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  Subjects -> ELECTRONICS (Total: 188 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 7)
Advances in Electronics     Open Access   (Followers: 94)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Power Electronics     Open Access   (Followers: 39)
Advancing Microelectronics     Hybrid Journal  
Aerospace and Electronic Systems, IEEE Transactions on     Hybrid Journal   (Followers: 344)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 26)
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: 14)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 30)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 22)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 38)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 13)
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: 9)
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: 305)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 1)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 123)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 103)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 102)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elkha : Jurnal Teknik Elektro     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 55)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage Materials     Full-text available via subscription   (Followers: 3)
EPJ Quantum Technology     Open Access   (Followers: 1)
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: 208)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
IACR Transactions on Symmetric Cryptology     Open Access  
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 100)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 81)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 51)
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: 75)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 73)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 58)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 44)
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: 78)
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 Energy Systems Integration     Open Access  
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 35)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 57)
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: 74)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 38)
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: 11)
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: 5)
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: 3)
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: 16)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 10)
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: 25)
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: 4)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 11)
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: 35)
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: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 9)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
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: 179)
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: 10)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 10)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal  
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 3)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 11)
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: 6)
Microelectronics and Solid State Electronics     Open Access   (Followers: 28)
Nanotechnology Magazine, IEEE     Full-text available via subscription   (Followers: 42)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal   (Followers: 1)
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 9)
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: 2)
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: 56)
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: 78)
Solid State Electronics Letters     Open Access  
Solid-State Circuits Magazine, IEEE     Hybrid Journal   (Followers: 13)
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
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)
Transactions on Electrical and Electronic Materials     Hybrid Journal  
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 6)
Ural Radio Engineering Journal     Open Access  
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: 38  
  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: Nov. 2019
      Issue No: Vol. 66, No. 11 (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: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • IEEE Transactions on Biomedical Engineering (T-BME)
    • Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • IEEE Transactions on Biomedical Engineering Handling Editors
    • Abstract: Presents a listing of the IEEE Transactions on Biomedical Engineering Handling Editors.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Improving Performance of Devanagari Script Input-Based P300 Speller Using
           Deep Learning
    • Authors: G. B. Kshirsagar;N. D. Londhe;
      Pages: 2992 - 3005
      Abstract: The performance of an existing Devanagari script (DS) input-based P300 speller with conventional machine learning techniques suffers from low information transfer rate (ITR). This occurs due to its required large size of display, i.e., 8 × 8 row-column (RC) paradigm which exhibits issues like crowding effect, adjacency, fatigue, task difficulty, and required large number of trials for character recognition. For P300 detection, deep learning algorithms have shown the state of art performance compared to the conventional machine learning algorithms in the recent past. Therefore, authors have been motivated to develop a deep learning architecture for DS-based P300 speller which can detect the target characters more accurately and in less number of trials. For this, two proven deep learning algorithms, stacked autoencoder (SAE) and deep convolution neural network (DCNN) have been adopted. For further bettering their performances, batch normalization and innovative double batch training is included here to achieve accelerated training and alleviate the problem of overfitting. Additionally, a leaky ReLU activation function has also been used in DCNN to overcome dying ReLU problem. The experiments have been performed on self-generated dataset of 20 Devanagari words with 79 characters acquired from 10 subjects using 16 channel actiCAP Xpress EEG recorder. The experimental results illustrated that the proposed DCNN is able to detect 88.22% correct targets in just three trials. Moreover, it also provides ITR of 20.58 bits per minutes, which is significantly higher than existing techniques.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Wearable Ultrasound Improves Motor Function in an MPTP Mouse Model of
           Parkinson's Disease
    • Authors: Hui Zhou;Lili Niu;Xiangxiang Xia;Zhengrong Lin;Xiufang Liu;Min Su;Ruibiao Guo;Long Meng;Hairong Zheng;
      Pages: 3006 - 3013
