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  Subjects -> ELECTRONICS (Total: 175 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: 76)
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: 305)
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: 35)
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: 44)
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: 253)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 104)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 85)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 91)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elkha : Jurnal Teknik Elektro     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 50)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage Materials     Full-text available via subscription   (Followers: 2)
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: 185)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
IACR Transactions on Symmetric Cryptology     Open Access  
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 96)
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: 65)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 69)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 55)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 19)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 39)
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: 70)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 11)
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: 45)
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: 57)
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: 12)
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: 23)
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 Field Robotics     Hybrid Journal   (Followers: 2)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 162)
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  
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: 6)
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: 8)
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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Journal Cover
Biomedical Engineering, IEEE Transactions on
Journal Prestige (SJR): 1.267
Citation Impact (citeScore): 5
Number of Followers: 35  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9294
Published by IEEE Homepage  [191 journals]
  • Frontcover
    • Abstract: Presents the front cover for this issue of the publication.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (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: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • IEEE Transactions on Biomedical Engineering (T-BME)
    • 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: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • IEEE Transactions on Biomedical Engineering Handling Editors
    • Abstract: Presents the Handling Editors for this issue of the publication.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Detecting Abnormal Pattern of Epileptic Seizures via Temporal
           Synchronization of EEG Signals
    • Authors: Miaolin Fan;Chun-An Chou;
      Pages: 601 - 608
      Abstract: Objective: Synchronization phenomena of epileptic electroencephalography (EEG) have long been studied. In this study, we aim at investigating the spatial-temporal synchronization pattern in epileptic human brains using the spectral graph theoretic features extracted from scalp EEG and developing an efficient multivariate approach for detecting seizure onsets in real time. Methods: A complex network model is used for representing the recurrence pattern of EEG signals, based on which the temporal synchronization patterns are quantified using the spectral graph theoretic features. Furthermore, a statistical control chart is applied to the extracted features overtime for monitoring the transits from normal to epileptic states in multivariate EEG systems. Results: Our method is tested on 23 patients from CHB-MIT Scalp EEG database. The results show that the graph theoretic feature yields a high sensitivity ($sim$98%) and low latency ($sim$6 s) on average, and seizure onsets in 18 patients are 100% detected. Conclusion: Our approach validates the increased temporal synchronization in epileptic EEG and achieves a comparable detection performance to previous studies. Significance: We characterize the temporal synchronization patterns of epileptic EEG using spectral network metrics. In addition, we found significant changes in temporal synchronization in epileptic EEG, which enable a patient-specific approach for real-time seizure detection for personalized diagnosis and treatment.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Prediction of Abdominal Aortic Aneurysm Growth Using Dynamical Gaussian
           Process Implicit Surface
    • Authors: Huan N. Do;Ahsan Ijaz;Hamidreza Gharahi;Byron Zambrano;Jonguen Choi;Whal Lee;Seungik Baek;
      Pages: 609 - 622
      Abstract: Objective: We propose a novel approach to predict the Abdominal Aortic Aneurysm (AAA) growth in future time, using longitudinal computer tomography (CT) scans of AAAs that are captured at different times in a patient-specific way. Methods: We adopt a formulation that considers a surface of the AAA as a manifold embedded in a scalar field over the three dimensional (3D) space. For this formulation, we develop our Dynamical Gaussian Process Implicit Surface (DGPIS) model based on observed surfaces of 3D AAAs as visible variables while the scalar fields are hidden. In particular, we use Gaussian process regression to construct the field as an observation model from CT training image data. We then learn a dynamic model to represent the evolution of the field. Finally, we derive the predicted AAA surface from the predicted field along with uncertainty quantified in future time. Results: A dataset of 7 subjects (4–7 scans) was collected and used to evaluate the proposed method by comparing its prediction Hausdorff distance errors against those of simple extrapolation. In addition, we evaluate the prediction results with respect to a conventional shape analysis technique such as Principal Component Analysis (PCA). All comparative results show the superior prediction performance of the proposed approach. Conclusion: We introduce a novel approach to predict the AAA growth and its predicted uncertainty in future time, using longitudinal CT scans in a patient-specific fashion. Significance: The capability to predict the AAA shape and its confidence region by our approach establish the potential for guiding clinicians with informed decision in conducting medical treatment and monitoring of AAAs.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • On the Relevance of Computing a Local Version of Sample Entropy in
           Cardiovascular Control Analysis
    • Authors: Alberto Porta;Vlasta Bari;Beatrice De Maria;Beatrice Cairo;Emanuele Vaini;Mara Malacarne;Massimo Pagani;Daniela Lucini;
      Pages: 623 - 631
