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  Subjects -> ELECTRONICS (Total: 184 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: 6)
Advances in Electronics     Open Access   (Followers: 79)
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: 319)
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: 270)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 106)
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: 93)
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: 198)
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: 67)
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: 20)
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: 70)
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: 25)
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: 4)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 6)
International Journal of Control     Hybrid Journal   (Followers: 11)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 2)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Hybrid Intelligence     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 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: 25)
Journal of Electrical Bioimpedance     Open Access  
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 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   (Followers: 2)
Journal of Field Robotics     Hybrid Journal   (Followers: 3)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 170)
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: 29)
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 ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
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: 19)
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)
Revue Méditerranéenne des Télécommunications     Open Access  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 54)
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: June 2019
      Issue No: Vol. 66, No. 6 (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: June 2019
      Issue No: Vol. 66, No. 6 (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: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • IEEE Transactions on Biomedical Engineering Handling Editors
    • Abstract: Presents a listing of the handling editors for this issue of the publication.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • A Patient-Specific Approach for Short-Term Epileptic Seizures Prediction
           Through the Analysis of EEG Synchronization
    • Authors: Paolo Detti;Garazi Zabalo Manrique de Lara;Renato Bruni;Marco Pranzo;Francesco Sarnari;Giampaolo Vatti;
      Pages: 1494 - 1504
      Abstract: Epilepsy is a neurological disorder arising from anomalies of the electrical activity in the brain, affecting about 65 millions individuals worldwide. Objective: This paper proposes a patient-specific approach for short-term prediction (i.e., within few minutes) of epileptic seizures. Methods: We use noninvasive EEG data, since the aim is exploring the possibility of developing a noninvasive monitoring/control device for the prediction of seizures. Our approach is based on finding synchronization patterns in the EEG that allow to distinguish in real time preictal from interictal states. In practice, we develop easily computable functions over a graph model to capture the variations in the synchronization, and employ a classifier for identifying the preictal state. Results: We compare two state-of-the-art classification algorithms and a simple and computationally inexpensive threshold-based classifier developed ad hoc. Results on publicly available scalp EEG database and on scalp data of the patients of the Unit of Neurology and Neurophysiology at University of Siena show that this simple and computationally viable processing is able to highlight the changes in synchronization when a seizure is approaching. Conclusion and significance: The proposed approach, characterized by low computational requirements and by the use of noninvasive techniques, is a step toward the development of portable and wearable devices for real-life use.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • A Wearable Pulse Oximeter With Wireless Communication and Motion Artifact
           Tailoring for Continuous Use
    • Authors: Pedro J. Chacon;Limeng Pu;Tallis H. da Costa;Young-Ho Shin;Taher Ghomian;Hamed Shamkhalichenar;Hsiao-Chun Wu;Brian A. Irving;Jin-Woo Choi;
      Pages: 1505 - 1513
      Abstract: Advances in several engineering fields have led to a trend toward miniaturization and portability of wearable biosensing devices, which used to be confined to large tools and clinical settings. Various systems to continuously measure electrophysiological activity through electrical and optical methods are one category of such devices. Being wearable and intended for prolonged use, the amount of noise introduced on sensors by movement remains a challenge and requires further optimization. User movement causes motion artifacts that alter the overall quality of the signals obtained, hence corrupting the resulting measurements. This paper introduces a fully wearable optical biosensing system to continuously measure pulse oximetry and heart rate, utilizing a reflectance-based probe. Furthermore, a novel data-dependent motion artifact tailoring algorithm is implemented to eliminate noisy data due to the motion artifact and measure oxygenation level with high accuracy in real time. By taking advantages of current wireless transmission and signal processing technologies, the developed wearable photoplethysmography device successfully captures the measured signals and sends them wirelessly to a mobile device for signal processing in real time. After applying motion artifact tailoring, evaluating accuracy with a continuous clinical device, the blood oxygenation measurements obtained from our system yielded an accuracy of at least 98%, when compared to a range of 93.6%-96.7% observed before from the same initial data. Additionally, heart rate accuracy above 97% was achieved. Motion artifact tailoring and removal in real time, continuous systems will allow wearable devices to be truly wearable and a reliable electrophysiological monitoring and diagnostics tool for everyday use.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Multi-Wavelength Photoplethysmography Enabling Continuous Blood Pressure
           Measurement With Compact Wearable Electronics
    • Authors: Jing Liu;Bryan P. Yan;Yuan-Ting Zhang;Xiao-Rong Ding;Peng Su;Ni Zhao;
      Pages: 1514 - 1525
      Abstract: Objective: To fight the “silent killer” hypertension, continuous blood pressure (BP) monitoring has been one of the most desired functions in wearable electronics. However, current BP measuring principles and protocols either involve a vessel occlusion process with a cuff or require multiple sensing nodes on the body, which makes it difficult to implement them in compact wearable electronics like smartwatches and wristbands with long-term wearability. Methods: In this work, we proposed a highly compact multi-wavelength photoplethysmography (MWPPG) module and a depth-resolved MWPPG approach for continuous monitoring of BP and systemic vascular resistance (SVR). By associating the wavelength-dependent light penetration depth in the skin with skin vasculatures, our method exploited the pulse transit time (PTT) on skin arterioles for tracking SVR (n = 20). Then, we developed an arteriolar PTT-based method for beat-to-beat BP measurement. The BP estimation accuracy of the proposed arteriolar PTT method was validated against Finometer (n = 20) and the arterial line (n = 4). Results: The correlation between arteriolar PTT and SVR was theoretically deduced and experimentally validated on 20 human subjects performing various maneuvers. The proposed arteriolar PTT-based method outperformed the traditional arterial PTT-based method with better BP estimation accuracy and simpler measurement setup, i.e., with a single sensing node. Conclusion: The proposed depth-resolved MWPPG method can provide accurate measurements of SVR and BP, which are traditionally difficult to measure in a noninvasive or continuous fashion. Significance: This MWPPG work provides the wearable healthcare electronics of compact size with a low-cost and physiology-based solution for continuous measurement of BP and SVR.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Magnetic Resonance Fingerprinting Using a Fast Dictionary Searching