      Abstract: Objective: Low-frequency low-intensity pulsed ultrasound (LIPUS) has emerged as a non-invasive neuromodulation tool. The aim of this study is to examine whether LIPUS stimulation of the motor cortex can improve parkinsonian motor deficit in a mouse model induced by 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Methods: Acute Parkinson's disease (PD) mouse model is built by injection of MPTP (20 mg/kg) every 4 h in a total of four doses in one day. Mice are randomized into control, MPTP, sham-LIPUS+MPTP, and LIPUS+MPTP group. For LIPUS+MPTP group, 7 days of LIPUS (800 kHz, 10% duty cycle, 100-Hz pulse repetition frequency, 40 min/day) is delivered to the motor cortex. An open field test (OFT) is conducted on day 4 and a pole test on day 5, respectively. Striatal total superoxide dismutase (T-SOD) and glutathione peroxidase (GSH-PX) are measured on day 8. The safety of LIPUS is verified using Hematoxylin and esosin (HE) staining and Nissl staining. Results: LIPUS treatment improves rearing number in the OFT on day 4 $(n= 8, p= 0.037)$ and locomotor activity in the pole test on day 5 $(n= 8, p= 0.007)$ compared with the sham-LIPUS+MPTP group. Moreover, LIPUS increases T-SOD $(n= 7, p= 0.006)$ and GSH-PX $(n= 7, p= 0.030)$ compared with the sham-LIPUS+MPTP group. In addition, HE and Nissl staining shows no brain tissue injury induced by LIPUS. Conclusion: These findings demonstrate that LIPUS -ay have neuromodulation effects in PD mice. Significance: LIPUS may provide a novel neuromodulation tool for PD treatment.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Portable System for Time-Domain Diffuse Correlation Spectroscopy
    • Authors: Davide Tamborini;Kimberly A. Stephens;Melissa M. Wu;Parya Farzam;Andrew M. Siegel;Oleg Shatrovoy;Megan Blackwell;David A. Boas;Stefan A. Carp;Maria Angela Franceschini;
      Pages: 3014 - 3025
      Abstract: We introduce a portable system for clinical studies based on time-domain diffuse correlation spectroscopy (DCS). After evaluating different lasers and detectors, the final system is based on a pulsed laser with about 550 ps pulsewidth, a coherence length of 38 mm, and two types of single-photon avalanche diodes (SPAD). The higher efficiency of the red-enhanced SPAD maximizes detection of the collected light, increasing the signal-to-noise ratio, while the better timing response of the CMOS SPAD optimizes the selection of late photons and increases spatial resolution. We discuss component selection and performance, and we present a full characterization of the system, measurement stability, a phantom-based validation study, and preliminary in vivo results collected from the forearms and the foreheads of four healthy subjects. With this system, we are able to resolve blood flow changes 1 cm below the skin surface with improved depth sensitivity and spatial resolution with respect to continuous wave DCS.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Rehab-Net: Deep Learning Framework for Arm Movement Classification Using
           Wearable Sensors for Stroke Rehabilitation
    • Authors: Madhuri Panwar;Dwaipayan Biswas;Harsh Bajaj;Michael Jöbges;Ruth Turk;Koushik Maharatna;Amit Acharyya;
      Pages: 3026 - 3037
      Abstract: In this paper, we present a deep learning framework “Rehab-Net” for effectively classifying three upper limb movements of the human arm, involving extension, flexion, and rotation of the forearm, which, over the time, could provide a measure of rehabilitation progress. The proposed framework, Rehab-Net is formulated with a personalized, light weight and low-complex, customized convolutional neural network (CNN) model, using two-layers of CNN, interleaved with pooling layers, followed by a fully connected layer that classifies the three movements from tri-axial acceleration input data collected from the wrist. The proposed Rehab-Net framework was validated on sensor data collected in two situations: 1) semi-naturalistic environment involving an archetypal activity of “making-tea” with four stroke survivors and 2) natural environment, where ten stroke survivors were free to perform any desired arm movement for the duration of 120 min. We achieved an overall accuracy of 97.89% on semi-naturalistic data and 88.87% on naturalistic data which exceeded state-of-the-art learning algorithms namely, linear discriminant analysis, support vector machines, and k-means clustering with an average accuracy of 48.89%, 44.14%, and 27.64%. Subsequently, a computational complexity analysis of the proposed model has been discussed with an eye toward hardware implementation. The clinical significance of this study is to accurately monitor the clinical progress of the rehabilitated subjects under the ambulatory settings.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • A Multi-Layer Gaussian Process for Motor Symptom Estimation in People With
           Parkinson's Disease
    • Authors: Muriel Lang;Franz M. J. Pfister;Jakob Fröhner;Kian Abedinpour;Daniel Pichler;Urban Fietzek;Terry Taewoong Um;Dana Kulić;Satoshi Endo;Sandra Hirche;
      Pages: 3038 - 3049
      Abstract: The assessment of Parkinson's disease (PD) poses a significant challenge, as it is influenced by various factors that lead to a complex and fluctuating symptom manifestation. Thus, a frequent and objective PD assessment is highly valuable for effective health management of people with Parkinson's disease (PwP). Here, we propose a method for monitoring PwP by stochastically modeling the relationships between wrist movements during unscripted daily activities and corresponding annotations about clinical displays of movement abnormalities. We approach the estimation of PD motor signs by independently modeling and hierarchically stacking Gaussian process models for three classes of commonly observed movement abnormalities in PwP including tremor, (non-tremulous) bradykinesia, and (non-tremulous) dyskinesia. We use clinically adopted severity measures as annotations for training the models, thus allowing our multi-layer Gaussian process prediction models to estimate not only their presence but also their severities. The experimental validation of our approach demonstrates strong agreement of the model predictions with these PD annotations. Our results show that the proposed method produces promising results in objective monitoring of movement abnormalities of PD in the presence of arbitrary and unknown voluntary motions, and makes an important step toward continuous monitoring of PD in the home environment.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Motion Compensated Dynamic MRI Reconstruction With Local Affine Optical
           Flow Estimation
    • Authors: Ningning Zhao;Daniel O’Connor;Adrian Basarab;Dan Ruan;Ke Sheng;
      Pages: 3050 - 3059
      Abstract: This paper proposes a novel framework to reconstruct dynamic magnetic resonance imaging (DMRI) with motion compensation (MC). Specifically, by combining the intensity-based optical flow constraint with the traditional compressed sensing scheme, we are able to jointly reconstruct the DMRI sequences and estimate the interframe motion vectors. Then, the DMRI reconstruction can be refined through MC with the estimated motion field. By employing the coarse-to-fine multi-scale resolution strategy, we are able to update the motion field in different spatial scales. The estimated motion vectors need to be interpolated to the finest resolution scale to compensate the DMRI reconstruction. Moreover, the proposed framework is capable of handling a wide class of prior information (regularizations) for DMRI reconstruction, such as sparsity, low rank, and total variation. The formulated optimization problem is solved by a primal–dual algorithm with linesearch due to its efficiency when dealing with non-differentiable problems. Experiments on various DMRI datasets validate the reconstruction quality improvement using the proposed scheme in comparison to several state-of-the-art algorithms.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Classification of Movement Preparation Between Attended and Distracted
