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  Subjects -> COMPUTER SCIENCE (Total: 2091 journals)
    - ANIMATION AND SIMULATION (31 journals)
    - ARTIFICIAL INTELLIGENCE (101 journals)
    - AUTOMATION AND ROBOTICS (105 journals)
    - CLOUD COMPUTING AND NETWORKS (64 journals)
    - COMPUTER ARCHITECTURE (10 journals)
    - COMPUTER ENGINEERING (11 journals)
    - COMPUTER GAMES (21 journals)
    - COMPUTER PROGRAMMING (26 journals)
    - COMPUTER SCIENCE (1215 journals)
    - COMPUTER SECURITY (48 journals)
    - DATA BASE MANAGEMENT (14 journals)
    - DATA MINING (35 journals)
    - E-BUSINESS (22 journals)
    - E-LEARNING (29 journals)
    - ELECTRONIC DATA PROCESSING (22 journals)
    - IMAGE AND VIDEO PROCESSING (40 journals)
    - INFORMATION SYSTEMS (108 journals)
    - INTERNET (94 journals)
    - SOCIAL WEB (52 journals)
    - SOFTWARE (34 journals)
    - THEORY OF COMPUTING (9 journals)

COMPUTER SCIENCE (1215 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 21)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 28)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 15)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 9)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 15)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 6)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 6)
ACM Transactions on Economics and Computation     Hybrid Journal   (Followers: 1)
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 32)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 28)
Advanced Science Letters     Full-text available via subscription   (Followers: 10)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 4)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Computer Science : an International Journal     Open Access   (Followers: 14)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 56)
Advances in Engineering Software     Hybrid Journal   (Followers: 28)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 14)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Human-Computer Interaction     Open Access   (Followers: 20)
Advances in Materials Science     Open Access   (Followers: 14)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 49)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 6)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 9)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal  
Air, Soil & Water Research     Open Access   (Followers: 12)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 6)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 12)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 13)
Annals of Pure and Applied Logic     Open Access   (Followers: 3)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 8)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 12)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 13)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 10)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 142)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 8)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 5)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 13)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Big Data and Cognitive Computing     Open Access   (Followers: 2)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 305)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 21)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 37)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 49)
British Journal of Educational Technology     Hybrid Journal   (Followers: 145)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 15)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 15)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 8)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Hybrid Journal   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 23)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 2)
Communications in Information Science and Management Engineering     Open Access   (Followers: 4)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 51)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 3)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 17)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 8)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 30)
Computer     Full-text available via subscription   (Followers: 98)
Computer Aided Surgery     Open Access   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 16)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 24)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)

        1 2 3 4 5 6 7 | Last

Journal Cover
Biomedical Engineering, IEEE Reviews in
Journal Prestige (SJR): 1.616
Citation Impact (citeScore): 7
Number of Followers: 21  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 1937-3333
Published by IEEE Homepage  [191 journals]
  • 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: 2018
      Issue No: Vol. 11 (2018)
       
  • IEEE Reviews in Biomedical Engineering (R-BME)
    • Abstract: Presents the Statement of Editorial Policy for this issue of the publication.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Editorial Health Engineering: Convergence Transforming Reactive Medicine
           to Proactive Healthcare
    • Authors: Y.-T. Zhang;
      Pages: 1 - 1
      Abstract: Presents the introductory editorial for this issue of the publication.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Breathing Rate Estimation From the Electrocardiogram and
           Photoplethysmogram: A Review
    • Authors: Peter H. Charlton;Drew A. Birrenkott;Timothy Bonnici;Marco A. F. Pimentel;Alistair E. W. Johnson;Jordi Alastruey;Lionel Tarassenko;Peter J. Watkinson;Richard Beale;David A. Clifton;