           Algorithm: MRF-ZOOM
    • Authors: Ze Wang;Jian Zhang;Di Cui;Jun Xie;Mengye Lyu;Edward S. Hui;Ed. X. Wu;
      Pages: 1526 - 1535
      Abstract: Objective: Magnetic resonance fingerprinting (MRF) is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan. In MRF, MR signal is manipulated to have distinct temporal behavior with regard to different combinations of the underlying MR parameters and across spatial regions. The temporal behavior of acquired MR signal is then used as a key to find its unique counterpart in a MR signal dictionary. The dictionary generation and searching (DGS) process represents the most important part of MRF, which however can be intractable because of the disk space requirement and the computational demand exponentially increases with the number of MR parameters, spatial coverage, and spatial resolution. The goal of this paper was to develop a fast and space efficient MRF DGS algorithm. Methods: The optimal DGS algorithm: MRF ZOOM was designed based on the properties of the parameter matching objective function characterized with full dictionary simulations. Both synthetic data and in-vivo data were used to validate the method. Conclusion: MRF ZOOM can dramatically save MRF DGS time without sacrificing matching accuracy. Significance: MRF ZOOM can facilitate a wide range of MRF applications.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Highly Efficient Isolation of Circulating Tumor Cells Using a Simple
           Wedge-Shaped Microfluidic Device
    • Authors: Luman Qin;Wei Zhou;Shoukun Zhang;Boran Cheng;Shubin Wang;Songzhan Li;Yanqin Yang;Shengxiang Wang;Kan Liu;Nangang Zhang;
      Pages: 1536 - 1541
      Abstract: Objective: We have developed a novel simple wedge-shaped microfluidic device for highly efficient isolation of circulating tumor cells (CTCs) from cancer patient blood samples. Methods: We used wet chemical etching and thermal bonding technologies to fabricate the wedge-shaped microdevice and performed optimization assays to obtain optimal capture parameters. Cancer cells spiked samples were used to evaluate the capture performance. Clinical assays were performed to isolate and identify CTCs from whole blood samples of patients with liver, breast, lung, and gastric cancer. Results: Outlet height of 5.5 μm and flow rate of 200 μL/min were chosen as the optimal CTC-capture conditions. This method exhibited excellent isolation performance (more than 85% capture efficiency) for four cancer cell lines (HepG2, SKBR3, A549, and BGC823). In clinical assay, the platform identified CTCs 5 in 6 liver (83.3%), 8 in 10 breast (80%), 5 in 8 lung (62.5%), 5 in 9 gastric (55.6%) cancer patients, and only 1 in 25 healthy blood samples (4%). Conclusion: Our wedge-shaped microfluidic device had several advantages, including relatively simple fabrication, high capture efficiency, simple sample processing steps, and easy observation. Significance: This method had successfully demonstrated the clinical feasibility of CTC isolation and shown a great potential of clinical usefulness in monitoring tumor prognosis and guiding individualized treatment in the future.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • On the Bending and Stretching of Liquid Metal Receive Coils for Magnetic
           Resonance Imaging
    • Authors: Andreas Mehmann;Matija Varga;Christian Vogt;Andreas Port;Jonas Reber;Josip Marjanovic;Klaas Paul Pruessmann;Gerhard Tröster;
      Pages: 1542 - 1548
      Abstract: The eGaIn coil on neoprene demonstrated in this paper presents a stretchable radio frequency receive coil for magnetic resonance imaging (MRI). The coil with dimensions $text{86 mm}times text{70 mm}$ is tuned to resonate at 128 MHz for 3 T MRI. We investigate the effect of stretching (up to 40% strain) and bending (50 mm radius of curvature) of the coil on the coil's resistance and resonance frequency. Measurements and simulations show a decrease in resonance frequency of 2.5 MHz per 10% strain. The higher resistivity of liquid metal compared to copper reduces the SNR of MRI scans by 34%; therefore, a tradeoff between flexibility and performance remains. Nevertheless, we have successfully performed MRI scans with the liquid metal coil.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Scalable and Robust Tensor Decomposition of Spontaneous Stereotactic EEG
           Data
    • Authors: Jian Li;Justin P. Haldar;John C. Mosher;Dileep R. Nair;Jorge A. Gonzalez-Martinez;Richard M. Leahy;
      Pages: 1549 - 1558
      Abstract: Objective: Identification of networks from resting brain signals is an important step in understanding the dynamics of spontaneous brain activity. We approach this problem using a tensor-based model. Methods: We develop a rank-recursive scalable and robust sequential canonical polyadic decomposition (SRSCPD) framework to decompose a tensor into several rank-1 components. Robustness and scalability are achieved using a warm start for each rank based on the results from the previous rank. Results: In simulations we show that SRSCPD consistently outperforms the multi-start alternating least square (ALS) algorithm over a range of ranks and signal-to-noise ratios (SNRs), with lower computation cost. When applying SRSCPD to resting in-vivo stereotactic EEG (SEEG) data from two subjects with epilepsy, we found components corresponding to default mode and motor networks in both subjects. These components were also highly consistent within subject between two sessions recorded several hours apart. Similar components were not obtained using the conventional ALS algorithm. Conclusion: Consistent brain networks and their dynamic behaviors were identified from resting SEEG data using SRSCPD. Significance: SRSCPD is scalable to large datasets and therefore a promising tool for identification of brain networks in long recordings from single subjects.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • A Single-Scan Inhomogeneity-Tolerant NMR Method for High-Resolution
           Two-Dimensional J-Resolved Spectroscopy
    • Authors: Haolin Zhan;Xiaoqing Lin;Zhiliang Wei;Qimiao Ye;Shuhui Cai;Xueqiu You;Yuqing Huang;Zhong Chen;
      Pages: 1559 - 1566
      Abstract: Objective: A robust and general single-scan NMR method, SGEN-J, is proposed for real-time recording high-resolution two-dimensional (2D) homonuclear J-resolved spectra under inhomogeneous magnetic fields. Methods: This proposed NMR method is designed based on the combination of a selective gradient encoding module to encode chemical shifts with spatial positions, and a J-modulation decoding module to reveal encoded structural information. Multi-band SGEN-J is further implemented to effectively enhance spectral sensitivity with a sustained tolerance of field inhomogeneity. Results: The SGEN-J provides an effective way to rapidly recover chemical shifts, J coupling constants, and multiplet patterns under inhomogeneous magnetic fields. Experiments on various chemical solutions were performed to demonstrate the feasibility and effectiveness of SGEN-J. Experiments on pig marrow tissues were performed to further investigate the applicability of SGEN-J to biological samples with intrinsic susceptibility variations. Conclusion: Based on intrinsic advantages, SGEN-J serves as a helpful complement to existing 2D J-resolved methodologies in molecular structure elucidation and biomedical study, and offer bright perspectives for real-time analyzing in vivo biological systems and monitoring in situ chemical reactions.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Three-Dimensional Whole Breast Segmentation in Sagittal and Axial Breast