           Self-Paced Motor Tasks
    • Authors: Susan Aliakbaryhosseinabadi;Ernest Nlandu Kamavuako;Ning Jiang;Dario Farina;Natalie Mrachacz-Kersting;
      Pages: 3060 - 3071
      Abstract: Objective: Brain-computer interface (BCI) systems aim to control external devices by using brain signals. The performance of these systems is influenced by the user's mental state, such as attention. In this study, we classified two attention states to a target task (attended and distracted task level) while attention to the task is altered by one of three types of distractors. Methods: A total of 27 participants were allocated into three experimental groups and exposed to one type of distractor. An attended condition that was the same across the three groups comprised only the main task execution (self-paced dorsiflexion) while the distracted condition was concurrent execution of the main task and an oddball task (dual-task condition). Electroencephalography signals were recorded from 28 electrodes to classify the two attention states of attended or distracted task conditions by extracting temporal and spectral features. Results: The results showed that the ensemble classification accuracy using the combination of temporal and spectral features (spectro-temporal features, 82.3 ± 2.7%) was greater than using temporal (69 ± 2.2%) and spectral (80.3 ± 2.6%) features separately. The classification accuracy was computed using a combination of different channel locations, and it was demonstrated that a combination of parietal and centrally located channels was superior for classification of two attention states during movement preparation (parietal channels: 84.6 ± 1.3%, central and parietal channels: 87.2 ± 1.5%). Conclusion: It is possible to monitor the users’ attention to the task for different types of distractors. Significance: It has implications for onlin- BCI systems where the requirement is for high accuracy of intention detection.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • FeetBeat: A Flexible Iontronic Sensing Wearable Detects Pedal Pulses and
           Muscular Activities
    • Authors: Zhichao Zhang;Zijie Zhu;Ben Bazor;SueBin Lee;Zhi Ding;Tingrui Pan;
      Pages: 3072 - 3079
      Abstract: Objective: Human feet have long been considered in close association with whole-body health, from which abundant cardiovascular and skeletomuscular information can be extracted. In this study, we aim to develop the world's first foot-based wearable system that can detect both pedal pulses and muscular activities, referred to as FeetBeat. Methods: Utilizing the flexible iontronic sensing technology, we have constructed and characterized a five-unit sensing array for detection of both pedal pulse signals and muscular activities. It is integrated into the tongue of an athletic shoe for real-time signal acquisition. Additionally, the linear array allows alignment-free capture of pulse signals and also provides a spatial reference to muscular activities. Results: An ultrahigh sensitivity of up to 1 nF/mmHg has been achieved for individual units, with a range of 1 to 200 mmHg. The pedal pulse waveforms have been detected to derive vital health signs, such as heart rates (HR) and respiratory rates, of which the pulse-derived HR is compared with the electrocardiogram. Moreover, individual tendon responses have been acquired to analyze different pedal gestures, from which multi-channel signals can be used to distinguish different activities. Conclusion: The FeetBeat device has shown the potential to be the world's first wearable platform to simultaneously analyze both vital signals and body activities from the measurable pedal pulse waveforms and muscular responses in a natural and unobtrusive fashion. The data-collecting wearable system provides a highly valuable means to assess the personalized health as well as daily activities on a continuous basis.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Recording of Neural Activity With Modulation of Photolysis of Caged
           Compounds Using Microelectrode Arrays in Rats With Seizures
    • Authors: Fei Gao;Guihua Xiao;Yilin Song;Mixia Wang;Ziyue Li;Yu Zhang;Shengwei Xu;Jingyu Xie;Huabing Yin;Xinxia Cai;
      Pages: 3080 - 3087
      Abstract: Objective: In this paper, a new method was established to monitor multichannel neural activity with microelectrode arrays (MEAs) under modulation of caged compounds in a rat model of seizures. Methods: The 16-channel MEAs were fabricated and implanted into the hippocampus of normal rats and epileptic rats for neural spike and local field potential (LFP) recording. Using optical fibers with drug delivery tubing, two different caged compounds [ruthenium-bipyridine-trimethylphosphine glutamate (RuBi-Glu) and ruthenium-bipyridine-trimethylphosphine gamma aminobutyric acid (RuBi-GABA)] were applied, and blue light (465 nm) was used to modulate neural activity. Results: In normal rats, RuBi-Glu excited neural activity, and RuBi-GABA inhibited neural activity. The amplitude of spikes increased 26% from 154 to 194 μV with RuBi-Glu modulation. During RuBi-GABA modulation, spikes recovered to 142 μV. The firing rate increased from 1.4 to 4.5 Hz with RuBi-Glu modulation and decreased to 0.8 Hz after RuBi-GABA modulation. The power of LFPs increased from 566 to 1128 μW with RuBi-Glu modulation and recovered to 710 μW with RuBi-GABA modulation. In epileptic rats, the neural activity during seizures was significantly inhibited by RuBi-GABA modulation. The amplitude of spikes was 242 μV during seizures and decreased to 112 μV with RuBi-GABA modulation. The firing rate decreased from 20.29 to 1.33 Hz with RuBi-GABA modulation. Conclusion: Using MEAs, the modulation of neural activity with caged compound photolysis was observed with high temporal–spatial resolution in normal and epileptic rats. Signifi-ance: This new method is important for monitoring neural activity with photo-switchable modulation.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Pixel-to-Pixel Learning With Weak Supervision for Single-Stage Nucleus
           Recognition in Ki67 Images
    • Authors: Fuyong Xing;Toby C. Cornish;Tell Bennett;Debashis Ghosh;Lin Yang;
      Pages: 3088 - 3097
      Abstract: Objective: Nucleus recognition is a critical yet challenging step in histopathology image analysis, for example, in Ki67 immunohistochemistry stained images. Although many automated methods have been proposed, most use a multi-stage processing pipeline to categorize nuclei, leading to cumbersome, low-throughput, and error-prone assessments. To address this issue, we propose a novel deep fully convolutional network for single-stage nucleus recognition. Methods: Instead of conducting direct pixel-wise classification, we formulate nucleus identification as a deep structured regression model. For each input image, it produces multiple proximity maps, each of which corresponds to one nucleus category and exhibits strong responses in central regions of the nuclei. In addition, by taking into consideration the nucleus distribution in histopathology images, we further introduce an auxiliary task, region of interest (ROI) extraction, to assist and boost the nucleus quantification with weak ROI annotation. The proposed network can be learned in an end-to-end, pixel-to-pixel manner for simultaneous nucleus detection and classification. Results: We have evaluated this network on a pancreatic neuroendocrine tumor Ki67 image dataset, and the experiments demonstrate that our method outperforms recent state-of-the-art approaches. Conclusion: We present a new, pixel-to-pixel deep neural network with two sibling branches for effective nucleus recognition and observe that learning with another relevant task, ROI extraction, can further boost individual nucleus localization and classification. Significance: Our method provides a clean, single-stage nucleus recognition pipeline for histopathology image analysis, especially a new perspective for Ki67 image quantification, which would potentially benefit individual object quantification in whole-slide images.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • FMG Versus EMG: A Comparison of Usability for Real-Time Pattern