      Abstract: Objective: Traditional definition of sample entropy (SampEn), here referred to as global SampEn (GSampEn), provides a conditional entropy estimate that blurs the local statistical properties of the time series. We hypothesized that a local version of SampEn (LSampEn) might be more powerful in the presence of determinism than GSampEn. Methods: LSampEn was computed by calculating the probability of the current sample conditioned on each reference pattern and averaging it over all reference patterns. The improved ability of LSampEn compared to GSampEn was demonstrated by simulating deterministic periodic, deterministic chaotic, and linear stochastic dynamics corrupted by additive noise and over real cardiovascular variability series recorded from 16 healthy subjects (max–min age range: 22–58 years) during incremental bicycle ergometer exercise. Results: We found that: i) LSampEn is more robust in describing deterministic periodic or nonlinear features in the presence of additive noise than GSampEn, ii) in association with a surrogate approach, LSampEn is more powerful in detecting nonlinear dynamics than GSampEn, iii) LSampEn and GSampEn are equivalent in the presence of stochastic linear dynamics, and iv) only LSampEn can detect the decrease of complexity of heart period variability during bicycle exercise being a likely hallmark of sympathetic activation. Conclusion: LSampEn preserves the GSampEn capability in characterizing the complexity of short sequences but improves its reliability in the presence of deterministic patterns featuring sharp state transitions and nonlinear dynamics. Significance: Variations of complexity can be measured with a greater statistical power over short series using LSampEn, especially when nonlinear features are present.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • In-Vivo Evaluation of Microultrasound and Thermometric
           Capsule Endoscopes
    • Authors: Holly S. Lay;Gerard Cummins;Benjami F. Cox;Yongqiang Qiu;Mihnea Vlad Turcanu;Rachael McPhillips;Ciaran Connor;Rachael Gregson;Eddie Clutton;Marc P. Y. Desmulliez;Sandy Cochran;
      Pages: 632 - 639
      Abstract: Clinical endoscopy and colonoscopy are commonly used to investigate and diagnose disorders in the upper gastrointestinal tract and colon, respectively. However, examination of the anatomically remote small bowel with conventional endoscopy is challenging. This and advances in miniaturization led to the development of video capsule endoscopy (VCE) to allow small bowel examination in a noninvasive manner. Available since 2001, current capsule endoscopes are limited to viewing the mucosal surface only due to their reliance on optical imaging. To overcome this limitation with submucosal imaging, work is under way to implement microultrasound (μUS) imaging in the same form as VCE devices. This paper describes two prototype capsules, termed Sonocap and Thermocap, which were developed respectively to assess the quality of μUS imaging and the maximum power consumption that can be tolerated for such a system. The capsules were tested in vivo in the oesophagus and small bowel of porcine models. Results are presented in the form of μUS B-scans as well as safe temperature readings observed up to 100 mW in both biological regions. These results demonstrate that acoustic coupling and μUS imaging can be achieved in vivo in the lumen of the bowel and the maximum power consumption that is possible for miniature μUS systems.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Sensory Stimulation Training for BCI System Based on Somatosensory
           Attentional Orientation
    • Authors: Lin Yao;Xinjun Sheng;Natalie Mrachacz-Kersting;Xiangyang Zhu;Dario Farina;Ning Jiang;
      Pages: 640 - 646
      Abstract: In this study, we propose a sensory stimulation training (SST) approach to improve the performance of a brain-computer interface (BCI) based on somatosensory attentional orientation (SAO). In this BCI, subjects imagine the tactile sensation and maintain the attention on the corresponding hand as if there was a tactile stimulus on the wrist skin. Twenty BCI naïve subjects were recruited and randomly divided into a Control-Group and an SST-Group. In the Control-Group, subjects performed left hand and right hand SAO tasks in six consecutive runs (with 40 trials in each run), divided into three blocks with each having two runs. For the SST-Group, two runs included real tactile stimulation to the left or right hand (SST training block), between the first two (Pre-SST block) and the last two SAO runs (Post-SST block). Results showed that the SST-Group had a significantly improved performance of 9.4% between the last block and the first block after SST training (F(2,18) = 11.11, p = 0.0007); in contrast, no significant difference was found in the Control-Group between the first, second, and the last block (F(2,18) = 2.07, p = 0.1546), indicating no learning effect. The tactile sensation-induced oscillatory dynamics were similar to those induced by SAO. In the SST-Group, R2 discriminative information was enhanced around the somatosensory cortex due to the real sensory stimulation as compared with that in the Control-Group. Since the SAO mental task is inherently an internal process, the proposed SST method is meant as an adjuvant to SAO to facilitate subjects in achieving an initial SAO-based BCI control.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Passive Wrist Stiffness: The Influence of Handedness
    • Authors: Stan Durand;Christian Pierre-Yves Rohan;Taya Hamilton;Wafa Skalli;Hermano Igo Krebs;
      Pages: 656 - 665
      Abstract: Objective: This paper reports on the quantification of passive wrist joint stiffness and investigates the potential influence of handedness and gender on stiffness estimates. Methods: We evaluated the torque–angle relationship during passive wrist movements in 2 degrees of freedom (into flexion–extension and radial–ulnar deviation) in 13 healthy subjects using a wrist robot. Experimental results determined intrasubject differences between dominant and nondominant wrist and intersubject differences between male and female participants. Results: We found differences in the magnitude of passive stiffness of left- and right-hand dominant males and right-hand dominant females suggesting that the dominant hand tends to be stiffer than the nondominant hand. Left-hand stiffness magnitude was found to be 37% higher than the right-hand stiffness magnitude in the left-handed male group and the right-hand stiffness magnitude was 11% and 40% higher in the right-handed male and female groups, respectively. Other joint stiffness features such as the orientation and the anisotropy of wrist stiffness followed the expected pattern from previous studies. Conclusion: The observed difference in wrist stiffness between the dominant and nondominant limb is likely due to biomechanical adaptations to repetitive asymmetric activities (such as squash, tennis, basketball, or activities of daily living such as writing, teeth brushing, etc.). Significance: Understanding and quantifying handedness influence on stiffness may have critical implication for the optimization of surgical and rehabilitative interventions.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Noninvasive Treatment-Efficacy Evaluation for HIFU Therapy Based on
           Magneto-Acousto-Electrical Tomography
    • Authors: Yan Zhou;Zhengfeng Yu;Qingyu Ma;Gepu Guo;Juan Tu;Dong Zhang;