           MRI With Dense Depth Field Modeling and Localized Self-Adaptation for
           Chest-Wall Line Detection
    • Authors: Dong Wei;Susan Weinstein;Meng-Kang Hsieh;Lauren Pantalone;Despina Kontos;
      Pages: 1567 - 1579
      Abstract: Objective: Whole breast segmentation is an essential task in quantitative analysis of breast MRI for cancer risk assessment. It is challenging, mainly, because the chest-wall line (CWL) can be very difficult to locate due to its spatially varying appearance-caused by both nature and imaging artifacts-and neighboring distracting structures. This paper proposes an automatic three-dimensional (3-D) segmentation method, termed DeepSeA, of whole breast for breast MRI. Methods: DeepSeA distinguishes itself from previous methods in three aspects. First, it reformulates the challenging problem of CWL localization as an equivalent problem that optimizes a smooth depth field and so fully utilizes the CWL's 3-D continuity. Second, it employs a localized self-adapting algorithm to adjust to the CWL's spatial variation. Third, it applies to breast MRI data in both sagittal and axial orientations equally well without training. Results: A representative set of 99 breast MRI scans with varying imaging protocols is used for evaluation. Experimental results with expert-outlined reference standard show that DeepSeA can segment breasts accurately: the average Dice similarity coefficients, sensitivity, specificity, and CWL deviation error are 96.04%, 97.27%, 98.77%, and 1.63 mm, respectively. In addition, the configuration of DeepSeA is generalized based on experimental findings, for application to broad prospective data. Conclusion: A fully automatic method-DeepSeA-for whole breast segmentation in sagittal and axial breast MRI is reported. Significance: DeepSeA can facilitate cancer risk assessment with breast MRI.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Eco-Friendly Highly Sensitive Transducers Based on a New KNN–NTK–FM
           Lead-Free Piezoelectric Ceramic for High-Frequency Biomedical Ultrasonic
           Imaging Applications
    • Authors: Ruimin Chen;Laiming Jiang;Tianfu Zhang;Takayuki Matsuoka;Masato Yamazaki;Xuejun Qian;Gengxi Lu;Ahmad Safari;Jianguo Zhu;K. Kirk Shung;Teng Ma;Qifa Zhou;
      Pages: 1580 - 1587
      Abstract: High-frequency ultrasonic imaging with improved spatial resolution has gained increasing attention in the field of biomedical imaging. Sensitivity of transducers plays a pivotal role in determining ultrasonic image quality. Conventional ultrasonic transducers are mostly made from lead-based piezoelectric materials that may be harmful to the human body and the environment. In this study, a new (K,Na)NbO3-KTiNbO5-BaZrO3-Fe2O3-MgO (KNN-NTK-FM) lead-free piezoelectric ceramic was utilized in developing eco-friendly transducers for high-frequency biomedical ultrasonic imaging applications. A needle transducer with a small active aperture size of 0.45 × 0.55 mm2 was designed and evaluated. The fabricated transducer exhibits great performance with a high center frequency (52.6 MHz), a good electromechanical coupling (keff ~ 0.45), a large bandwidth (64.4% at -6 dB), and a very low two-way insertion loss (10.1 dB). Such high sensitivity is superior to those transducers based on other lead-free piezoelectric materials and can even be comparable to the lead-based ones. Imaging performance of the KNN-NTK-FM needle transducer was analyzed by imaging a wire phantom and an agar tissue-mimicking phantom. Imaging capabilities of the transducer were further demonstrated by ex vivo imaging studies on a porcine eyeball and a rabbit aorta. The results suggest that the KNN-NTK-FM piezoceramic has many attractive properties over other lead-free piezoelectric materials in developing eco-friendly highly sensitive transducers for high-frequency biomedical ultrasonic imaging applications.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Continuous Wavelet Transform for Decoding Finger Movements From
           Single-Channel EEG
    • Authors: Jacob B. Salyers;Yue Dong;Yan Gai;
      Pages: 1588 - 1597
      Abstract: Human body movements can be reflected in brain signals and collected noninvasively with electroencephalography (EEG). Motor-related signals include sensory motor rhythms (also known as the Mu wave) in the upper-alpha band of 8-13 Hz and slow cortical potentials (SCPs) in the low frequency range of 0.1-5 Hz. This study compares the two signals for decoding finger movements. Human subjects were asked to individually lift each of the five digits of their right hand, at the rate of one every 10 s. EEG was recorded using a bipolar montage between ipsilateral and contralateral motor cortices. Electromyograms were obtained for identifying movement onsets. Linear discriminant analysis (LDA) generated significant performance with SCPs but not with Mu. Meanwhile, continuous wavelet transform (CWT) was applied to SCPs or Mu to create a spectrogram for each finger, showing distinctive amplitude and phase patterns. A dprime-based weighting algorithm was used to extract time-frequency features. With a template-matching paradigm, both SCP and Mu spectrograms yielded significant classification accuracies for multiple subjects, with the highest being>50% (chance = 20%). Interestingly, the index finger was better distinguished with Mu for most of the subjects, whereas the ring finger was better distinguished with SCPs. The CWT algorithm outperformed LDA by better decoding the thumb. This study suggests that the time-frequency characteristics of a single-channel EEG, when phase is preserved, contain critical information on finger movements. SCPs and Mu seem to work in an independent but complementary manner.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Thermoacoustic Tomography of In Vivo Human Finger Joints
    • Authors: Zihui Chi;Yuan Zhao;Jinge Yang;Tingting Li;Guang Zhang;Huabei Jiang;
      Pages: 1598 - 1608
      Abstract: Objective: the purpose of this study was to demonstrate the potential of thermoacoustic tomography (TAT) to reveal anatomic structures of in vivo human finger joints. Methods: all the participating volunteers provided written informed consent. Eight healthy middle and index fingers from five volunteers were imaged in vivo by our TAT imaging system. Axial T1-weighted MR imaging (3.0 T) was used to validate the TAT findings. Comparative analyses between TAT and MRI images were performed in two dimension for all the fingers imaged. Three-dimensional (3-D) images and animations were also obtained for some of the fingers thermoacoustically scanned. Results: various intra- and extra-articular tissues were identified in TAT images in high fidelity. These TAT images matched well with the MRI images. Both the 3-D images and animations effectively displayed the extension and transformation of the entire finger along the axis. Conclusion: TAT can noninvasively visualize anatomic structures of the finger joints based on the electrical properties of the joint tissues. The results obtained indicate that TAT may have the potential to contribute to the detection of joint and bone diseases. Significance: this study represents the first for TAT of in vivo human joints and fingers. This study reveals that TAT can effectively recover both soft and hard tissues of the healthy interphalangeal joints, which provides a foundation for its clinical application to detection and diagnosis of joint and bone diseases.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Mechanical Effects of Cochlear Implant on Acoustic Hearing