           Recognition Based Control
    • Authors: Alex Belyea;Kevin Englehart;Erik Scheme;
      Pages: 3098 - 3104
      Abstract: Force Myography (FMG), which measures the surface pressure profile exerted by contracting muscles, has been proposed as an alternative to electromyography (EMG) for human-machine interfaces. Although FMG pattern recognition-based control systems have yielded higher offline classification accuracy, but comparatively few works have examined the usability of FMG for real-time control. In this work, we conduct a comprehensive comparison of EMG and FMG-based schemes using both classification and regression controllers. Methods: Twenty participants performed a two degree of freedom Fitts' Law-style virtual target acquisition task using both FMG- and EMG-based classification and regression control schemes. Performance was evaluated based on the standard Fitts' law testing metrics throughput, path efficiency, average speed, number of timeouts, overshoot, stopping distance, and simultaneity. Results: The FMG-based classification system significantly outperformed the EMG-based classification system in both throughput (0.902±0.270) vs. (0.751±0.309), (ρ
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Highlighting Directional Reflectance Properties of Retinal Substructures
           From D-OCT Images
    • Authors: Florence Rossant;Kate Grieve;Michel Paques;
      Pages: 3105 - 3118
      Abstract: Optical coherence tomography (OCT), which is routinely used in ophthalmology, enables transverse optical imaging of the retina and, hence, the identification of the different neuronal layers. Directional OCT (D-OCT) extends this technology by acquiring sets of images at different incidence angles of the light beam. In this way, reflectance properties of photoreceptor substructures are highlighted, enabling physicians to study their orientation, which is potentially an interesting biomarker for retinal diseases. Nevertheless, commercial OCT devices equipped to automate D-OCT acquisition do not yet exist, meaning that physicians manually deviate the light beam to acquire a set of D-OCT images sequentially. Therefore, the intensities in the stack of images are not directly comparable, and a normalization step is required before differential analysis. In this paper, we present advanced image processing methods to perform differential analysis of a set of D-OCT images and extract the angle-dependent retinal substructures. Our approach relies on a robust and accurate normalization algorithm followed by a classification that is spatially regularized. We also propose a robust color representation that facilitates interpretation of D-OCT data in general, by detecting and highlighting angle-dependent structures in healthy and diseased eyes. Experimental results show evidence of photoreceptor disarray in a variety of retinal diseases, demonstrating the potential medical interest of the approach.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • A Novel Single-Character Visual BCI Paradigm With Multiple Active
           Cognitive Tasks
    • Authors: Nannan Zhang;Zongtan Zhou;Yadong Liu;Erwei Yin;Jun Jiang;Dewen Hu;
      Pages: 3119 - 3128
      Abstract: Objective: To introduce a novel event-related potential (ERP)-based brain–computer interface (BCI) paradigm with active mental tasks multiplying precise judgment and visual cognitive capacities and evaluate its performance. Methods: This study employed a paradigm with three types of targets (true-, pseudo-, and non-), double flash codes, colors and color terms, and four test conditions. The primary hypothesis was that active mental tasks combining multiple cognitive capacities and clear judgment for different categories of stimuli increase the BCI performance and evoke stronger or specific ERPs. Classification methods were proposed and evaluated, and two were used in online experiments. Results: The modes containing active mental tasks provided higher accuracy than the control mode (by up to 19.06%). The color-word matching mode had the highest judgment level and achieved the best performance. True-stimuli evoked strong P3b, while pseudotarget signals provided obvious N4, but the control mode seemed less sensitive to both of them. Different types of stimuli evoked distinctive N2 and P3a components. Conclusion: An appropriate boost in the judgment level using multiple stimuli and cognitive approaches could be investigated to improve the BCI performance and evoke or enhance ERPs. Utilizing active mental tasks may be a promising way to promote BCIs. Significance: Active mental tasks combining multiple cognitive capacities and precise judgments were adopted in an ERP-based BCI. Color and color words were introduced as stimuli to construct an alternative paradigm, and the judgment levels of different conditions were calculated. High accuracies and the participants’ preferences were obtained, which may promote the effective use of BCIs.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Enhanced Antitumor Efficacy Achieved Through Combination of nsPEFs and
           Low-Dosage Paclitaxel
    • Authors: Youyu Zhang;Zheng Mao;Bin Wang;Jianhua Zhang;Nan Lu;Ronghan Hong;Shoulong Dong;Chenguo Yao;Qing Huo Liu;
      Pages: 3129 - 3135
      Abstract: Looking for a safe and effective cancer therapy for patients is becoming an important and promising research direction. Nanosecond pulsed electric field (nsPEF) has been found to be a potential non-thermal therapeutic technique with few side effects in pre-clinical studies. On the other hand, paclitaxel (PTX), as a common chemotherapeutic agent, shows full anti-tumor activities and is used to treat a wide variety of cancers. However, the delivery of PTX is challenging due to its poor aqueous solubility. Hence, high dosages of PTX have been used to achieve effective treatment, which creates some side effects. In this study, nsPEF was combined with low-level PTX, in order to validate if this combined treatment could bring about enhanced efficacy and allow reduced doses of PTX in clinical application. Cell proliferation, apoptosis, and cell cycle distribution were examined using MTT and flow cytometry assay, respectively. Results showed that combination treatments of nsPEF and PTX exhibited significant synergistic effects in vitro. The underlying mechanism might be that these two agents acted at different targets and coordinately enhanced MDA-MB-231 cell death.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • The Classification of Minor Gait Alterations Using Wearable Sensors and
           Deep Learning
    • Authors: Alexander Turner;Stephen Hayes;
      Pages: 3136 - 3145