      Pages: 666 - 674
      Abstract: Objective: As a novel noninvasive modality of oncotherapy or stroke treatment, high-intensity focused ultrasound (HIFU) has drawn more and more attention in the past decades. Whereas, real-time temperature monitoring and treatment-efficacy evaluation are still the key issues for HIFU therapy. Methods: Based on the temperature–conductivity relation of tissues with a sharp conductivity variation of irreversible thermocoagulation at 69 °C, a noninvasive method of treatment-efficacy evaluation for HIFU ablation using the magneto-acousto-electrical tomography (MAET) technology is theoretically studied. By applying the nonlinear Khokhlov–Zabolotskaya–Kuznetsov equation and Pennes equation, a cylindrical model is established to simulate the distributions of pressure, temperature, and conductivity with the consideration of harmonic components. Results: The MAET signals are simulated to analyze the characteristics of the peak amplitude and the axial interval of the two clusters generated by the conductivity boundary of HIFU ablation. Conclusion: The axial interval can be used as the indictor to evaluate the size of HIFU ablation with the minimum axial width of one wavelength. Significance: The favorable results demonstrate the feasibility of real-time treatment-efficacy evaluation for HIFU therapy using the MAET technology and suggest potential applications in clinical practice.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • In Vivo Impedance Characterization of Cortical Recording Electrodes Shows
           Dependence on Electrode Location and Size
    • Authors: Sam E. John;Nicholas V. Apollo;Nicholas L. Opie;Gil S. Rind;Stephen M. Ronayne;Clive N. May;Thomas J. Oxley;David B. Grayden;
      Pages: 675 - 681
      Abstract: Objective: Neural prostheses are improving the quality of life for those suffering from neurological impairments. Electrocorticography electrodes located in subdural, epidural, and intravascular positions show promise as long-term neural prostheses. However, chronic implantation affects the electrochemical environments of these arrays. Methods: In the present work, the effect of electrode location on the electrochemical properties of the interface was compared. The impedances of the electrode arrays were measured using electrochemical impedance spectroscopy in vitro in saline and in vivo four-week postimplantation. Results: There was not a significant effect of electrode location (subdural, intravascular, or epidural) on the impedance magnitude, and the effect of the electrode size on the impedance magnitude was frequency dependent. There was a frequency-dependent statistically significant effect of electrode location and electrode size on the phase angles of the three arrays. The subdural and epidural arrays showed phase shifts closer to –90° indicating the capacitive nature of the interface in these locations. The impact of placing electrodes within a blood vessel and adjacent to the blood vessel wall was most obvious when looking at the phase responses at frequencies below 10 kHz. Conclusion: Our results show that intravascular electrodes, like those in subdural and epidural positions, show electrical properties that are suitable for recording. These results provide support for the use of intravascular arrays in clinically relevant neural prostheses and diagnostic devices. Significance: Comparison of electrochemical impedance of the epidural, intravascular, and subdural electrode array showed that all three locations are possible placement options, since impedances are in comparable ranges.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • An Entropy-Regularized Framework for Detecting Copy Number Variants
    • Authors: Majid Mohammadi;Fahime Farahi;
      Pages: 682 - 688
      Abstract: The detection of DNA copy number variants (CNVs) is essential for the diagnosis and prognosis of multiple diseases including cancer. Array-based comparative genomic hybridization (aCGH) is a technique to find these aberrations. The available methods for CNV discovery are often predicated on several critical assumptions based on which various regularizations are employed. However, most of the resulting problems are not differentiable and finding their optimums needs massive computations. This paper addresses a new entropic regularization, which is significantly fast and robust against various types of noises. The proposed problem takes advantage of the quadratic Renyi's entropy estimation which is not convex, but the half-quadratic programming gives an efficient solution with guaranteed convergence. We further theoretically prove that minimizing Renyi's entropy estimation would induce the sparsity and smoothness, two salient and desired features for recovered aCGH profiles. Extensive experimental results on simulated and real datasets illustrate the robustness and speed of the proposed method in comparison to the state-of-the-art algorithms.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Predicting Athlete Ground Reaction Forces and Moments From Spatio-Temporal
           Driven CNN Models
    • Authors: William Robert Johnson;Jacqueline Alderson;David Lloyd;Ajmal Mian;
      Pages: 689 - 694
      Abstract: The accurate prediction of three-dimensional (3-D) ground reaction forces and moments (GRF/Ms) outside the laboratory setting would represent a watershed for on-field biomechanical analysis. To extricate the biomechanist's reliance on ground embedded force plates, this study sought to improve on an earlier partial least squares (PLS) approach by using deep learning to predict 3-D GRF/Ms from legacy marker based motion capture sidestepping trials, ranking multivariate regression of GRF/Ms from five convolutional neural network (CNN) models. In a possible first for biomechanics, tactical feature engineering techniques were used to compress space-time and facilitate fine-tuning from three pretrained CNNs, from which a model derivative of ImageNet called “CaffeNet” achieved the strongest average correlation to ground truth GRF/Ms $r(F_{text{mean}})$ 0.9881 and $r(M_{text{mean}})$ 0.9715 ($rtext{RMSE}$ 4.31 and 7.04%). These results demonstrate the power of CNN models to facilitate real-world multivariate regression with practical application for spatio-temporal sports analytics.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Tensor Based Temporal and Multilayer Community Detection for Studying
           Brain Dynamics During Resting State fMRI
    • Authors: Esraa Al-sharoa;Mahmood Al-khassaweneh;Selin Aviyente;
      Pages: 695 - 709