    • Authors: Wei Xuan Chan;Yong-Jin Yoon;Choongsoo S. Shin;Namkeun Kim;
      Pages: 1609 - 1617
      Abstract: Residual hearing loss in cochlear implant users is investigated using the mechanical-human-cochlear model. Hearing loss due to stiffening of the round window increases significantly as input frequencies decrease from 3 kHz to 1 kHz but remains constant at lower frequencies, whereas loss due to the presence of an electrode insert becomes significantly higher at lower frequencies (
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Hydraulic Characterization of Implantable Rotary Blood Pumps
    • Authors: Stefan Boës;Bente Thamsen;Mattia Haas;Marianne Schmid Daners;Mirko Meboldt;Marcus Granegger;
      Pages: 1618 - 1627
      Abstract: Objective: The hydraulic properties of implantable rotary blood pumps (RBPs) determine their interaction with the cardiovascular system. A systematic comparison in this regard has not yet been performed for different clinically used RBPs. The aim of this study is to describe the hydraulic characteristics of four RBPs with a universal mathematical model and to compare their behavior under clinical operating conditions. Methods: First, static and dynamic pump properties of four RBPs (HVAD, Heartmate II, Heartmate 3, and Incor) including their peripheral components were identified in an in vitro setup; results were translated into mathematical models based on principles of turbomachinery including the low and backflow regions. Second, the four hydraulic models were compared in a numerical simulation of the cardiovascular system for full- and partial-support conditions. Results: A model structure applicable to each of the investigated RBPs was developed. Deviations between simulated and measured signals for static and dynamic properties were small (2.6 ± 0.5 mmHg, 0.38 ± 0.14 L/min, respectively). For a simulated partial support condition, flow pulsatility ranged from 4.1 (Incor) to 9.1 L/min (HVAD). Negative flow rates during diastole were observed in three out of four pumps. Conclusion: Hydraulic properties differ greatly between the investigated RBPs, with flat characteristics for the HVAD and Heartmate II and steeper curves for the Heartmate 3 and especially the Incor. Significance: Hydraulic characteristics of implantable RBPs are particularly important at lower pump flow rates if backflow is to be avoided. For further research, we provide dynamic hydraulic models of the four RBPs including their periphery.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Numerical Design of High-Efficiency Whole-Body Gradient Coils With a
           Hybrid Cylindrical-Planar Structure
    • Authors: Chaoqun Niu;Qiuliang Wang;Yang Hu;Yaohui Wang;Fangfang Tang;Feng Liu;Stuart Crozier;
      Pages: 1628 - 1636
      Abstract: In this paper, a set of novel whole-body gradient coils is designed for cylindrical magnetic resonance imaging (MRI) systems. For the sake of high coil efficiency, the design scheme focuses on the imaging volume occupied by the patient, discounting the large space under the patient bed that is unused during imaging. To further improve the coil performance, the coils are designed on an unconventional, hybrid cylindrical-planar structure, where the primary coils are arranged on a chord-truncated cylindrical former while the shielding coils remain on the cylindrical assemblies. In this new coil configuration, the primary layers make the best possible use of the space closest to the imaging volume, whilst the shielding layers are positioned the furthest from the primary layers; thus, the best gradient field/current ratio can be obtained for the body coil configuration. Using a boundary element method, a full gradient set was designed to demonstrate the effectiveness of the proposed scheme. Compared with conventional designs, the new approach provides significantly improved coil performance. For the three gradient axes, the inductance was reduced by 25%-50%, the resistance was decreased by 19%-39%, and the minimum wire distance was increased by 5.2%-45.5%. In terms of shielding effect, the maximum stray fields of the X- and Y-gradient coils are reduced by 79.5% and 38.7%, respectively. It is concluded that the new design is capable of producing high-quality gradients with less eddy currents and thermal heating concerns, being suitable for MRI applications demanding a high gradient performance.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Ultrasound Image Segmentation: A Deeply Supervised Network With Attention
           to Boundaries
    • Authors: Deepak Mishra;Santanu Chaudhury;Mukul Sarkar;Arvinder Singh Soin;
      Pages: 1637 - 1648
      Abstract: Objective: Segmentation of anatomical structures in ultrasound images requires vast radiological knowledge and experience. Moreover, the manual segmentation often results in subjective variations, therefore, an automatic segmentation is desirable. We aim to develop a fully convolutional neural network (FCNN) with attentional deep supervision for the automatic and accurate segmentation of the ultrasound images. Method: FCNN/CNNs are used to infer high-level context using low-level image features. In this paper, a sub-problem specific deep supervision of the FCNN is performed. The attention of fine resolution layers is steered to learn object boundary definitions using auxiliary losses, whereas coarse resolution layers are trained to discriminate object regions from the background. Furthermore, a customized scheme for downweighting the auxiliary losses and a trainable fusion layer are introduced. This produces an accurate segmentation and helps in dealing with the broken boundaries, usually found in the ultrasound images. Results: The proposed network is first tested for blood vessel segmentation in liver images. It results in F1 score, mean intersection over union, and dice index of 0.83, 0.83, and 0.79, respectively. The best values observed among the existing approaches are produced by U-net as 0.74, 0.81, and 0.75, respectively. The proposed network also results in dice index value of 0.91 in the lumen segmentation experiments on MICCAI 2011 IVUS challenge dataset, which is near to the provided reference value of 0.93. Furthermore, the improvements similar to vessel segmentation experiments are also observed in the experiment performed to segment lesions. Conclusion: Deep supervision of the network based on the input-output characteristics of the layers results in improvement in overall segmentation accuracy. Significance: Sub-problem specific deep supervision for ultrasound image segmentation is the main contribution of this paper. Currently the network is train-d and tested for fixed size inputs. It requires image resizing and limits the performance in small size images.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Adaptive and Wireless Recordings of Electrophysiological Signals During
           Concurrent Magnetic Resonance Imaging
    • Authors: Ranajay Mandal;Nishant Babaria;Jiayue Cao;Zhongming Liu;
      Pages: 1649 - 1657