      Abstract: Objective: This paper describes how non-invasive wearable sensors can be used in combination with deep learning to classify artificially induced gait alterations without the requirement for a medical professional or gait analyst to be present. This approach is motivated by the goal of diagnosing gait abnormalities on a symptom-by-symptom basis, irrespective of other neuromuscular movement disorders the patients may be affected by. This could lead to improvements in treatment and offer a greater insight into movement disorders. Methods: In-shoe pressure was measured for 12 able-bodied participants, each subject to eight artificially induced gait alterations, achieved by modifying the underside of the shoe. The data were recorded at 100 Hz over 2520 data channels and were analyzed using the deep learning architecture and the long term short term memory networks. Additionally, the rationale for the decision-making process of these networks was investigated. Conclusion: Long term short term memory networks are applicable to the classification of the gait function. The classifications can be made using only 2 s of sparse data (82.0% accuracy over 96 000 instances of test data) from participants who were not a part of the training set. Significance: This paper provides potential for the gait function to be accurately classified using non-invasive techniques, and at more regular intervals, outside of a clinical setting, without the need for healthcare professionals to be present.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Dual-Element Intravascular Ultrasound Transducer for Tissue Harmonic
           Imaging and Frequency Compounding: Development and Imaging Performance
    • Authors: Junsu Lee;Jin Ho Chang;
      Pages: 3146 - 3155
      Abstract: Objective: For accurate diagnosis of atherosclerosis, the high spatial and contrast resolutions of intravascular ultrasound (IVUS) images are a key requirement. Increasing the center frequency of IVUS is a simple solution to meet this requirement. However, this leads to a reduction in imaging depth due to the frequency-dependent attenuation of ultrasound. Here, we report a recently developed dual-element IVUS transducer for tissue harmonic imaging (THI) and frequency compounding to increase the spatial and contrast resolutions of IVUS images, while maintaining the imaging depth to assess the overall morphological change of blood vessels. Methods: One 35-MHz element is used for producing general IVUS images and the other 70-MHz element is for receiving the second harmonic signals induced by the 35-MHz ultrasound. The fundamental and second harmonic signals can also be used for frequency compound imaging to further improve contrast resolution. The spatial and contrast resolutions achieved by the developed transducer were evaluated through wire and tissue-mimicking phantom imaging tests. Additionally, the images of a stent deployed in a tissue-mimicking phantom and an excised pig artery were acquired to assess clinical usefulness of the transducer. Results: The results demonstrated that the developed IVUS transducer enables us to simultaneously examine the overall morphological change of blood vessels by the 35-MHz ultrasound images and the near vessel layers such as the intima, the media, and the adventitia by either THI or compound images with high spatial and contrast resolutions. In addition, the developed transducer facilitates the simultaneous acquisition of 35- and 70-MHz fundamental images when needed. Conclusion: The developed dual-element IVUS transducer makes it possible to fully realize the potential benefits of IVUS in the diagnosis of atherosclerosis.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Design and In Vivo Verification of a CMOS Bone-Guided
           Cochlear Implant Microsystem
    • Authors: Xin-Hong Qian;Yi-Chung Wu;Tzu-Yi Yang;Cheng-Hsiang Cheng;Hsing-Chien Chu;Wan-Hsueh Cheng;Ting-Yang Yen;Tzu-Han Lin;Yung-Jen Lin;Yu-Chi Lee;Jia-Heng Chang;Shih-Ting Lin;Shang-Hsuan Li;Tsung-Chen Wu;Chien-Chang Huang;Sung-Hao Wang;Chia-Fone Lee;Chia-Hsiang Yang;Chung-Chih Hung;Tai-Shih Chi;Chien-Hao Liu;Ming-Dou Ker;Chung-Yu Wu;
      Pages: 3156 - 3167
      Abstract: Objective: To develop and verify a CMOS bone-guided cochlear implant (BGCI) microsystem with electrodes placed on the bone surface of the cochlea and the outside of round window for treating high-frequency hearing loss. Methods: The BGCI microsystem consists of an external unit and an implanted unit. The external system-on-chip is designed to process acoustic signals through an acquisition circuit and an acoustic DSP processor to generate stimulation patterns and commands that are transmitted to the implanted unit through a 13.56 MHz wireless power and bidirectional data telemetry. In the wireless power telemetry, a voltage doubler/tripler (2X/3X) active rectifier is used to enhance the power conversion efficiency and generate 2 and 3 V output voltages. In the wireless data telemetry, phase-locked loop based binary phase-shift keying and load-shift keying modulators/demodulators are adopted for the downlink and uplink data through high-Q coils, respectively. The implanted chip with four-channel high-voltage-tolerant stimulator generates biphasic stimulation currents up to 800 μA. Results: Electrical tests on the fabricated BGCI microsystem have been performed to verify the chip functions. The in vivo animal tests in guinea pigs have shown the evoked third wave of electrically evoked auditory brainstem response waveforms. It is verified that auditory nerves can be successfully stimulated and acoustic hearing can be partially preserved. Conclusion and Significance: Different from traditional cochlear implants, the proposed BGCI microsystem is less invasive, preserves partially acoustic hearing, and provides an effective alternative for treating high-frequency hearing loss.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • A Palm-Sized Cryoprobe System With a Built-In Thermocouple and Its
           Application in an Animal Model of Epilepsy
    • Authors: Tatsuji Tokiwa;Lev Zimin;Hiroshi Ishiguro;Takao Inoue;Hiroshi Kajigaya;Sadahiro Nomura;Michiyasu Suzuki;Takeshi Yamakawa;
      Pages: 3168 - 3175
      Abstract: Objective: The purpose of this study is to propose a palm-sized cryoprobe system with a built-in thermocouple (TC) for highly accurate and sensitive temperature measurements, and to verify the effectiveness of the system. Methods: Conventional cryoprobe systems based on the boiling effect of a refrigerant have triple coaxial tubes. In the proposed system, the outer and middle coaxial tubes are made of two different metals that are welded only at the probe tip, thereby forming a TC. The thermoelectric properties of the built-in TC and measurement accuracy were investigated in agar in a constant-temperature chamber. The system was also applied in a penicillin G-induced rat brain epilepsy model. Results: We verified that the built-in TC has appropriate thermoelectric properties and that the system more accurately and sensitively measured transient temperature changes at the probe tip wall compared to conventional systems, showing the cooling performance of the system. In the rat model, epileptiform activities disappeared on freezing, and reliable cell necrosis was achieved at an end temperature of −45.2 ± 1.6 °C. Conclusions: The proposed system is suitable for reliable cryosurgery. Significance: The system is probably to be valuable for clarifying the relationship between freezing temperature and cell necrosis in vivo.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • A Hand-Held Non-Robotic Surgical Tool With a Wrist and an Elbow