      Abstract: Objective: In recent years, resting state fMRI has been widely utilized to understand the functional organization of the brain for healthy and disease populations. Recent studies show that functional connectivity during resting state is a dynamic process. Studying this temporal dynamics provides a better understanding of the human brain compared to static network analysis. Methods: In this paper, a new tensor based temporal and multi-layer community detection algorithm is introduced to identify and track the brain network community structure across time and subjects. The framework studies the temporal evolution of communities in fMRI connectivity networks constructed across different regions of interests. The proposed approach relies on determining the subspace that best describes the community structure using Tucker decomposition of the tensor. Results: The brain dynamics are summarized into a set of functional connectivity states that are repeated over time and subjects. The dynamic behavior of the brain is evaluated in terms of consistency of different subnetworks during resting state. The results illustrate that some of the networks, such as the default mode, cognitive control and bilateral limbic networks, have low consistency over time indicating their dynamic behavior. Conclusion: The results indicate that the functional connectivity of the brain is dynamic and the detected community structure experiences smooth temporal evolution. Significance: The work in this paper provides evidence for temporal brain dynamics during resting state through dynamic multi-layer community detection which enables us to better understand the behavior of different subnetworks.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Robust Heartbeat Detection From Multimodal Data via CNN-Based
           Generalizable Information Fusion
    • Authors: B. S. Chandra;C. S. Sastry;S. Jana;
      Pages: 710 - 717
      Abstract: Objective: Heartbeat detection remains central to cardiac disease diagnosis and management, and is traditionally performed based on electrocardiogram (ECG). To improve robustness and accuracy of detection, especially, in certain critical-care scenarios, the use of additional physiological signals such as arterial blood pressure (BP) has recently been suggested. Therefore, estimation of heartbeat location requires information fusion from multiple signals. However, reported efforts in this direction often obtain multimodal estimates somewhat indirectly, by voting among separately obtained signal-specific intermediate estimates. In contrast, we propose to directly fuse information from multiple signals without requiring intermediate estimates, and thence estimate heartbeat location in a robust manner. Method: We propose as a heartbeat detector, a convolutional neural network (CNN) that learns fused features from multiple physiological signals. This method eliminates the need for hand-picked signal-specific features and ad hoc fusion schemes. Furthermore, being data-driven, the same algorithm learns suitable features from arbitrary set of signals. Results: Using ECG and BP signals of PhysioNet 2014 Challenge database, we obtained a score of 94%. Furthermore, using two ECG channels of MIT-BIH arrhythmia database, we scored 99.92%. Both those scores compare favorably with previously reported database-specific results. Also, our detector achieved high accuracy in a variety of clinical conditions. Conclusion: The proposed CNN-based information fusion (CIF) algorithm is generalizable, robust and efficient in detecting heartbeat location from multiple signals. Significance: In medical signal monitoring systems, our technique would accurately estimate heartbeat locations even when only a subset of channels are reliable.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Models for Nociception Stimulation and Memory Effects in Awake and Aware
           Healthy Individuals
    • Authors: Dana Copot;Clara Ionescu;
      Pages: 718 - 726
      Abstract: Objective: This paper introduces a primer in the health care practice, namely a mathematical model and methodology for detecting and analysing nociceptor stimulation followed by related tissue memory effects. Methods: Noninvasive nociceptor stimulus protocol and prototype device for measuring bioimpedance is provided. Various time instants, sensor location, and stimulus train have been analysed. Results: The method and model indicate that nociceptor stimulation perceived as pain in awake healthy volunteers is noninvasively detected. The existence of a memory effect is proven from data. Sensor location had minimal effect on detection level, while day-to-day variability was observed without being significant. Conclusion: Following the experimental study, the model enables a comprehensive management of chronic pain patients, and possibly other analgesia, or pain related regulatory loops. Significance: A device and methodology for noninvasive for detecting nociception stimulation have been developed. The proposed method and models have been validated on healthy volunteers.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Bayesian Multiobjective Optimisation With Mixed Analytical and Black-Box
           Functions: Application to Tissue Engineering
    • Authors: Simon Olofsson;Mohammad Mehrian;Roberto Calandra;Liesbet Geris;Marc Peter Deisenroth;Ruth Misener;
      Pages: 727 - 739
      Abstract: Tissue engineering and regenerative medicine looks at improving or restoring biological tissue function in humans and animals. We consider optimising neotissue growth in a three-dimensional scaffold during dynamic perfusion bioreactor culture, in the context of bone tissue engineering. The goal is to choose design variables that optimise two conflicting objectives, first, maximising neotissue growth and, second, minimising operating cost. We make novel extensions to Bayesian multiobjective optimisation in the case of one analytical objective function and one black-box, i.e. simulation based and objective function. The analytical objective represents operating cost while the black-box neotissue growth objective comes from simulating a system of partial differential equations. The resulting multiobjective optimisation method determines the tradeoff between neotissue growth and operating cost. Our method exhibits better data efficiency than genetic algorithms, i.e. the most common approach in the literature, on both the tissue engineering example and standard test functions. The multiobjective optimisation method applies to real-world problems combining black-box models with easy-to-quantify objectives such as cost.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Monitoring the Relative Blood Pressure Using a Hydraulic Bed Sensor System
    • Authors: Bo Yu Su;Moein Enayati;K. C. Ho;Marjorie Skubic;Laurel Despins;James Keller;Mihail Popescu;Giovanna Guidoboni;Marilyn Rantz;
      Pages: 740 - 748
      Abstract: We propose a nonwearable hydraulic bed sensor system that is placed underneath the mattress to estimate the relative systolic blood pressure of a subject, which only differs from the actual blood pressure by a scaling and an offset factor. Two types of features are proposed to obtain the relative blood pressure, one based on the strength and the other on the morphology of the bed sensor ballistocardiogram pulses. The relative blood pressure is related to the actual by a scale and an offset factor that can be obtained through calibration. The proposed system is able to extract the relative blood pressure more accurately with a less sophisticated sensor system compared to those from the literature. We tested the system using a dataset collected from 48 subjects right after active exercises. Comparison with the ground truth obtained from the blood pressure cuff validates the promising performance of the proposed system, where the mean correlation between the estimate and the ground truth is near to 90% for the strength feature and 83% for the morphology feature.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Capacitive ECG Monitoring in Cardiac Patients During Simulated Driving
