary head motion experiments: linear and rotational accelerations. Methods: This study introduces a strategy for integrating harmonic phase analysis of tagged magnetic resonance imaging (MRI) and finite-element models to extract mechanically representative deformation measurements. The method was calibrated using simulated as well as experimental data, demonstrated in a phantom including data with image artifacts, and used to measure brain deformation in human volunteers undergoing rotational and linear acceleration. Results: Evaluation methods yielded a displacement error of 1.1 mm compared to human observers and strain errors between ${text{0.1}}pm {text{0.2}}{% ,(text{mean}pm text{std}.,text{dev.)}}$ for linear acceleration and ${text{0.7}}pm {text{0.3}}% $ for rotational acceleration. This study also demonstrates an approach that can reduce error by 86% in the presence of corrupted data. Analysis of results shows consistency with 2-D motion estimation, agreement with external sensors, and the expected physical behavior of the brain. Conclusion: Mechanical regularization is useful for obtaining dense spatiotemporal measurements of in vivo brain deformation under different loading regimes. Significance: The measurements suggest that the brain's 3-D response to mild accelerations includes distinct patterns observable using practical MRI resolutions. This type of measurement can provide validation data for computer models for the study of traumatic brain injury.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Half Thresholding Pursuit Algorithm for Fluorescence Molecular Tomography
    • Authors: Xuelei He;Jingjing Yu;Xiaodong Wang;Huangjian Yi;Yanrong Chen;Xiaolei Song;Xiaowei He;
      Pages: 1468 - 1476
      Abstract: Objective: Fluorescence Molecular Tomography (FMT) is a promising optical tool for small animal imaging. The $ell _{1/2}$-norm regularization has attracted attention in the field of FMT due to its ability in enhancing sparsity of solution and coping with the high ill-posedness of the inverse problem. However, efficient algorithm for solving the nonconvex regularized model deserve to explore. Method: A Half Thresholding Pursuit Algorithm (HTPA) combined with parameter optimization is proposed in this paper to efficiently solve the nonconvex optimization model. Specifically, the half thresholding iteration method is utilized to solve $ell _{1/2}$-norm model, pursuit strategy is used to accelerate the process of iteration, and the parameter optimization scheme is designed to obtain robust parameter. Results: Analysis and assessment on simulated and experimental data demonstrate that the proposed HTPA performs better in location accuracy and reconstructed fluorescent yield in less time cost, compared with the state-of-the-art reconstruction algorithms. Conclusion: The proposed HTPA combined with the parameter optimization scheme is an efficient and robust reconstruction approach to FMT.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Estimating Missing Data in Temporal Data Streams Using Multi-Directional
           Recurrent Neural Networks
    • Authors: Jinsung Yoon;William R. Zame;Mihaela van der Schaar;
      Pages: 1477 - 1490
      Abstract: Missing data is a ubiquitous problem. It is especially challenging in medical settings because many streams of measurements are collected at different—and often irregular—times. Accurate estimation of the missing measurements is critical for many reasons, including diagnosis, prognosis, and treatment. Existing methods address this estimation problem by interpolating within data streams or imputing across data streams (both of which ignore important information) or ignoring the temporal aspect of the data and imposing strong assumptions about the nature of the data-generating process and/or the pattern of missing data (both of which are especially problematic for medical data). We propose a new approach, based on a novel deep learning architecture that we call a Multi-directional Recurrent Neural Network that interpolates within data streams and imputes across data streams. We demonstrate the power of our approach by applying it to five real-world medical datasets. We show that it provides dramatically improved estimation of missing measurements in comparison to 11 state-of-the-art benchmarks (including Spline and Cubic Interpolations, MICE, MissForest, matrix completion, and several RNN methods); typical improvements in Root Mean Squared Error are between 35%–50%. Additional experiments based on the same five datasets demonstrate that the improvements provided by our method are extremely robust.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
  • Corrections to “Automatic Croup Diagnosis Using Cough Sound
           Recognition”
    • Authors: Roneel V. Sharan;Udantha R. Abeyratne;Vinayak R. Swarnkar;Paul Porter;
      Pages: 1491 - 1491
      Abstract: Presents corrections to shareholder information from this paper, “Automatic croup diagnosis using cough sound recognition,” (Sharan, R.V., et al), IEEE Trans. Biomed. Eng., vol. 66, no. 2, pp. 485–495, Feb. 2019.
      PubDate: May 2019
      Issue No: Vol. 66, No. 5 (2019)
       
 
 
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