    • Authors: Katherine E. Riojas;Patrick L. Anderson;Ray A. Lathrop;S. Duke Herrell;D. Caleb Rucker;Robert J. Webster;
      Pages: 3176 - 3184
      Abstract: Objective: This paper describes a surgical device that provides both wrist and elbow dexterity without motors or electronics. The device provides dexterity advantages in minimally invasive surgery typically associated with robotic systems, but does so with many fewer components. Fully mechanical designs of this type promise to deliver “robot-like dexterity” at a lower financial cost than current surgical robotic systems. Methods: Most non-robotic articulated surgical tools developed to date feature one or two degrees-of-freedom (DOF) close to the tool tip (i.e., a “wrist”). In this paper, we describe a new tool that not only features a two-DOF wrist, but also augments its dexterity with a two-DOF “elbow” consisting of a multi-backbone design seen previously only in robotic systems. Such an elbow offers high stiffness in a thin form factor. This elbow requires static balancing, which we accomplish with springs in the handle, so that the surgeon can benefit from the stiffness without feeling it while using the device. Results: We report the overall tool design and experiments evaluating how well our static balance mechanism compensates for the multi-backbone elbow's intrinsic stiffness. Conclusion: We demonstrate the use of a multi-backbone elbow in a manual tool for the first time and show how to combine the elbow with a pin joint wrist in a fully mechanical (i.e., non-robotic) tool. Significance: This paper is a step toward high dexterity, low-cost surgical instruments that bring some benefits of surgical robotic systems to patients and surgeons at a lower cost.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Micropipette Aspiration of Single Cells for Both Mechanical and Electrical
    • Authors: Huayan Pu;Na Liu;Jiasheng Yu;Yang Yang;Yi Sun;Yan Peng;Shaorong Xie;Jun Luo;Liang Dong;Haige Chen;Yu Sun;
      Pages: 3185 - 3191
      Abstract: Cellular physical properties have been identified to reflect cell states. Existing techniques are able to characterize either mechanical or electrical properties of a cell. This paper presents a micropipette aspiration technique that enables the characterization of both mechanical (instantaneous elastic modulus, equilibrium elastic modulus, and viscosity), and electrical (specific membrane capacitance) properties of the same single cell. Two bladder cancer cell lines (RT4 and T24) with different metastatic potential were used to evaluate the technique. The results showed that high-grade bladder cancer cells (T24, grade III) possess lower viscosity, lower elastic modulus, and larger SMC than the low-grade cancer cells (RT4, grade I). The Naive Bayes classifier was utilized to assess the classification accuracy using single-physical and multi-physical parameters. The classification results confirmed that the use of multi-biophysical parameters resulted in higher accuracy (97.5%), sensitivity (100%), and specificity (95.2%) than the use of a single-physical parameter for distinguishing T24 and RT4 cells.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Deep Learning Movement Intent Decoders Trained With Dataset Aggregation
           for Prosthetic Limb Control
    • Authors: Henrique Dantas;David J. Warren;Suzanne M. Wendelken;Tyler S. Davis;Gregory A. Clark;V John Mathews;
      Pages: 3192 - 3203
      Abstract: Significance: The performance of traditional approaches to decoding movement intent from electromyograms (EMGs) and other biological signals commonly degrade over time. Furthermore, conventional algorithms for training neural network based decoders may not perform well outside the domain of the state transitions observed during training. The work presented in this paper mitigates both these problems, resulting in an approach that has the potential to substantially improve the quality of life of the people with limb loss. Objective: This paper presents and evaluates the performance of four decoding methods for volitional movement intent from intramuscular EMG signals. Methods: The decoders are trained using the dataset aggregation (DAgger) algorithm, in which the training dataset is augmented during each training iteration based on the decoded estimates from previous iterations. Four competing decoding methods, namely polynomial Kalman filters (KFs), multilayer perceptron (MLP) networks, convolutional neural networks (CNN), and long short-term memory (LSTM) networks, were developed. The performances of the four decoding methods were evaluated using EMG datasets recorded from two human volunteers with transradial amputation. Short-term analyses, in which the training and cross-validation data came from the same dataset, and long-term analyses, in which the training and testing were done in different datasets, were performed. Results: Short-term analyses of the decoders demonstrated that CNN and MLP decoders performed significantly better than KF and LSTM decoders, showing an improvement of up to 60% in the normalized mean-square decoding error in cross-validation tests. Long-term analyses indicated that the CNN, MLP, and LSTM decoders performed significantly better than a KF-based decoder at most analyzed cases of temporal separations (0–150 days) between the acq-isition of the training and testing datasets. Conclusion: The short-term and long-term performances of MLP- and CNN-based decoders trained with DAgger demonstrated their potential to provide more accurate and naturalistic control of prosthetic hands than alternate approaches.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Implantable Multi-Modality Probe for Subdural Simultaneous Measurement of
           Electrophysiology, Hemodynamics, and Temperature Distribution
    • Authors: Toshitaka Yamakawa;Takao Inoue;Masatsugu Niwayama;Fumiaki Oka;Hirochika Imoto;Sadahiro Nomura;Michiyasu Suzuki;
      Pages: 3204 - 3211
      Abstract: Objective: The purpose of this paper is to demonstrate how the integration of the multi-channel measurement capabilities of near-infrared spectroscopy (NIRS), electrocorticography (ECoG), and negative temperature coefficient thermistor sensors into a single device compact enough for subdural implantation can provide beneficial information on various aspects of brain cortical activity and prove a powerful medical modality for pre-, intra-, and post-operative diagnoses in neurosurgery. Methods: The development of a flexible multi-modal multi-channel probe for the simultaneous measurement of the NIRS, ECoG, and surficial temperature obtained from the cerebral cortex was carried out. Photoelectric bare chips for NIRS channels, miniature temperature-coefficient thermistors for measuring localized temperature variation, and 3-mm-diameter platinum plates for ECoG recording were assembled on a polyimide-based flexible printed circuit to create six channels for each modality. A conformal coating of Parylene-C was applied on all the channels except the ECoG to make the probe surface biocompatible. Results: As a first-in-human study, the simultaneous measurement capability of the multi-modality probe, with sufficient signal-to-noise ratio and accuracy, to observe pathological neural activities in subjects during surgery and post-operative monitoring, with no complications two weeks since the implantation, was confirmed. Conclusion: The feasibility of using a single device to assess the dynamic pathological activity from three different aspects was determined for human patients. Significance: The simultaneous and accurate multi-channel recording of electrical, hemodynamic, and thermographic cortical activities in a single device small enough for subdural implantation is likely to have major implications in neurosurgery and neuroscience.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Real-Time Visualization of an Acoustically Active Injection Catheter With