    • Authors: Lennart Leicht;Erik Skobel;Christian Knackstedt;Marcel Mathissen;Angela Sitter;Tobias Wartzek;Werner Möhler;Sebastian Reith;Steffen Leonhardt;Daniel Teichmann;
      Pages: 749 - 758
      Abstract: Objective: This study aims to compare the informative value of a capacitively coupled electrocardiogram (cECG) to a conventional galvanic reference ECG (rECG) in patients after a major cardiac event under simulated driving conditions. Addressed research questions are the comparison and coherence of cECG and rECG by means of the signal quality, the artifact rate, the rate of assessable data for differential diagnosis, the visibility of characteristic ECG structures in cECG, the precision of ECG time intervals, and heart rate (in particular, despite possible waveform deformations due to the cardiac preconditions). Methods: In a clinical trial, cECG and rECG data were recorded from ten patients after a major cardiac event. The cECG and rECG data were blindly evaluated by two cardiologists with regard to signal quality, artifacts, assessable data for differential diagnosis, visibility of ECG structures, and ECG time intervals. The results were statistically compared. Results: The cECG presented with more artifacts, an inferior signal quality, and less assessable data. However, when the data were assessable, determination of the ECG interval lengths was coherent to the one obtained from the rECG. Conclusion: When the signal quality is sufficient, the cECG yields the same informative value as the rECG. Significance: For certain scenarios, cECG might replace rECG systems. Hence, it is an important research question whether a similar amount of information can be obtained using a cECG system.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Improving Accuracy of Noninvasive Hemoglobin Monitors: A Functional
           Regression Model for Streaming SpHb Data
    • Authors: Devashish Das;Kalyan S. Pasupathy;Nadeem N. Haddad;M. Susan Hallbeck;Martin D. Zielinski;Mustafa Y. Sir;
      Pages: 759 - 767
      Abstract: Objective: The purpose of this paper is to develop a method for improving the accuracy of SpHb monitors, which are noninvasive hemoglobin monitoring tools, leading to better critical care protocols in trauma care. Methods: The proposed method is based on fitting smooth spline functions to SpHb measurements collected over a time window and then using a functional regression model to predict the true HgB value for the end of the time window. Results: The accuracy of the proposed method is compared to traditional methods. The mean absolute error between the raw SpHb measurements and the gold standard hemoglobin measurements was 1.26 g/Dl. The proposed method reduced the mean absolute error to 1.08 g/Dl. [1] Conclusion: Fitting a smooth function to SpHb measurements improves the accuracy of Hgb predictions. Significance: Accurate prediction of current and future HgB levels can lead to sophisticated decision models that determine the optimal timing and amount of blood product transfusions.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Computer-Vision Techniques for Water-Fat Separation in Ultra High-Field
           MRI Local Specific Absorption Rate Estimation
    • Authors: Angel Torrado-Carvajal;Yigitcan Eryaman;Esra Abaci Turk;Joaquin L. Herraiz;Juan A. Hernandez-Tamames;Elfar Adalsteinsson;Lawrence L. Wald;Norberto Malpica;
      Pages: 768 - 774
      Abstract: Objective: The purpose is to prove that computer-vision techniques allow synthesizing water-fat separation maps for local specific absorption rate (SAR) estimation, when patient-specific water-fat images are not available. Methods: We obtained ground truth head models by using patient-specific water-fat images. We obtained two different label-fusion water-fat models generating a water-fat multi-atlas and applying the STAPLE and local-MAP-STAPLE label-fusion methods. We also obtained patch-based water-fat models applying a local group-wise weighted combination of the multi-atlas. Electromagnetic (EM) simulations were performed and B1+ magnitude and 10g averaged SAR maps were generated. Results: We found local approaches provide a high DICE overlap (72.6±10.2% fat and 91.6±1.5% water in local-MAP-STAPLE, and 68.8±8.2% fat and 91.1±1.0% water in patch-based), low Hausdorff distances (18.6±7.7mm fat and 7.4±11.2mm water in local-MAP-STAPLE, and 16.4±8.5mm fat and 7.2±11.8mm water in patch-based) and a low error in volume estimation (15.6±34.4% fat and 5.6±4.1% water in the local-MAP-STAPLE, and 14.0±17.7% fat and 4.7±2.8% water in patch-based). The positions of the peak 10g-averaged local SAR hotspots were the same for every model. Conclusion: We have created patient-specific head models using three different computer-vision based water-fat separation approaches and compared the predictions of B1+ field and SAR distributions generated by simulating these models. Our results prove that a computer-vision approach can be used for patient-specific water-fat separation, and utilized for local SAR estimation in high-field MRI. Significance: Computer-vision approaches can be used for patient-specific water-fat separation and for patient specific local -AR estimation, when water-fat images of the patient are not available.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Ionic Direct Current Modulation for Combined Inhibition/Excitation of the
           Vestibular System
    • Authors: Felix P. Aplin;Dilawer Singh;Charles C. Della Santina;Gene Y. Fridman;
      Pages: 775 - 783
      Abstract: Objective: Prosthetic electrical stimulation delivered to the vestibular nerve could provide therapy for people suffering from bilateral vestibular dysfunction. Common encoding methods use pulse-frequency modulation (PFM) to stimulate the semicircular canals of the vestibular system. We previously showed that delivery of ionic direct current (iDC) can also modulate the vestibular system. In this study, we compare the dynamic range of head velocity encoding from iDC modulation to that of PFM controls. Methods: Gentamicin-treated wild-type chinchillas were implanted with microcatheter tubes that delivered ionic current to the left ear vestibular canals and stimulated with steps of anodic/cathodic iDC or PFM. Evoked vestibulo-ocular reflex eye velocity was used to compare PFM and iDC vestibular modulation. Results: Cathodic iDC steps effectively elicited eye rotations consistent with an increased firing rate of the implanted semicircular canal afferents. Anodic iDC current steps elicited eye rotations in the opposite direction that, when paired with an adapted cathodic offset, increased the dynamic range of eye rotation velocities in comparison to PFM controls. Conclusion: Our results suggest that iDC modulation can effectively modulate the vestibular system across a functional range of rotation vectors and velocities, with a potential benefit over a PFM stimulation paradigm. Significance:  In conjunction with a safe dc delivery system, iDC modulation could potentially increase the range of simulated head rotation velocities available to neuroelectric vestibular prostheses.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • An Independent Component Analysis Approach to Motion Noise Cancelation of