      Pages: 2 - 20
      Abstract: Breathing rate (BR) is a key physiological parameter used in a range of clinical settings. Despite its diagnostic and prognostic value, it is still widely measured by counting breaths manually. A plethora of algorithms have been proposed to estimate BR from the electrocardiogram (ECG) and pulse oximetry (photoplethysmogram, PPG) signals. These BR algorithms provide opportunity for automated, electronic, and unobtrusive measurement of BR in both healthcare and fitness monitoring. This paper presents a review of the literature on BR estimation from the ECG and PPG. First, the structure of BR algorithms and the mathematical techniques used at each stage are described. Second, the experimental methodologies that have been used to assess the performance of BR algorithms are reviewed, and a methodological framework for the assessment of BR algorithms is presented. Third, we outline the most pressing directions for future research, including the steps required to use BR algorithms in wearable sensors, remote video monitoring, and clinical practice.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Pain-Free Blood Glucose Monitoring Using Wearable Sensors: Recent
           Advancements and Future Prospects
    • Authors: Sarah Ali Siddiqui;Yuan Zhang;Jaime Lloret;Houbing Song;Zoran Obradovic;
      Pages: 21 - 35
      Abstract: Keeping track of blood glucose levels non-invasively is now possible due to diverse breakthroughs in wearable sensors technology coupled with advanced biomedical signal processing. However, each user might have different requirements and priorities when it comes to selecting a self-monitoring solution. After extensive research and careful selection, we have presented a comprehensive survey on noninvasive/pain-free blood glucose monitoring methods from the recent five years (2012-2016). Several techniques, from bioinformatics, computer science, chemical engineering, microwave technology, etc., are discussed in order to cover a wide variety of solutions available for different scales and preferences. We categorize the noninvasive techniques into nonsample- and sample-based techniques, which we further grouped into optical, nonoptical, intermittent, and continuous. The devices manufactured or being manufactured for noninvasive monitoring are also compared in this paper. These techniques are then analyzed based on certain constraints, which include time efficiency, comfort, cost, portability, power consumption, etc., a user might experience. Recalibration, time, and power efficiency are the biggest challenges that require further research in order to satisfy a large number of users. In order to solve these challenges, artificial intelligence (AI) has been employed by many researchers. AI-based estimation and decision models hold the future of noninvasive glucose monitoring in terms of accuracy, cost effectiveness, portability, efficiency, etc. The significance of this paper is twofold: first, to bridge the gap between IT and medical field; and second, to bridge the gap between end users and the solutions (hardware and software).
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • A Review of Signal Processing Techniques for Electrocardiogram Signal
           Quality Assessment
    • Authors: Udit Satija;Barathram Ramkumar;M. Sabarimalai Manikandan;
      Pages: 36 - 52
      Abstract: Electrocardiogram (ECG) signal quality assessment (SQA) plays a vital role in significantly improving the diagnostic accuracy and reliability of unsupervised ECG analysis systems. In practice, the ECG signal is often corrupted with different kinds of noises and artifacts. Therefore, numerous SQA methods were presented based on the ECG signal and/or noise features and the machine learning classifiers and/or heuristic decision rules. This paper presents an overview of current state-of-the-art SQA methods and highlights the practical limitations of the existing SQA methods. Based upon past and our studies, it is noticed that a lightweight ECG noise analysis framework is highly demanded for real-time detection, localization, and classification of single and combined ECG noises within the context of wearable ECG monitoring devices which are often resource constrained.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Promises and Challenges in the Use of Consumer-Grade Devices for Sleep
           Monitoring
    • Authors: Sirinthip Roomkham;David Lovell;Joseph Cheung;Dimitri Perrin;
      Pages: 53 - 67
      Abstract: The market for smartphones, smartwatches, and wearable devices is booming. In recent years, individuals and researchers have used these devices as additional tools to monitor and track sleep, physical activity, and behavior. Their use in sleep research and clinical applications could address the difficulties in scaling up studies that rely on polysomnography, the gold-standard. However, the use of commercial devices for large-scale sleep studies is not without challenges. With this in mind, this paper presents an extensive review of sleep monitoring systems and the techniques used in their development. We also discuss their performance in terms of reliability and validity, and consider the needs and expectations of users, whether they are experts, patients, or the general public. Through this review, we highlight a number of challenges with current studies: a lack of standard evaluation methods for consumer-grade devices (e.g., reliability and validity assessment); limitations in the populations studied; consumer expectations of monitoring devices; constraints on the resources of consumer-grade devices (e.g., power consumption).