           Ultrasound Imaging: Algorithm and In Vivo Validation in a Swine Model
    • Authors: Viksit Kumar;Minako Katayama;Rachael Peavler;Azra Alizad;Marek Belohlavek;Mostafa Fatemi;
      Pages: 3212 - 3219
      Abstract: Objective: To independently visualize a catheter and needle during minimally invasive surgery in order to aid in precisely guiding them to their intended location. Methods: Symmetric frequency detection allows for the visualization of the acoustically active catheter tip as a unique color in live imaging. This study extends the algorithm to identify two different crystals by unique colors, validating the algorithm with in vivo pig experiments while simulating the human condition using different attenuation pads. Results: The catheter and needle tip were identified with unique colors, differentiable from common Doppler colors, with a frame rate varying between 8 and 10 Hz. Both were visible at graded levels of attenuation induced by interposed polymer pads. Reducing ensemble length increased the frame rate and decreased the signal-to-noise ratio (SNR), though not significantly. At the highest in-path attenuation of 12 dB at 5 MHz, the catheter spot marker was visible whereas the needle was not. The SNR of the catheter signal varied between 12.50 and 18.24 dB and the size of the spot marker varied between 149 and 1015 mm2. The SNR of the needle signal varied between 6.37 and 16.3 dB and the size of the spot marker between 59 and 169 mm2. A reliability index greater than 50% was achieved for all cases except for the needle crystal at the highest attenuation setting. Conclusion: Modified symmetric frequency detection algorithm can uniquely visualize both catheter and needle in real time with in-path attenuation. Significance: Unambiguous and distinct visualization of separate locations on the catheter facilitates real-time tracking of minimally invasive procedures.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Structure Prior Constrained Estimation of Human Cardiac Diffusion Tensors
    • Authors: Chun-Yu Chu;Chang-Yu Sun;Zi-Xiang Kuai;Feng Yang;Yue-Min Zhu;
      Pages: 3220 - 3230
      Abstract: Objective: The purpose of this paper is to increase the accuracy of human cardiac diffusion tensor (DT) estimation in diffusion magnetic resonance imaging (dMRI) with a few diffusion gradient directions. Methods: A structure prior constrained (SPC) method is proposed. The method consists in introducing two regularizers in the conventional nonlinear least squares estimator. The two regularizers penalize the dissimilarity between neighboring DTs and the difference between estimated and prior fiber orientations, respectively. A novel numerical solution is presented to ensure the positive definite estimation. Results: Experiments on ex vivo human cardiac data show that the SPC method is able to well estimate DTs at most voxels, and is superior to state-of-the-art methods in terms of the mean errors of principal eigenvector, second eigenvector, helix angle, transverse angle, fractional anisotropy, and mean diffusivity. Conclusion: The SPC method is a practical and reliable alternative to current denoising- or regularization-based methods for the estimation of human cardiac DT. Significance: The SPC method is able to accurately estimate human cardiac DTs in dMRI with a few diffusion gradient directions.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Ultrasound Tracking of the Acoustically Actuated Microswimmer
    • Authors: Qiyang Chen;Fang-Wei Liu;Zunding Xiao;Nitin Sharma;Sung Kwon Cho;Kang Kim;
      Pages: 3231 - 3237
      Abstract: Objective: The purpose of this paper is to demonstrate the ultrasound tracking strategy for the acoustically actuated bubble-based microswimmer. Methods: The ultrasound tracking performance is evaluated by comparing the tracking results with the camera tracking. A benchtop experiment is conducted to capture the motion of two types of microswimmers by synchronized ultrasound and camera systems. A laboratory developed tracking algorithm is utilized to estimate the trajectory for both tracking methods. Results: The trajectory reconstructed from ultrasound tracking method compares well with the conventional camera tracking, exhibiting a high accuracy and robustness for three different types of moving trajectories. Conclusion: Ultrasound tracking is an accurate and reliable approach to track the motion of the acoustically actuated microswimmers. Significance: Ultrasound imaging is a promising candidate for noninvasively tracking the motion of microswimmers inside the body in biomedical applications and may further promote the real-time control strategy for the microswimmers.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Aortic Frequency Response Determination via Bioimpedance Plethysmography
    • Authors: Roman Kusche;Arthur-Vincent Lindenberg;Sebastian Hauschild;Martin Ryschka;
      Pages: 3238 - 3246
      Abstract: Objective: Arterial stiffness is an important marker to predict cardiovascular events. Common measurement techniques to determine the condition of the aorta are limited to the acquisition of the arterial pulse wave at the extremities. The goal of this paper is to enable non-invasive measurements of the aortic pulse wave velocity, instead. An additional aim is to extract further information, related to the conditions of the aorta, from the pulse wave signal instead of only its velocity. Methods: After discussing the problems of common pulse wave analysis procedures, an approach to determine the frequency response of the aorta is presented. Therefore, the aorta is modeled as an electrical equivalent circuit. To determine the specific numeric values of this system, a measurement approach is presented, which is based on non-invasive bioimpedance plethysmography measurements above the aortic arch and at the inguinal region. The conversion of the measurement results to the system parameters is realized by a digital algorithm, which is proposed in this paper as well. To evaluate the approach, a study on three subjects is performed. Results: The measurement results demonstrate that the proposed approach yields realistic frequency responses. For better approximation of the aortic system function, more complex models are recommended to investigate in the future. Since this paper is limited to three subjects without a ground truth, further measurements will be necessary. Significance: The proposed approach could solve the problems of current methods to determine the condition of the aorta. Its application is non-invasive, harmless, and easy to execute.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • A Projection CCA Method for Effective fMRI Data Analysis
    • Authors: Muhammad Ali Qadar;Abd-Krim Seghouane;
      Pages: 3247 - 3256