           Cardio-Mechanical Signals
    • Authors: Chenxi Yang;Negar Tavassolian;
      Pages: 784 - 793
      Abstract: This paper proposes a new framework for measuring sternal cardio-mechanical signals from moving subjects using multiple sensors. An array of inertial measurement units are attached to the chest wall of subjects to measure the seismocardiogram (SCG) from accelerometers and the gyrocardiogram (GCG) from gyroscopes. A digital signal processing method based on constrained independent component analysis is applied to extract the desired cardio-mechanical signals from the mixture of vibration observations. Electrocardiogram and photoplethysmography modalities are evaluated as reference sources for the constrained independent component analysis algorithm. Experimental studies with 14 young, healthy adult subjects demonstrate the feasibility of extracting seismo- and gyrocardiogram signals from walking and jogging subjects, with speeds of 3.0 mi/h and 4.6 mi/h, respectively. Beat-to-beat and ensemble-averaged features are extracted from the outputs of the algorithm. The beat-to-beat cardiac interval results demonstrate average detection rates of 91.44% during walking and 86.06% during jogging from SCG, and 87.32% during walking and 76.30% during jogging from GCG. The ensemble-averaged pre-ejection period (PEP) calculation results attained overall squared correlation coefficients of 0.9048 from SCG and 0.8350 from GCG with reference PEP from impedance cardiogram. Our results indicate that the proposed framework can improve the motion tolerance of cardio-mechanical signals in moving subjects. The effective number of recordings during day time could be potentially increased by the proposed framework, which will push forward the implementation of cardio-mechanical monitoring devices in mobile healthcare.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Functional Informed Fiber Tracking Using Combination of Diffusion and
           Functional MRI
    • Authors: Zhipeng Yang;Peiyu He;Jiliu Zhou;Zhaohua Ding;Xi Wu;
      Pages: 794 - 801
      Abstract: Fiber tractography using diffusion weighted MRI (DWI) is a primary tool for mapping structural connectivity in the human brain in vivo. However, this method suffers from a number of inherent limitations that have a significant impact on its capability in faithfully constructing fiber bundles for specific function. In this paper, a novel tractography algorithm combining DWI and functional MRI (fMRI) was proposed. Specifically, a spatio-temporal correlation tensor that characterizes the anisotropy of fMRI signals in white matter was introduced to complement the estimation of fiber orientation density function from DWI. The proposed method has been demonstrated to identify functional pathways implicated in fMRI task. It can effectively follow tracts in the genu of the corpus callosum that connects to the frontal lobe cortex, obtain connections between the thalamus and the anterior insula under sensory simulation, and reconstruct optic radiations in the visual circuit under visual stimulation. Taken together, the method we proposed in this work may benefit our understanding of structure-function relations in the human brain.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • A Novel Synchronous Micro Motor for Intravascular Ultrasound Imaging
    • Authors: Jue Peng;Lucai Ma;Xiaozhen Li;Hu Tang;Yunfei Li;Siping Chen;
      Pages: 802 - 809
      Abstract: Objective: Intravascular ultrasound (IVUS) is an important method for evaluating lumen dimensions and guiding intervention. However, the current IVUS catheter using a proximal motor and flexible drive shaft is easily rotated at an unstable speed when it passes through along bending vessel. One approach to solve this problem is to develop a catheter driven by a distal motor. Methods: This paper presents a rotation device incorporating a high-frequency transducer as an attempt to facilitate this approach. A novel micro distal synchronous micro motor with 3.7 mm length and 1.2 mm outer diameter was proposed as an actuator for the IVUS catheter. A 0.5 mm × 0.5 mm Pb(Mg1/3Nb2/3)O3–PbTiO3 single crystal 1–3 composite single-element transducer was designed and manufactured. The probe is fixed to the front end of the catheter. The 45° reflector, which is opposite to the probe, was used to steer ultrasound to the tissue. Results: The results showed that the maximum torque and rotation speed of the motor were 2.79 μNm and 275 revolutions per second, respectively, at a driving current of 0.34 A. The maximum angular error was 7° at 0.13 A and 30 Hz. The center frequency and −6 dB fractional bandwidth of single element were 34 MHz and 72%, respectively. At the center frequency, the two-way insertion loss was 14 dB. Conclusion: The integrated distal motor IVUS catheter, with small dimensions, a good torque, speed stability, and good ultrasound imaging performance, has tremendous potential in blood vessel imaging. Significance: The novel structure of the catheter could facilitate endoluminal sonography, reducing risks of the clinical diagnosis.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Wearable Sensors for Frequency-Multiplexed EIT and Multilead ECG Data
    • Authors: Michael Rapin;Fabian Braun;Andy Adler;Josias Wacker;Inéz Frerichs;Barbara Vogt;Olivier Chételat;
      Pages: 810 - 820
      Abstract: This paper presents a wearable sensor architecture for frequency-multiplexed electrical impedance tomography (EIT) and synchronous multilead electrocardiogram (ECG) data acquisition. The system is based on a novel electronic sensing architecture, called cooperative sensors, that significantly reduces the cabling complexity and enables flexible EIT stimulation and measurement patterns. The cooperative-sensor architecture was initially designed for ECG and has been extended for multichannel bioimpedance measurement. This approach allows for an adjustable EIT stimulation pattern via frequency-division multiplexing. This paper also shows a calibration procedure as well as EIT system noise performance assessment. Preliminary measurements on a healthy volunteer showed the ability of the wearable system to measure EIT data synchronously with multilead ECG. Ventilation-related and heartbeat-related EIT images were reconstructed, demonstrating the feasibility of the proposed architecture for noninvasive cardiovascular monitoring.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Noninvasive Quantification of Cell Density in Three-Dimensional Gels by
    • Authors: Brian J. Archer;Till Überrück;Julia J. Mack;Khalid Youssef;Nanette N. Jarenwattananon;Deniz Rall;Denis Wypysek;Martin Wiese;Bernhard Blümich;Matthias Wessling;M. Luisa Iruela-Arispe;Louis-S. Bouchard;
      Pages: 821 - 830