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Why Deep Learning Is Changing the Way to Approach NGS Data Processing: A
           Review
    • Authors: Fabrizio Celesti;Antonio Celesti;Jiafu Wan;Massimo Villari;
      Pages: 68 - 76
      Abstract: Nowadays, big data analytics in genomics is an emerging research topic. In fact, the large amount of genomics data originated by emerging next-generation sequencing (NGS) techniques requires more and more fast and sophisticated algorithms. In this context, deep learning is re-emerging as a possible approach to speed up the DNA sequencing process. In this review, we specifically discuss such a trend. In particular, starting from an analysis of the interest of the Internet community in both NGS and deep learning, we present a taxonomic analysis highlighting the major software solutions based on deep learning algorithms available for each specific NGS application field. We discuss future challenges in the perspective of cloud computing services aimed at deep learning based solutions for NGS.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • A Review of Automated Pain Assessment in Infants: Features, Classification
           Tasks, and Databases
    • Authors: Ghada Zamzmi;Rangachar Kasturi;Dmitry Goldgof;Ruicong Zhi;Terri Ashmeade;Yu Sun;
      Pages: 77 - 96
      Abstract: Bedside caregivers assess infants' pain at constant intervals by observing specific behavioral and physiological signs of pain. This standard has two main limitations. The first limitation is the intermittent assessment of pain, which might lead to missing pain when the infants are left unattended. Second, it is inconsistent since it depends on the observer's subjective judgment and differs between observers. Intermittent and inconsistent assessment can induce poor treatment and, therefore, cause serious long-term consequences. To mitigate these limitations, the current standard can be augmented by an automated system that monitors infants continuously and provides quantitative and consistent assessment of pain. Several automated methods have been introduced to assess infants' pain automatically based on analysis of behavioral or physiological pain indicators. This paper comprehensively reviews the automated approaches (i.e., approaches to feature extraction) for analyzing infants' pain and the current efforts in automatic pain recognition. In addition, it reviews the databases available to the research community and discusses the current limitations of the automated pain assessment.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Quantitative MRI Brain Studies in Mild Cognitive Impairment and
           Alzheimer's Disease: A Methodological Review
    • Authors: Stephanos Leandrou;Styliani Petroudi;Panayiotis A. Kyriacou;Constantino Carlos Reyes-Aldasoro;Constantinos S. Pattichis;
      Pages: 97 - 111
      Abstract: Classifying and predicting Alzheimer's disease (AD) in individuals with memory disorders through clinical and psychometric assessment is challenging, especially in mild cognitive impairment (MCI) subjects. Quantitative structural magnetic resonance imaging acquisition methods in combination with computer-aided diagnosis are currently being used for the assessment of AD. These acquisitions methods include voxel-based morphometry, volumetric measurements in specific regions of interest (ROIs), cortical thickness measurements, shape analysis, and texture analysis. This review evaluates the aforementioned methods in the classification of cases into one of the following three groups: normal controls, MCI, and AD subjects. Furthermore, the performance of the methods is assessed on the prediction of conversion from MCI to AD. In parallel, it is also assessed which ROIs are preferred in both classification and prognosis through the different states of the disease. Structural changes in the early stages of the disease are more pronounced in the medial temporal lobe, especially in the entorhinal cortex, whereas with disease progression, both entorhinal cortex and hippocampus offer similar discriminative power. However, for the conversion from MCI subjects to AD, entorhinal cortex provides better predictive accuracies rather than other structures, such as the hippocampus.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • A Survey of Graph Cuts/Graph Search Based Medical Image Segmentation
    • Authors: Xinjian Chen;Lingjiao Pan;
      Pages: 112 - 124
      Abstract: Medical image segmentation is a fundamental and challenging problem for analyzing medical images. Among different existing medical image segmentation methods, graph-based approaches are relatively new and show good features in clinical applications. In the graph-based method, pixels or regions in the original image are interpreted into nodes in a graph. By considering Markov random field to model the contexture information of the image, the medical image segmentation problem can be transformed into a graph-based energy minimization problem. This problem can be solved by the use of minimum s-t cut/ maximum flow algorithm. This review is devoted to cut-based medical segmentation methods, including graph cuts and graph search for region and surface segmentation. Different varieties of cut-based methods, including graph-cuts-based methods, model integrated graph cuts methods, graph-search-based methods, and graph search/graph cuts based methods, are systematically reviewed. Graph cuts and graph search with deep learning technique are also discussed.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Review on Otological Robotic Systems: Toward Microrobot-Assisted