      Abstract: Objective: Canonical correlation analysis (CCA) is a data-driven method that has been successfully used in functional magnetic resonance imaging (fMRI) data analysis. Standard CCA extracts meaningful information from a pair of data sets by seeking pairs of linear combinations from two sets of variables with maximum pairwise correlation. So far, however, this method has been used without incorporating prior information available for fMRI data. In this paper, we address this issue by proposing a new CCA method named pCCA (for projection CCA). Methods: The proposed method is obtained by projection onto a set of basis vectors that better characterize temporal information in the fMRI data set. A methodology is presented to describe the basis selection process using discrete cosine transform (DCT) basis functions. Employing DCT guides the estimated canonical variates, yielding a more computationally efficient CCA procedure. Results: The performance gain of the proposed pCCA algorithm over standard and regularized CCA is illustrated on both simulated and real fMRI datasets from resting state, block paradigm task-related and event-related experiments. The results have shown that the proposed pCCA successfully extracts latent components from the task as well as resting-state datasets with increased specificity of the activated voxels. Conclusion: In addition to offering a new CCA approach, when applied on fMRI data, the proposed algorithm adapts to variations of brain activity patterns and reveals the functionally connected brain regions. Significance: The proposed method can be seen as a regularized CCA method where regularization is introduced via basis expansion, which has the advantage of enforcing smoothness on canonical components.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • A Novel Framework for Estimating Time-Varying Multivariate Autoregressive
           Models and Application to Cardiovascular Responses to Acute Exercise
    • Authors: Kyriaki Kostoglou;Andrew D. Robertson;Bradley J. MacIntosh;Georgios D. Mitsis;
      Pages: 3257 - 3266
      Abstract: Objective: We present a novel modeling framework for identifying time-varying (TV) couplings between time-series of biomedical relevance. Methods: The proposed methodology is based on multivariate autoregressive (MVAR) models, which have been extensively used to study couplings between biosignals. Contrary to the standard estimation methods that assume time-invariant relationships, we propose a modified recursive Kalman filter (KF) to track changes in the model parameters. We perform model order selection and hyperparameter optimization simultaneously using Genetic Algorithms, greatly improving accuracy and computation time. In addition, we address the effect of residual heteroscedasticity, possibly associated with event-related changes or phase transitions during a given experimental protocol, on the TV-MVAR coupling measures by using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models to fit the TV-MVAR residuals. Results: Using simulated data, we show that the proposed framework yields more accurate parameter estimates compared to the conventional KF, particularly when the true system parameters exhibit different rate of variations over time. Furthermore, by accounting for heteroskedasticity, we obtain more accurate estimates of the strength and directionality of the underlying couplings. We also use our approach to investigate TV hemodynamic interactions during exercise in young and old healthy adults, as well as individuals with chronic stroke. We extract TV coupling patterns that reflect well known exercise-induced effects on the underlying regulatory mechanisms with excellent time resolution. Conclusion and Significance: The proposed modeling framework can be used to efficiently quantify TV couplings between biosignals. It is fully automated and does not require prior knowledge of the system TV characteristics.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • A New Method for Continuous Relative Blood Volume and Plasma Sodium
           Concentration Estimation During Hemodialysis
    • Authors: Enrico Ravagli;Mattias Holmer;Leif Sörnmo;Stefano Severi;
      Pages: 3267 - 3277
      Abstract: Objective: Non-invasive sensing and reliable estimation of physiological parameters are important features of hemodialysis machines, especially for therapy customization (biofeedback). In this paper, we present a new method for joint estimation of two important hemodialysis-related physiological parameters—relative blood volume and plasma sodium concentration. Methods: Our method makes use of a non-invasive sensor setup and a mathematical estimator. The estimator, based on the Kalman filter, allows merging data from multiple sensors, newly designed as well as onboard, with modeling knowledge about the hemodialysis process. The system was validated on in vitro hemodialysis sessions using bovine blood. Results: The estimation error we obtained (0.97 ± 0.73% on relative blood volume and 0.47 ± 0.19 mM on plasmatic sodium) proved to be comparable with that of the reference data for both parameters—the system is sufficiently accurate to be relevant in a clinical context. Conclusion: Our system has the potential to provide accurate and important information on the state of a patient undergoing hemodialysis, while only low-cost modifications to the existing onboard sensors are required. Significance: Through improved knowledge of blood parameters during hemodialysis, our method will allow better patient monitoring and therapy customization in hemodialysis.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
  • Catheter Treatment of Ventricular Tachycardia: A Reference-Less
           Pace-Mapping Method to Identify Ablation Targets
    • Authors: Freddy Odille;Alberto Battaglia;Philip Hoyland;Jean-Marc Sellal;Damien Voilliot;Christian de Chillou;Jacques Felblinger;
      Pages: 3278 - 3287
      Abstract: Objective: A novel method is developed to identify ablation targets for the catheter treatment of ventricular tachycardia (VT). Methods: The method is based on pace-mapping, which is a validated technique to determine the catheter ablation targets. Conventionally, it consists of stimulating the heart ventricle from various sites and comparing the resulting activation pathways to that of a clinical VT by the analysis of surface electrocardiograms (ECG). In this paper, a novel pace-mapping method is presented, which does not require a reference ECG recording of the VT. A three-dimensional correlation gradient map is reconstructed by semiautomatic analysis of ECG morphological changes within the network of pace-mapping sites. In these maps, abnormal points are identified by high correlation gradient values (i.e., corresponding to slow propagation of the electric influx, as in the core of the reentrant VT circuit). The relation between the conventional and reference-less method is described theoretically and evaluated in a retrospective study including 24 VT ablation procedures. Results: The “reference-less” method was able to identify normal points with a high accuracy (negative predictive value: NPV = 97%), and to detect more abnormal points, as predicted by the theory. Correlation gradients computed by the proposed method were significantly higher in ablation zones than in other zones of the ventricle (p < 10–12), indicating excellent prediction of the ablation targets. Significance: The reference-less method might either be used in complement of the conventional method or to treat patients in whom VT cannot be induced during the intervention.
      PubDate: Nov. 2019
      Issue No: Vol. 66, No. 11 (2019)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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Fax: +00 44 (0)131 4513327
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