      Abstract: Objective: For tissue engineering, there is a need for quantitative methods to map cell density inside three-dimensional (3-D) bioreactors to assess tissue growth over time. The current cell mapping methods in 2-D cultures are based on optical microscopy. However, optical methods fail in 3-D due to increased opacity of the tissue. We present an approach for measuring the density of cells embedded in a hydrogel to generate quantitative maps of cell density in a living, 3-D tissue culture sample. Methods: Quantification of cell density was obtained by calibrating the $boldsymbol {^1}$H $boldsymbol {T_2}$, magnetization transfer (MT) and diffusion-weighted nuclear magnetic resonance (NMR) signals to samples of known cell density. Maps of cell density were generated by weighting NMR images by these parameters post-calibration. Results: The highest sensitivity weighting arose from MT experiments, which yielded a limit of detection (LOD) of ${ {boldsymbol{2.5}} times {text{10}}^8}$ cells/mL/$sqrt{hbox{Hz}}$ in a 400 MHz (9.4 T) magnet. Conclusion: This mapping technique provides a noninvasive means of visualizing cell growth within optically opaque bioreactors. Significance: We anticipate that such readouts of tissue culture growth will provide valuable feedback for controlled cell growth in bioreactors.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Background Removal and Vessel Filtering of Noncontrast Ultrasound Images
           of Microvasculature
    • Authors: Mahdi Bayat;Mostafa Fatemi;Azra Alizad;
      Pages: 831 - 842
      Abstract: Objective: Recent advances in ultrasound Doppler imaging have made it possible to visualize small vessels with diameters near the imaging resolution limits using spatiotemporal singular value thresholding of long ensembles of ultrasound data. However, vessel images derived based on this method present severe intensity variations and additional background noise that limits visibility and subsequent processing such as centerline extraction and morphological analysis. The goal of this paper is to devise a method to enhance vessel-background separation directly on the power Doppler images by exploiting blood echo-noise independence. Method: We present a two-step algorithm to mitigate these adverse effects when using singular value thresholding for obtaining gross vasculature images. Our method comprises a morphological-based filtering for removing global and local background signals and a multiscale Hessian-based vessel enhancement filtering to further improve the vascular structures. We applied our method for in vivo imaging of the microvasculature of kidney in one healthy subject, liver in five healthy subjects, thyroid nodules in five patients, and breast tumors in five patients. Results: Singular value thresholding, top-hat filtering, and Hessian-based vessel enhancement filtering each provided an average peak-to-side level gain of 1.11, 18.55, and 2.26 dB, respectively, resulting in an overall gain of 21.92 dB when compared to the conventional power Doppler imaging using infinite impulse response filtering. Conclusion: Singular value thresholding combined with morphological and Hessian-based vessel enhancement filtering provides a powerful tool for visualization of the deep-seated small vessels using long ultrasound echo ensembles without requiring any type of contrast enhancing agents. Significance: This method provides a fas- and cost-effective modality for in vivo assessment of the microvasculature suitable for both clinical and preclinical applications.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Intravenous Administration-Oriented Pharmacokinetic Model for Dynamic
           Bioluminescence Imaging
    • Authors: Yunpeng Dai;Guodong Wang;Duofang Chen;Jipeng Yin;Yonghua Zhan;Yongzhan Nie;Kaichun Wu;Jimin Liang;Xueli Chen;
      Pages: 843 - 847
      Abstract: Objective: In vivo bioluminescence imaging (BLI) is a promising tool for monitoring the growth and metastasis of tumors. However, quantitative BLI research based on intravenous (IV) injection is limited, which greatly restricts its further application. To address this problem, we designed a pharmacokinetic (PK) model which is suitable for applying on IV administration of small amounts of D-Luciferin. Methods: After three weeks of postimplantation, mkn28-luc xenografted mice were subjected to 40-min dynamic BLI immediately following D-Luciferin intravenous injection on days 1, 3, 5, 7, and 9. Furthermore, the PK model was applied on dynamic BLI data to obtain the sum of kinetic rate constants (SKRC). Results: Results showed that the SKRC values decreased rapidly with the growth of the tumor. There was a statistical difference between the SKRC values measured at different time points, while the time point of luminous intensity peak was unaffected by the growth of the tumor. Conclusion: In short, our results imply that dynamic BLI combined with our PK model can predict tumor growth earlier and with higher sensitivity compared to the conventional method, which is crucial for improving drug evaluation efficacy. In addition, the dynamic BLI may provide a valuable reference for the noninvasive acquiring arterial input function, which may also provide a new application prospect for hybrid PET-optical imaging.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Efficient Bronchoscopic Video Summarization
    • Authors: Patrick D. Byrnes;William Evan Higgins;
      Pages: 848 - 863
      Abstract: Bronchoscopy enables many minimally invasive chest procedures for diseases such as lung cancer and asthma. Guided by the bronchoscope's video stream, a physician can navigate the complex three-dimensional (3-D) airway tree to collect tissue samples or administer a disease treatment. Unfortunately, physicians currently discard procedural video because of the overwhelming amount of data generated. Hence, they must rely on memory and anecdotal snapshots to document a procedure. We propose a robust automatic method for summarizing an endobronchial video stream. Inspired by the multimedia concept of the video summary and by research in other endoscopy domains, our method consists of three main steps: 1) shot segmentation, 2) motion analysis, and 3) keyframe selection. Overall, the method derives a true hierarchical decomposition, consisting of a shot set and constituent keyframe set, for a given procedural video. No other method to our knowledge gives such a structured summary for the raw, unscripted, unedited videos arising in endoscopy. Results show that our method more efficiently covers the observed endobronchial regions than other keyframe-selection approaches and is robust to parameter variations. Over a wide range of video sequences, our method required on average only 6.5% of available video frames to achieve a video coverage = 92.7%. We also demonstrate how the derived video summary facilitates direct fusion with a patient's 3-D chest computed-tomography scan in a system under development, thereby enabling efficient video browsing and retrieval through the complex airway tree.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Effect of Region of Interest Size on the Repeatability of Quantitative
           Brain Imaging Biomarkers