           Cholesteatoma Surgery
    • Authors: Bassem Dahroug;Brahim Tamadazte;Stefan Weber;Laurent Tavernier;Nicolas Andreff;
      Pages: 125 - 142
      Abstract: Otologic surgical procedures over time have become minimally invasive due to the development of medicine, microtechniques, and robotics. This trend then provides an expected reduction in the patient's recovery time and improvement in the accuracy of diagnosis and treatment. One of the most challenging difficulties that such techniques face are precise control of the instrument and supply of an ergonomic system to the surgeon. The objective of this literature review is to present requirements and guidelines for a surgical robotic system dedicated to middle ear surgery. This review is particularly focused on cholesteatoma surgery (diagnosis and surgical tools), which is one of the most frequent pathologies that urge for an enhanced treatment. This review also presents the current robotic systems that are implemented for otologic applications.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Deformable Models for Surgical Simulation: A Survey
    • Authors: Jinao Zhang;Yongmin Zhong;Chengfan Gu;
      Pages: 143 - 164
      Abstract: This paper presents a survey of the state-of-the-art deformable models studied in the literature, with regard to soft tissue deformable modeling for interactive surgical simulation. It first introduces the challenges of surgical simulation, followed by discussions and analyses on the deformable models, which are classified into three categories: the heuristic modeling methodology, continuum-mechanical methodology, and other methodologies. It also examines linear and nonlinear deformable modeling, model internal forces, and numerical time integrations, together with modeling of soft tissue anisotropy, viscoelasticity, and compressibility. Finally, various issues in the existing deformable models are discussed to outline the remaining challenges of deformable models in surgical simulation.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Computational Modeling of Wound Suture: A Review
    • Authors: Arnab Chanda;Tysum Ruchti;Vinu Unnikrishnan;
      Pages: 165 - 176
      Abstract: Suturing is an acquired skill which is based on a surgeon's experience. To date, no two sutures are the same with respect to the type of knot, tension, or suture material. With advancement in medical technologies, robotic suturing is becoming more and more important to operate on complex and difficult to reach internal surgical sites. While it is very difficult to translate a surgeon's suturing expertise to an automated environment, computational models could be employed to estimate baseline suture force requirements for a given wound shape, size, and suture material, which could be subsequently processed by a robot. In the literature, there have been few attempts to characterize wound closure and suture mechanics using simple two- and three-dimensional computational models. Single and multiple skin layers (epidermis, dermis, and hypodermis) and tissues with different wound geometries and sizes have been simulated under simple wound flap displacements to estimate suture force requirements. Also, recently, sutures were modeled to simulate a realistic wound closure via suture pulling, and skin prestress effect due to the natural tension of skin was incorporated in a few models to understand its effects on wound closure mechanics. An extensive review of this literature on computational modeling of wound suture would provide valuable insights into the areas in which further research work is required. Discussion of various computational challenges in modeling sutures in a numerical environment will help in better understanding the roadblocks and the required advancements in suture modeling.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • A Review on Accelerometry-Based Gait Analysis and Emerging Clinical
           Applications
    • Authors: Delaram Jarchi;James Pope;Tracey K. M. Lee;Larisa Tamjidi;Amirhosein Mirzaei;Saeid Sanei;
      Pages: 177 - 194