      Abstract: Strong electromagnetic fields that occur during functional magnetic resonance imaging (fMRI) presents a challenging environment for concurrent electrophysiological recordings. Here, we present a miniaturized, wireless platform-“MR-Link” (Multimodal Recording Link) that provides a hardware solution for simultaneous electrophysiological and fMRI signal acquisition. The device detects the changes in the electromagnetic field during fMRI to synchronize amplification and sampling of electrophysiological signals with minimal artifacts. It wirelessly transmits the recorded data at a frequency detectable by the MR-receiver coil. The transmitted data is readily separable from MRI in the frequency domain. To demonstrate its efficacy, we used this device to record electrocardiograms and somatosensory evoked potential during concurrent fMRI scans. The device minimized the fMRI-induced artifacts in electrophysiological data and wirelessly transmitted the data back to the receiver coil without compromising the fMRI signal quality. The device is compact (22 mm dia., 2 gms) and can be placed within the MRI bore to precisely synchronize with fMRI. Therefore, MR-Link offers an inexpensive system by eliminating the need for amplifiers with a high dynamic range, high-speed sampling, additional storage, or synchronization hardware for electrophysiological signal acquisition. It is expected to enable a broader range of applications of simultaneous fMRI and electrophysiology in animals and humans.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Magnetocardiography-Based Ischemic Heart Disease Detection and
           Localization Using Machine Learning Methods
    • Authors: Rong Tao;Shulin Zhang;Xiao Huang;Minfang Tao;Jian Ma;Shixin Ma;Chaoxiang Zhang;Tongxin Zhang;Fakuan Tang;Jianping Lu;Chenxing Shen;Xiaoming Xie;
      Pages: 1658 - 1667
      Abstract: Objective: This study focused on developing a fast and accurate automatic ischemic heart disease detection/localization methodology. Methods: T wave was segmented from averaged Magnetocardiography (MCG) recordings and 164 features were subsequently extracted. These features were categorized into three groups: time domain features, frequency domain features, and information theory features. Next, we compared different machine learning classifiers including: k-nearest neighbor, decision tree, support vector machine (SVM), and XGBoost. To identify ischemia heart disease (IHD) case, we selected three classifiers with best performance and applied model ensemble to average results. All 164 features were used in this stage. To localize ischemia, we classified IHD group according to stenosis locations, including left anterior descending (LAD), left circumflex artery (LCX), and right coronary artery (RCA). For this task, we used XGBoost classifier and 18 time domain features. Results: For IHD detection, the SVM-XGBoost model achieved best results with accuracy = 94.03%, precision = 86.56%, recall = 97.78%, F-score = 92.79%, AUC = 0.98, and average precision = 0.98. For ischemia localization, XGBoost model achieved accuracy = 0.74, 0.68, and 0.65, for LAD, LCX, and RCA, respectively. Conclusion: we have developed an automatic IHD detection and localization system. We find that 1. T wave repolarization synchronicity is an important factor to distinguish IHD from normal subjects 2. Magnetic field pattern is associated with stenosis location. Significance: The proposed machine learning method provides the clinicians a fast and accurate diagnosis tool to interpret MCG data, boosting its acceptance into clinics. Furthermore, the magnetic pole characteristics revealed by the method shows to be related to ischemia location, presenting the opportunity to noninvasively locate ischemia.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Identifying Ketamine Responses in Treatment-Resistant Depression Using a
           Wearable Forehead EEG
    • Authors: Zehong Cao;Chin-Teng Lin;Weiping Ding;Mu-Hong Chen;Cheng-Ta Li;Tung-Ping Su;
      Pages: 1668 - 1679
      Abstract: This study explores responses to ketamine in patients with treatment-resistant depression (TRD) using a wearable forehead electroencephalography (EEG) device. We recruited and randomly assigned 55 outpatients with TRD into three approximately equal-sized groups (A: 0.5-mg/kg ketamine; B: 0.2-mg/kg ketamine; and C: normal saline) under double-blind conditions. The ketamine responses were measured by EEG signals and Hamilton depression rating scale scores. At baseline, the responders showed significantly weaker EEG theta power than the non-responders (p
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Micro-Coil Design Influences the Spatial Extent of Responses to
           Intracortical Magnetic Stimulation
    • Authors: Seung Woo Lee;Krishnan Thyagarajan;Shelley I. Fried;
      Pages: 1680 - 1694
      Abstract: Objective: Electrical stimulation via cortically implanted electrodes has been proposed to treat a wide range of neurological disorders. Effectiveness has been limited, however, in part due to the inability of conventional electrodes to activate specific types of neurons while avoiding other types. Recent demonstrations that magnetic stimulation from a micro-coil can selectively activate pyramidal neurons (PNs) while avoiding passing axons suggest the possibility that such an approach can overcome some this limitation and here we use computer simulations to explore how the micro-coil design influences the selectivity with which neurons are activated. Methods: A computational model was developed to compare the selectivity of magnetic stimulation induced by rectangular-, V-, and W-shaped coil designs. The more promising designs (V- and W-shapes) were fabricated for use in electrophysiological experiments including in vitro patch-clamp recording and calcium imaging (GCaMP6f) of mouse brain slices. Results: Both V- and W-shaped coils reliably activated layer 5 (L5) PNs but V-coils were more effective while W-coils were more selective. Activation thresholds with double-loop coils were approximately one-half those of single-loop coils. Calcium imaging revealed that both V- and W-coils better confine activation than electrodes. Conclusion: Individual design features can influence both the strength as well as the selectivity of micro-coils and can be accurately predicted by computer simulations. Significance: Our results show that how coil design influences the response of cortical neurons to stimulation and are an important step toward the development of next-generation cortical prostheses.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Biophysical Modeling for Brain Tissue Conductivity Estimation Using SEEG
           Electrodes
    • Authors: Andres Carvallo;Julien Modolo;Pascal Benquet;Stanislas Lagarde;Fabrice Bartolomei;Fabrice Wendling;
      Pages: 1695 - 1704
      Abstract: Objective: We aimed at providing an accurate estimation of human brain tissue electrical conductivity in clinico, using local, low-intensity pulsed stimulation. Methods: Using the quasi-static approximation of Maxwell equations, we derived an analytical model of the electric field generated by intracerebral stereotactic-EEG (SEEG) electrodes. We coupled this electric field model with a model of the electrode-electrolyte interface to provide an explicit, analytical expression of brain tissue conductivity based on the recorded brain tissue response to pulse stimulation. Results: We validated our biophysical model using saline solutions calibrated in electrical conductivity, rat brain tissue, and electrophysiological data recorded in clinico from two epileptic patients during SEEG. Conclusion: This new model-based method offers a fast and reliable estimation of brain tissue electrical conductivity by accounting for contributions from the electrode-electrolyte interface. Significance: This method outperforms standard bioimpedance measurements since it provides absolute (as opposed to relative) changes in brain tissue conductivity. Application for diagnosis is envisioned since conductivity values strongly differ when estimated in the healthy versus hyperexcitable brain tissue.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Viscoelastic Properties of Human Autopsy Brain Tissues as Biomarkers for