    • Authors: Kourosh Jafari-Khouzani;Kamran Paynabar;Fatemeh Hajighasemi;Bruce Rosen;
      Pages: 864 - 872
      Abstract: In the repeatability analysis, when the measurement is the mean value of a parametric map within a region of interest (ROI), the ROI size becomes important as by increasing the size, the measurement will have a smaller variance. This is important in decision-making in prospective clinical studies of brain when the ROI size is variable, e.g., in monitoring the effect of treatment on lesions by quantitative MRI, and in particular when the ROI is small, e.g., in the case of brain lesions in multiple sclerosis. Thus, methods to estimate repeatability measures for arbitrary sizes of ROI are desired. We propose a statistical model of the values of parametric map within the ROI and a method to approximate the model parameters, based on which we estimate a number of repeatability measures including repeatability coefficient, coefficient of variation, and intraclass correlation coefficient for an ROI with an arbitrary size. We also show how this gives an insight into related problems such as spatial smoothing in voxel-wise analysis. Experiments are conducted on simulated data as well as on scan–rescan brain MRI of healthy subjects. The main application of this study is the adjustment of the decision threshold based on the lesion size in treatment monitoring.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Ultrasound Measurement of Vascular Density to Evaluate Response to
           Anti-Angiogenic Therapy in Renal Cell Carcinoma
    • Authors: Juan D. Rojas;Virginie Papadopoulou;Tomasz J. Czernuszewicz;Rajalekha M. Rajamahendiran;Anna Chytil;Yun-Chen Chiang;Diana C. Chong;Victoria L. Bautch;W. Kimryn Rathmell;Stephen Aylward;Ryan C. Gessner;Paul A. Dayton;
      Pages: 873 - 880
      Abstract: Background: Functional and molecular changes often precede gross anatomical changes, so early assessment of a tumor's functional and molecular response to therapy can help reduce a patient's exposure to the side effects of ineffective chemotherapeutics or other treatment strategies. Objective: Our intent was to test the hypothesis that an ultrasound microvascular imaging approach might provide indications of response to therapy prior to assessment of tumor size. Methods: Mice bearing clear-cell renal cell carcinoma xenograft tumors were treated with antiangiogenic and Notch inhibition therapies. An ultrasound measurement of microvascular density was used to serially track the tumor response to therapy. Results: Data indicated that ultrasound-derived microvascular density can indicate response to therapy a week prior to changes in tumor volume and is strongly correlated with physiological characteristics of the tumors as measured by histology ($rho = {text{0.75}}$). Furthermore, data demonstrated that ultrasound measurements of vascular density can determine response to therapy and classify between-treatment groups with high sensitivity and specificity. Conclusion/Significance: Results suggests that future applications utilizing ultrasound imaging to monitor tumor response to therapy may be able to provide earlier insight into tumor behavior from metrics of microvascular density rather than anatomical tumor size measurements.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Nonlinear Mixed-Effects Models for PET Data
    • Authors: Yakuan Chen;Jeff Goldsmith;R. Todd Ogden;
      Pages: 881 - 891
      Abstract: Objective: The current state-of-the-art for compartment modeling of dynamic PET data can be described as a two-stage approach. In Stage 1, individual estimates of kinetic parameters are obtained by fitting models using standard techniques, such as nonlinear least squares, to each individual's data one subject at a time. Population-level effects, such as the difference between diagnostic groups, are analyzed in Stage 2 using standard statistical methods by treating the individual estimates as if they were observed data. While this approach is generally valid, it is possible to increase efficiency and precision of the analysis, allow more complex models to be fitted, and also to permit parameter-specific investigation by fitting data across subjects simultaneously. We explore the application of nonlinear mixed-effects (NLME) models for estimation and inference in this setting. Methods: In the NLME framework, subjects are modeled simultaneously through the inclusion of random effects of subjects for each kinetic parameter; meanwhile, population parameters are estimated directly in a joint model. Results: Simulation results indicate that NLME outperforms the two-stage approach in estimating group-level effects and also has improved power to detect differences across groups. We applied our NLME approach to clinical PET data and found effects not detected by the two-stage approach. Conclusion: The proposed NLME approach is more accurate and correspondingly more powerful than the two-stage approach in compartment modeling of PET data. Significance: The NLME method can broaden the methodological scope of PET modeling because of its efficiency and stability.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
  • Validation and Use of a Musculoskeletal Gait Model to Study the Role of
           Functional Electrical Stimulation
    • Authors: Ziyun Ding;Nur Liyana Azmi;Anthony M. J. Bull;
      Pages: 892 - 897
      Abstract: Objective: Musculoskeletal modeling has been used to predict the effect of functional electrical stimulation (FES) on the mechanics of the musculoskeletal system. However, validation of the resulting muscle activations due to FES is challenging as conventional electromyography (EMG) recording of signals from the stimulated muscle is affected by stimulation artefacts. A validation approach using a combination of musculoskeletal modeling and EMG was proposed, whereby the effect on nonstimulated muscles is assessed using both techniques. The aim is to quantify the effect of FES on biceps femoris long head (BFLH) and validate this directly against EMG of gluteus maximus (GMAX). The hypotheses are that GMAX activation correlates with BFLH activation; and the muscle activation during FES gait can be predicted using musculoskeletal modeling. Methods: Kinematics, kinetics, and EMG of healthy subjects were measured under four walking conditions (normal walking followed by FES walking with three levels of BFLH stimulation). Measured kinematics and kinetics served as inputs to the musculoskeletal model. Results: Strong positive correlations were found between GMAX activation and BFLH activation in early stance peak (R = 0.78, p = 0.002) and impulse (R = 0.63, p = 0.021). The modeled peak and impulse of GMAX activation increased with EMG peak (p < 0.001) and impulse (p = 0.021). Conclusion: Musculoskeletal modeling can be used reliably to quantify the effect of FES in a healthy gait. Significance: The validation approach using EMG and musculoskeletal modeling developed and tested can potentially be applied to the use of FES for other muscles and activities.
      PubDate: March 2019
      Issue No: Vol. 66, No. 3 (2019)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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