      Abstract: Gait analysis continues to be an important technique for many clinical applications to diagnose and monitor certain diseases. Many mental and physical abnormalities cause measurable differences in a person's gait. Gait analysis has applications in sport, computer games, physical rehabilitation, clinical assessment, surveillance, human recognition, modeling, and many other fields. There are established methods using various sensors for gait analysis, of which accelerometers are one of the most often employed. Accelerometer sensors are generally more user friendly and less invasive. In this paper, we review research regarding accelerometer sensors used for gait analysis with particular focus on clinical applications. We provide a brief introduction to accelerometer theory followed by other popular sensing technologies. Commonly used gait phases and parameters are enumerated. The details of selecting the papers for review are provided. We also review several gait analysis software. Then we provide an extensive report of accelerometry-based gait analysis systems and applications, with additional emphasis on trunk accelerometry. We conclude this review with future research directions.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • A Review on Tumor-Treating Fields (TTFields): Clinical Implications
           Inferred From Computational Modeling
    • Authors: Cornelia Wenger;Pedro C. Miranda;Ricardo Salvador;Axel Thielscher;Zeev Bomzon;Moshe Giladi;Maciej M. Mrugala;Anders R. Korshoej;
      Pages: 195 - 207
      Abstract: Tumor-treating fields (TTFields) are a cancer treatment modality that uses alternating electric fields of intermediate frequency (~100-500 kHz) and low intensity (1-3 V/cm) to disrupt cell division. TTFields are delivered by transducer arrays placed on the skin close to the tumor and act regionally and noninvasively to inhibit tumor growth. TTFields therapy is U.S. Food and Drug Administration approved for the treatment of glioblastoma multiforme, the most common and aggressive primary human brain cancer. Clinical trials testing the safety and efficacy of TTFields for other solid tumor types are underway. The objective of this paper is to review computational approaches used to characterize TTFields. The review covers studies of the macroscopic spatial distribution of TTFields generated in the human head, and of the microscopic field distribution in tumor cells. In addition, preclinical and clinical findings related to TTFields and principles of its operation are summarized. Particular emphasis is put on outlining the potential clinical value inferred from computational modeling.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Identifying Important Attributes for Early Detection of Chronic Kidney
           Disease
    • Authors: Anandanadarajah Nishanth;Tharmarajah Thiruvaran;
      Pages: 208 - 216
      Abstract: Individuals with chronic kidney disease (CKD) are often not aware that the medical tests they take for other purposes may contain useful information about CKD, and that this information is sometimes not used effectively to tackle the identification of the disease. Therefore, attributes of different medical tests are investigated to identify which attributes may contain useful information about CKD. A database with several attributes of healthy subjects and subjects with CKD are analyzed using different techniques. Common spatial pattern (CSP) filter and linear discriminant analysis are first used to identify the dominant attributes that could contribute in detecting CKD. Here, the CSP filter is applied to optimize a separation between CKD and nonCKD subjects. Then, classification methods are also used to identify the dominant attributes. These analyses suggest that hemoglobin, albumin, specific gravity, hypertension, and diabetes mellitus, together with serum creatinine, are the most important attributes in the early detection of CKD. Further, it suggests that in the absence of information on hypertension and diabetes mellitus, random blood glucose and blood pressure attributes may be used.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Electrical Stimulation and Bone Healing: A Review of Current Technology
           and Clinical Applications
    • Authors: Jawad M. Khalifeh;Zohny Zohny;Matthew MacEwan;Manu Stephen;William Johnston;Paul Gamble;Youchun Zeng;Ying Yan;Wilson Z. Ray;
      Pages: 217 - 232
      Abstract: Pseudarthrosis is an exceedingly common, costly, and morbid complication in the treatment of long bone fractures and after spinal fusion surgery. Electrical bone growth stimulation (EBGS) presents a unique approach to accelerate healing and promote fusion success rates. Over the past three decades, increased experience and widespread use of EBGS devices has led to significant improvements in stimulation paradigms and clinical outcomes. In this paper, we comprehensively review the literature and examine the history, scientific evidence, available technology, and clinical applications for EBGS. We summarize indications, limitations, and provide an overview of cost-effectiveness and future directions of EBGS technology. Various models of electrical stimulation have been proposed and marketed as adjuncts for spinal fusions and long bone fractures. Clinical studies show variable safety and efficacy of EBGS under different conditions and clinical scenarios. While the results of clinical trials do not support indiscriminate EBGS utilization for any bone injury, the evidence does suggest that EBGS is desirable and cost efficient for certain orthopedic indications, especially when used in combination with standard, first-line treatments. This review should serve as a reference to inform practicing clinicians of available treatment options, facilitate evidence-based decision making, and provide a platform for further research.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Engineering Approaches to Assessing Hydration Status