           Alzheimer's Diseases
    • Authors: Kihan Park;Gabrielle E. Lonsberry;Marla Gearing;Allan I. Levey;Jaydev P. Desai;
      Pages: 1705 - 1713
      Abstract: Objective: The present study investigates viscoelastic properties of human autopsy brain tissue via nanoindentation to find feasible biomarkers for Alzheimer's disease (AD) in ex vivo condition and to understand the mechanics of the human brain better, especially on the difference before and after progression of AD. Methods: Viscoelastic properties of paraformaldehyde-fixed, paraffinembedded thin (8 μm) sectioned normal and AD affected human autopsy brain tissue samples are investigated via nanoindentation with a combined loading profile of a linear preloading and a sinusoidal loading at various loading frequencies from 0.01 to 10 Hz. In 1200 indentation tests for ten human autopsy brain tissue samples from ten different subjects (five AD cases and five normal controls), viscoelastic properties such as Young's modulus, storage modulus, loss modulus, and loss factor of both gray and white matter brain tissues samples from normal and AD affected tissues were measured experimentally. Results: We found that the normal brain tissues have higher Young's modulus values than the AD affected brain tissues by 23.5% and 27.9% on average for gray and white matter, respectively, with statistically significant differences (p
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Distinguishing Patients With a Coordination Disorder From Healthy Controls
           Using Local Features of Movement Trajectories During the Finger-to-Nose
           Test
    • Authors: Venustiano Soancatl Aguilar;Octavio Martinez Manzanera;Deborah A. Sival;Natasha M. Maurits;Jos B. T. M. Roerdink;
      Pages: 1714 - 1722
      Abstract: Assessment of coordination disorders is valuable for monitoring progression of patients, distinguishing healthy and pathological conditions, and ultimately aiding in clinical decision making, thereby offering the possibility to improve medical care or rehabilitation. A common method to assess movement disorders is by using clinical rating scales. However, rating scales depend on the evaluation and interpretation of an observer, implying that subjective phenotypic assignment precedes the application of the scales. Objective and more accurate methods are under continuous development but gold standards are still scarce. Here, we show how a method we previously developed, originally aimed at assessing dynamic balance by a probabilistic generalized linear model, can be used to assess a broader range of functional movements. In this paper, the method is applied to distinguish patients with coordination disorders from healthy controls. We focused on movements recorded during the finger-to-nose task (FNT), which is commonly used to assess coordination disorders. We also compared clinical FNT scores and model scores. Our method achieved 84% classification accuracy in distinguishing patients and healthy participants, using only two features. Future work could entail testing the reliability of the method by using additional features and other clinical tests such as finger chasing, quiet standing, and/or usage of tracking devices such as depth cameras or force plates.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Automated Balloon Control in Resuscitative Endovascular Balloon Occlusion
           of the Aorta
    • Authors: Cormac McCarthy;Ian Kanterman;Fabian Trauzettel;H. Alexander Jaeger;Alice-Anne Goetz;Benjamin Colvard;Lee Swanstrom;Padraig Cantillon-Murphy;
      Pages: 1723 - 1729
      Abstract: Objective: The goal of this study was to demonstrate the technical feasibility of automated balloon pressure management during resuscitative endovascular balloon occlusion of the aorta (REBOA) in the pre-clinical setting. Methods: This paper presents an intelligent balloon management device which automates the balloon inflation process, preventing the possibility of balloon over or under inflation, optimizes inflation pressure, and if indicated, deflates automating partial REBOA to allow the distal organ perfusion. Edwards TruWave pressure transducers are used to monitor the blood pressure proximal and distal to the balloon, as well as the internal balloon pressure. A faux PID controller, implemented on an Arduino platform, is used in a feedback control loop to allow a user-defined mean arterial pressure setpoint to be reached, via a syringe driver which allows intelligent inflation and deflation of the catheter balloon. Results: Ex vivo testing on a vascular perfusion simulator provided the characteristic behavior of a fully occluded aorta, namely the decrease of distal pressure to zero. In vivo testing on live porcine models indicated that automated partial REBOA is achievable and by enabling partial occlusion may offer improved medical outcomes compared to the manual control. Conclusion: Automated balloon pressure management of endovascular occlusion is feasible and can be successfully implemented without changes on current clinical workflows. Significance: With further development, automated balloon management may significantly improve clinical outcomes in REBOA.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • A Stochastic Gradient Approach for Robust Heartbeat Detection With Doppler
           Radar Using Time-Window-Variation Technique
    • Authors: Chen Ye;Kentaroh Toyoda;Tomoaki Ohtsuki;
      Pages: 1730 - 1741
      Abstract: Heart rate (HR) variability indicates health condition and mental stress. The development of non-contact HR monitoring techniques with Doppler radar is attracting great attention. However, the performance of heartbeat detection via radar signals easily degrades due to respiration and body motion. In this paper, first, a stochastic gradient approach is applied to reconstruct the high-resolution spectrum of heartbeat by proposing the zero-attracting sign least-mean-square (ZA-SLMS) algorithm. To correct the quantized gradient of cost function and penalize the sparse constraint on updating the spectrum, a more accurate heartbeat spectrum is reconstructed. Then, to better adapt to the noises of different strengths caused by subjects' movements, an adaptive regularization parameter is introduced in the ZA-SLMS algorithm as an improved variant, which can adaptively regulate the proportion between gradient correction and sparse penalty. Moreover, in view of the stability of the location of the spectral peak associated with the HR when the size of time window slightly changes, a time-window-variation (TWV) technique is further incorporated in the improved ZA-SLMS (IZA-SLMS) algorithm for more stable HR estimation. Through the experiments on five subjects, our proposal is demonstrated to bring a significant improvement in accuracy compared with existing detection methods. Specifically, the IZA-SLMS algorithm with TWV achieves the smallest average error of 3.79 beats per minute when subjects type on a laptop.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • In Vivo Visualization of Vasculature in Adult Zebrafish by Using
           High-Frequency Ultrafast Ultrasound Imaging