    • Authors: David C. Garrett;Nyssa Rae;Jared R. Fletcher;Sasha Zarnke;Sarah Thorson;David B. Hogan;Elise C. Fear;
      Pages: 233 - 248
      Abstract: Dehydration is a common condition characterized by a decrease in total body water. Acute dehydration can cause physical and cognitive impairment, heat stroke and exhaustion, and, if severe and uncorrected, even death. The health effects of chronic mild dehydration are less well studied with urolithiasis (kidney stones) the only condition consistently associated with it. Aside from infants and those with particular medical conditions, athletes, military personnel, manual workers, and older adults are at particular risk of dehydration due to their physical activity, environmental exposure, and/or challenges in maintaining fluid homeostasis. This review describes the different approaches that have been explored for hydration assessment in adults. These include clinical indicators perceived by the patient or detected by a practitioner and routine laboratory analyses of blood and urine. These techniques have variable accuracy and practicality outside of controlled environments, creating a need for simple, portable, and rapid hydration monitoring devices. We review the wide array of devices proposed for hydration assessment based on optical, electromagnetic, chemical, and acoustical properties of tissue and bodily fluids. However, none of these approaches has yet emerged as a reliable indicator in diverse populations across various settings, motivating efforts to develop new methods of hydration assessment.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Introduction to the Special Section: Convergence of Automation Technology,
           Biomedical Engineering, and Health Informatics Toward the Healthcare 4.0
    • Authors: Zhibo Pang;Geng Yang;Ridha Khedri;Yuan-Ting Zhang;
      Pages: 249 - 259
      Abstract: Industry 4.0 is spilling out from manufacturing to healthcare. In this article, we provide a brief history and key enabling technologies of Industry 4.0, and its revolution in healthcare-Healthcare 4.0-and its reshaping of the landscape of the entire healthcare value chain. We discuss the shift in the system design paradigm from open, small, and single loop to closed, large, and multiple loops. We provide the example of a Caregiving Home, and discuss emerging research topics and challenges, including healthcare big data, automated medical production, healthcare robotics, and human-robot symbiosis. Relevant papers published in this special section are also presented.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Detection and Automation Technologies for the Mass Production of Droplet
           Biomicrofluidics
    • Authors: Zongjie Wang;
      Pages: 260 - 274
      Abstract: Droplet microfluidics utilizes two immiscible flows to generate small droplets with the diameter of a few to a few hundred micrometers. These droplets are promising tools for biomedical engineering because of the high throughput and the ease to finely tune the microenvironments. In addition to the great success of droplet biomicrofluidics in the proof-of-concept biosensing, regenerative medicine, and drug delivery, few droplet biomicrofluidic devices have a transformative impact on the industrial and clinical applications. The main issues are the low volume throughput and the lack of proper methods for quality control and automation. This review covers the methodologies for the mass production, detection, and automation of droplet generators. Recent advances in droplet mass production using parallelized devices and modified junction structures are discussed. Detection techniques, including optical and electrical detection methods, are comprehensively reviewed in detail. Newly emerged droplet closed-loop control systems are surveyed to highlight the progress in system integration and automation. Overall, with the advances in parallel droplet generation, highly sensitive detection, and robust closed-loop regulation, it is anticipated that the productivity and reliability of droplet biomicrofluidics will be significantly improved to meet the industrial and clinical needs.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Chronic Diseases and Health Monitoring Big Data: A Survey
    • Authors: Rongheng Lin;Zezhou Ye;Hao Wang;Budan Wu;
      Pages: 275 - 288
      Abstract: With the advancement of technology in data science and network technology, the world has stepped into the Era of Big Data, and the medical field is rich in data suitable for analysis. Thus, in recent years, there has been much research in medical big data, mainly targeting data collection, data analysis, and visualization. However, very few works provide a full survey of the medical big data on chronic diseases and health monitoring. This review investigates recent research efforts and conducts a comprehensive overview of the work on medical big data, especially as related to chronic diseases and health monitoring. It focuses on the full cycles of the big data processing, which includes medical big data preprocessing, big data tools and algorithms, big data visualization, and security issues in big data. It also attempts to combine common big data technologies with special medical needs by analyzing in detail existing works of medical big data. To the best of our knowledge, this is the first survey that targets chronic diseases and health monitoring big data technologies.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Advances in Automation Technologies for Lower Extremity
           Neurorehabilitation: A Review and Future Challenges
    • Authors: Wenhao Deng;Ioannis Papavasileiou;Zhi Qiao;Wenlong Zhang;Kam-Yiu Lam;Song Han;
      Pages: 289 - 305
      Abstract: The world is experiencing an unprecedented, enduring, and pervasive aging process. With more people who need walking assistance, the demand for lower extremity gait rehabilitation has increased rapidly over the years. The current clinical gait rehabilitative training requires heavy involvement of both medical doctors and physical therapists, and thus, are labor intensive, subjective, and expensive. To address these problems, advanced automation techniques, especially along with the proliferation of smart sensing and actuation devices and big data analytics platforms, have been introduced into this field to make the gait rehabilitation convenient, efficient, and personalized. This survey paper provides a comprehensive review on recent technological advances in wearable sensors, biofeedback devices, and assistive robots. Empowered by the emerging networking and computing technologies in the big data era, these devices are being interconnected into smart and connected rehabilitation systems to provide nonintrusive and continuous monitoring of physical and neurological conditions of the patients, perform complex gait analysis and diagnosis, and allow real-time decision making, biofeedback, and control of assistive robots. For each technology category, a detailed comparison among the existing solutions is provided. A thorough discussion is also presented on remaining open problems and future directions to further improve the safety, efficiency, and usability of the technologies.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Noncontact Wearable Wireless ECG Systems for Long-Term Monitoring
    • Authors: Sumit Majumder;Leon Chen;Ognian Marinov;Chih-Hung Chen;Tapas Mondal;M. Jamal Deen;
      Pages: 306 - 321
      Abstract: Electrocardiography (ECG) is the most common and extensively used vital sign monitoring method in modern healthcare systems. Different designs of ambulatory ECG systems were developed as alternatives to the commonly used 12-lead clinical ECG systems. These designs primarily focus on portability and user convenience, while maintaining signal integrity and lowering power consumption. Here, a wireless ECG monitoring system is developed using flexible and dry capacitive electrodes for long-term monitoring of cardiovascular health. Our capacitive-coupled dry electrodes can measure ECG signals over a textile-based interface material between the skin and electrodes. The electrodes are connected to a data acquisition system that receives the raw ECG signals from the electrodes and transmits the data using Bluetooth to a computer. A software application was developed to process, store, and display the ECG signal in real time. ECG measurements were obtained over different types of textile materials and in the presence of body movements. Our experimental results show that the performance of our ECG system is comparable to other reported ECG monitoring systems. In addition, to put this research into perspective, recent ambulatory ECG monitoring systems, ECG systems-on-chip, commercial ECG monitoring systems, and different state-of-the-art ECG systems are reviewed, compared, and critically discussed.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
  • Corrections to “Treatment of the Partial Hand Amputation: An
           Engineering Perspective”
    • Authors: Ilario Imbinto;Carlo Peccia;Marco Controzzi;Andrea Giovanni Cutti;Angelo Davalli;Rinaldo Sacchetti;Christian Cipriani;
      Pages: 322 - 322
      Abstract: In the above-named paper by Imbinto et al. (ibid., vol. 9, pp. 32–48, 2016), typographical errors appear in (1) (2) (3), whereas (4) is missing of a factor; all the equations are reported within Section III-C of the paper. The modifications are provided in this correction.
      PubDate: 2018
      Issue No: Vol. 11 (2018)
       
 
 
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