    • Authors: Chao-Chuan Chang;Pei-Yu Chen;Hsin Huang;Chih-Chung Huang;
      Pages: 1742 - 1751
      Abstract: Objective: Zebrafish has been recently considered an ideal vertebrate for studying developmental biology, genetics, particularly for modeling tumorigenesis, angiogenesis, and regeneration in vivo. However, when a zebrafish matures completely, its body loses transparency, thus making conventional optical imaging techniques difficult for imaging internal anatomy and vasculature. Acoustic wave penetration outperforms optical methods, high-frequency (>30 MHz) ultrasound (HFUS) was consequently an alternative imaging modality for adult zebrafish imaging, particularly for echocardiography However, visualizing peripheral vessels in a zebrafish by using conventional HFUS is still difficult. Methods: In the present study, high-frequency micro-Doppler imaging (HFμDI) based on ultrafast ultrasound imaging was proposed for zebrafish dorsal vascular mapping in vivo. HFμDI uses a 40-MHz ultrasound transducer, which is an ultrafast ultrasound imaging technology with the highest frequency available currently. Blood flow signals were extracted using an eigen-based clutter filter with different settings. Experiments were performed on an 8-month-old wild-type AB-line adult zebrafish. Results: Blood vessels, including intersegmental vessels, parachordal vessel, dorsal longitudinal anastomotic vessel, and dorsal aorta, from the dorsal side of the zebrafish were clearly observed in two-dimensional (2-D) and 3-D HFμDI. Conclusion: The maximum image depth of HFμDI and the minimal diameter of vessel can be detected were 4 mm and 36 μm, respectively; they were determined without any use of microbubbles. The maximum flow velocity range was approximately 3-4 mm/s on the dorsal vessels of the adult zebrafish. Significance: Compared with conventional ultrasound Doppler imaging, HFμDI exhibited superior small vessel imaging.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • A Machine Learning Shock Decision Algorithm for Use During Piston-Driven
           Chest Compressions
    • Authors: Iraia Isasi;Unai Irusta;Andoni Elola;Elisabete Aramendi;Unai Ayala;Erik Alonso;Jo Kramer-Johansen;Trygve Eftestøl;
      Pages: 1752 - 1760
      Abstract: Goal: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The best current methods are computationally demanding, and their accuracy could be improved. The objective of this work was to introduce a computationally efficient algorithm for shock decision during piston-driven CPR with increased accuracy. Methods: The study dataset contains 201 shockable and 844 nonshockable ECG segments from 230 cardiac arrest patients treated with the LUCAS-2 mechanical CPR device. Compression artifacts were removed using the state-of-the-art adaptive filters, and shock/no-shock discrimination features were extracted from the stationary wavelet transform analysis of the filtered ECG, and fed to a support vector machine (SVM) classifier. Quasi-stratified patient wise nested cross-validation was used for feature selection and SVM hyperparameter optimization. The procedure was repeated 50 times to statistically characterize the results. Results: Best results were obtained for a six-feature classifier with mean (standard deviation) sensitivity, specificity, and total accuracy of 97.5 (0.4), 98.2 (0.4), and 98.1 (0.3), respectively. The algorithm presented a five-fold reduction in computational demands when compared to the best available methods, while improving their balanced accuracy by 3 points. Conclusions: The accuracy of the best available methods was improved while drastically reducing the computational demands. Significance: An efficient and accurate method for shock decisions during mechanical CPR is now available to improve therapy and contribute to increase cardiac arrest survival.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Functional Mixed-Effects Modeling of Longitudinal Duchenne Muscular
           Dystrophy Electrical Impedance Myography Data Using State-Space Approach
    • Authors: Kush Kapur;Benjamin Sanchez;Adam Pacheck;Basil Darras;Seward B. Rutkove;Rajesh Selukar;
      Pages: 1761 - 1768
      Abstract: Objective: Electrical impedance myography (EIM) is a quantitative and objective tool to evaluate muscle status. EIM offers the possibility to replace conventional physical functioning scores or quality of life measures, which depend on patient cooperation and mood. Methods: Here, we propose a functional mixed-effects model using a state-space approach to describe the response trajectories of EIM data measured on 16 boys with Duchenne muscular dystrophy and 12 healthy controls, both groups measured over a period of two years. The modeling framework presented imposes a smoothing spline structure on EIM data collected at each visit and taking into account of within subject correlations of these curves along the longitudinal measurements. The modeling framework is recast in a state-space approach, thereby allowing for the employment of computationally efficient diffuse Kalman filtering and smoothing algorithms for the model estimation, as well as the estimates of the posterior variance-covariance matrix for the construction of the Bayesian 95% confidence bands. Results: The proposed model allows us to simultaneously adjust for baseline variables, differentiate the longitudinal changes in the smooth functional response and estimate the subject and subject-time specific deviations from the population-averaged response curves. The code is made publicly available in the supplementary material. Significance: The modeling approach presented will potentially enhance EIM capability to serve as a biomarker for testing therapeutic efficacy in DMD and other clinical trials.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Heart Rate Variability-Based Driver Drowsiness Detection and Its
           Validation With EEG
    • Authors: Koichi Fujiwara;Erika Abe;Keisuke Kamata;Chikao Nakayama;Yoko Suzuki;Toshitaka Yamakawa;Toshihiro Hiraoka;Manabu Kano;Yukiyoshi Sumi;Fumi Masuda;Masahiro Matsuo;Hiroshi Kadotani;
      Pages: 1769 - 1778
      Abstract: Objective: Driver drowsiness detection is a key technology that can prevent fatal car accidents caused by drowsy driving. The present work proposes a driver drowsiness detection algorithm based on heart rate variability (HRV) analysis and validates the proposed method by comparing with electroencephalography (EEG)-based sleep scoring. Methods: Changes in sleep condition affect the autonomic nervous system and then HRV, which is defined as an RR interval (RRI) fluctuation on an electrocardiogram trace. Eight HRV features are monitored for detecting changes in HRV by using multivariate statistical process control, which is a well known anomaly detection method. Result: The performance of the proposed algorithm was evaluated through an experiment using a driving simulator. In this experiment, RRI data were measured from 34 participants during driving, and their sleep onsets were determined based on the EEG data by a sleep specialist. The validation result of the experimental data with the EEG data showed that drowsiness was detected in 12 out of 13 pre-N1 episodes prior to the sleep onsets, and the false positive rate was 1.7 times per hour. Conclusion: The present work also demonstrates the usefulness of the framework of HRV-based anomaly detection that was originally proposed for epileptic seizure prediction. Significance: The proposed method can contribute to preventing accidents caused by drowsy driving.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • In Vivo Detection of Chronic Kidney Disease Using Tissue Deformation
           Fields From Dynamic MR Imaging
    • Authors: Erlend Hodneland;Eirik Keilegavlen;Erik A. Hanson;Erling Andersen;Jan Ankar Monssen;Jarle Rørvik;Sabine Leh;Hans-Peter Marti;Arvid Lundervold;Einar Svarstad;Jan M. Nordbotten;
      Pages: 1779 - 1790
      Abstract: Objective: Chronic kidney disease (CKD) is a serious medical condition characterized by gradual loss of kidney function. Early detection and diagnosis is mandatory for adequate therapy and prognostic improvement. Hence, in the current pilot study we explore the use of image registration methods for detecting renal morphologic changes in patients with CKD. Methods: Ten healthy volunteers and nine patients with presumed CKD underwent dynamic T1 weighted imaging without contrast agent. From real and simulated dynamic time series, kidney deformation fields were estimated using a poroelastic deformation model. From the deformation fields several quantitative parameters reflecting pressure gradients, and volumetric and shear deformations were computed. Eight of the patients also underwent a kidney biopsy as a gold standard. Results: We found that the absolute deformation, normalized volume changes, as well as pressure gradients correlated significantly with arteriosclerosis from biopsy assessments. Furthermore, our results indicate that current image registration methodologies are lacking sensitivity to recover mild changes in tissue stiffness. Conclusion: Image registration applied to dynamic time series correlated with structural renal changes and should be further explored as a tool for invasive measurements of arteriosclerosis. Significance: Under the assumption that the proposed framework can be further developed in terms of sensitivity and specificity, it can provide clinicians with a non-invasive tool of high spatial coverage available for characterization of arteriosclerosis and potentially other pathological changes observed in chronic kidney disease.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Bio-Physical Modeling, Characterization, and Optimization of
           Electro-Quasistatic Human Body Communication
    • Authors: Shovan Maity;Mingxuan He;Mayukh Nath;Debayan Das;Baibhab Chatterjee;Shreyas Sen;
      Pages: 1791 - 1802
      Abstract: Human body communication (HBC) has emerged as an alternative to radio wave communication for connecting low power, miniaturized wearable, and implantable devices in, on, and around the human body. HBC uses the human body as the communication channel between on-body devices. Previous studies characterizing the human body channel has reported widely varying channel response much of which has been attributed to the variation in measurement setup. This calls for the development of a unifying bio-physical model of HBC, supported by in-depth analysis and an understanding of the effect of excitation, termination modality on HBC measurements. This paper characterizes the human body channel up to 1 MHz frequency to evaluate it as a medium for the broadband communication. The communication occurs primarily in the electro-quasistatic (EQS) regime at these frequencies through the subcutaneous tissues. A lumped bio-physical model of HBC is developed, supported by experimental validations that provide insight into some of the key discrepancies found in previous studies. Voltage loss measurements are carried out both with an oscilloscope and a miniaturized wearable prototype to capture the effects of non-common ground. Results show that the channel loss is strongly dependent on the termination impedance at the receiver end, with up to 4 dB variation in average loss for different termination in an oscilloscope and an additional 9 dB channel loss with wearable prototype compared to an oscilloscope measurement. The measured channel response with capacitive termination reduces low-frequency loss and allows flat-band transfer function down to 13 KHz, establishing the human body as a broadband communication channel. Analysis of the measured results and the simulation model shows that instruments with 50 Ω input impedance (Vector Network Analyzer, Spectrum Analyzer) provides pessimistic estimation of channel loss at low frequencies. Instead, high impedance and capacit-ve termination should be used at the receiver end for accurate voltage mode loss measurements of the HBC channel at low frequencies. The experimentally validated bio-physical model shows that capacitive voltage mode termination can improve the low frequency loss by up to 50 dB, which helps broadband communication significantly.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • Estimation of Refractive Index for Biological Tissue Using Micro-Optical
           Coherence Tomography
    • Authors: Hongying Tang;Xinyu Liu;Si Chen;Xiaojun Yu;Yuemei Luo;Junying Wu;Xianghong Wang;Linbo Liu;
      Pages: 1803 - 1809
      Abstract: The refractive index of a biological tissue is required for investigating the tissue's optical properties. Efforts have been made to characterize the refractive indices of biological tissues at a single wavelength, but it is more convenient to know the Cauchy's coefficients, which provide refractive index over a wide range of wavelengths. We demonstrate a method to noninvasively provide the Cauchy's dispersion coefficients of biological tissues using a micro-optical coherence tomography. Using the short-frequency Fourier transforms, the relative optical thickness of the sample in the wavelength range of the broadband source was obtained from interferograms. The coefficients of the Cauchy's equation were estimated based on the wavelength-dependent sample thickness. We validated the proposed method using distilled water and fresh rat cornea ex vivo, and the experimental results were consistent with the reference data.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
  • A Single Sensor Dual-Modality Photoacoustic Fusion Imaging for
           Compensation of Light Fluence Variation
    • Authors: Haoran Jin;Ruochong Zhang;Siyu Liu;Zesheng Zheng;Yuanjin Zheng;
      Pages: 1810 - 1813
      Abstract: Objective: A photoacoustic signal is proportional to the product of the optical absorption coefficient and the local light fluence; quantitative photoacoustic measurements of the optical absorption coefficients, therefore, require an accurate compensation of optical fluence variation. Usually, an additional diffuse optical tomography is incorporated to estimate the light fluence variation, but it is often troubled with the bulky measurement system. On this note, we present a dual-modality photoacoustic fusion imaging method that is implemented with a normal photoacoustic imaging (PAI) device. Methods: A single piezoelectric transducer is employed to receive the photoacoustic waves and passive ultrasound (PU) waves simultaneously. Since the PU wave is generated by the backscattering and diffuse reflection photons, it has the capacity to facilitate diffuse reflectance (DR) imaging. We merged photoacoustic and DR imaging based on their dual-modality with a compensation of the optical fluence variation. Results: The absorption coefficient differences caused by the light fluence variation are reduced more than half with the proposed method, when comparing to the pure photoacoustic imaging. Conclusion: The dual-modality photoacoustic fusion imaging is able to correct the PAI errors caused by the optical fluence variation. Significance: The proposed method can be widely accepted by different PAI applications to compensate the light fluence variations without any additional required element.
      PubDate: June 2019
      Issue No: Vol. 66, No. 6 (2019)
       
 
 
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