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  Subjects -> COMPUTER SCIENCE (Total: 2011 journals)
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COMPUTER SCIENCE (1172 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 15)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 24)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 9)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 13)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 16)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 6)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
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: 1)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 21)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 9)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 25)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
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: 26)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 16)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 6)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 18)
Advances in Computer Science : an International Journal     Open Access   (Followers: 15)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Advances in Engineering Software     Hybrid Journal   (Followers: 27)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 11)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 27)
Advances in Human-Computer Interaction     Open Access   (Followers: 21)
Advances in Materials Sciences     Open Access   (Followers: 16)
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: 40)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 4)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 8)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
Air, Soil & Water Research     Open Access   (Followers: 9)
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: 5)
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: 3)
Annals of Data Science     Hybrid Journal   (Followers: 11)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
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: 13)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Clinical Informatics     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
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: 15)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
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: 136)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
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: 4)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 11)
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)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 285)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 18)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 34)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 47)
British Journal of Educational Technology     Hybrid Journal   (Followers: 136)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 2)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
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: 1)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 20)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 55)
Communications of the Association for Information Systems     Open Access   (Followers: 18)
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: 9)
Computación y Sistemas     Open Access  
Computation     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
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: 11)
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: 15)
Computational Linguistics     Open Access   (Followers: 22)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 4)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
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: 90)
Computer Aided Surgery     Hybrid Journal   (Followers: 5)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 10)
Computer Engineering and Applications Journal     Open Access   (Followers: 5)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 22)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)
Computer Music Journal     Hybrid Journal   (Followers: 18)
Computer Physics Communications     Hybrid Journal   (Followers: 6)
Computer Science - Research and Development     Hybrid Journal   (Followers: 8)
Computer Science and Engineering     Open Access   (Followers: 19)
Computer Science and Information Technology     Open Access   (Followers: 13)
Computer Science Education     Hybrid Journal   (Followers: 14)
Computer Science Journal     Open Access   (Followers: 22)

        1 2 3 4 5 6 | Last

Journal Cover Biomedical Engineering, IEEE Transactions on
  [SJR: 1.201]   [H-I: 138]   [34 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0018-9294
   Published by IEEE Homepage  [191 journals]
  • IEEE Engineering in Medicine and Biology Society
    • PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • IEEE Transactions on Biomedical Engineering (T-BME)
    • PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • IEEE Transactions on Biomedical Engineering Handling Editors
    • PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Low-Cost Methodology for Skin Strain Measurement of a Flexed Biological
    • Authors: Bevin Lin;Kevin M. Moerman;Connor G. McMahan;Kenneth A. Pasch;Hugh M. Herr;
      Pages: 2750 - 2759
      Abstract: Objective: The purpose of this manuscript is to compute skin strain data from a flexed biological limb, using portable, inexpensive, and easily available resources. Methods: We apply and evaluate this approach on a person with bilateral transtibial amputations, imaging left and right residual limbs in extended and flexed knee postures. We map 3-D deformations to a flexed biological limb using freeware and a simple point-and-shoot camera. Mean principal strain, maximum shear strain, as well as lines of maximum, minimum, and nonextension are computed from 3-D digital models to inform directional mappings of the strain field for an unloaded residual limb. Results: Peak tensile strains are ∼0.3 on the anterior surface of the knee in the proximal region of the patella, whereas peak compressive strains are ∼ −0.5 on the posterior surface of the knee. Peak maximum shear strains are ∼0.3 on the posterior surface of the knee. The accuracy and precision of this methodology are assessed for a ground-truth model. The mean point location distance is found to be 0.08 cm, and the overall standard deviation for point location difference vectors is 0.05 cm. Conclusion: This low-cost and mobile methodology may prove critical for applications such as the prosthetic socket interface where whole-limb skin strain data are required from patients in the field outside of traditional, large-scale clinical centers. Significance: Such data may inform the design of wearable technologies that directly interface with human skin.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Optimal Control of Inspired Perfluorocarbon Temperature for Ultrafast
           Hypothermia Induction by Total Liquid Ventilation in an Adult Patient
    • Authors: Mathieu Nadeau;Michaël Sage;Matthias Kohlhauer;Julien Mousseau;Jonathan Vandamme;Étienne Fortin-Pellerin;Jean-Paul Praud;Renaud Tissier;Hervé Walti;Philippe Micheau;
      Pages: 2760 - 2770
      Abstract: Goal: Recent preclinical studies have shown that therapeutic hypothermia induced in less than 30 min by total liquid ventilation (TLV) strongly improves the survival rate after cardiac arrest. When the lung is ventilated with a breathable perfluorocarbon liquid, the inspired perfluorocarbon allows us to control efficiently the cooling process of the organs. While TLV can rapidly cool animals, the cooling speed in humans remains unknown. The objective is to predict the efficiency and safety of ultrafast cooling by TLV in adult humans. Methods:  It is based on a previously published thermal model of ovines in TLV and the design of a direct optimal controller to compute the inspired perfluorocarbon temperature profile. The experimental results in an adult sheep are presented. The thermal model of sheep is subsequently projected to a human model to simulate the optimal hypothermia induction and its sensitivity to physiological parameter uncertainties. Results: The results in the sheep showed that the computed inspired perfluorocarbon temperature command can avoid arterial temperature undershoot. The projection to humans revealed that mild hypothermia should be ultrafast (reached in fewer than 3 min (−72 °C/h) for the brain and 20 min (−10 °C/h) for the entire body). Conclusion: The projection to human model allows concluding that therapeutic hypothermia induction by TLV can be ultrafast and safe. Significance: This study is the first to simulate ultrafast cooling by TLV in a human model and is a strong motivation to translate TLV to humans to improve the quality of life of postcardiac arrest patients.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Simultaneous Measurement of Multiple Mechanical Properties of Single Cells
           Using AFM by Indentation and Vibration
    • Authors: Chuang Zhang;Jialin Shi;Wenxue Wang;Ning Xi;Yuechao Wang;Lianqing Liu;
      Pages: 2771 - 2780
      Abstract: Objective: The mechanical properties of cells, which are the main characteristics determining their physical performance and physiological functions, have been actively studied in the fields of cytobiology and biomedical engineering and for the development of medicines. In this study, an indentation-vibration-based method is proposed to simultaneously measure the mechanical properties of cells in situ, including cellular mass (m), elasticity (k), and viscosity (c).Methods: The proposed measurement method is implemented based on the principle of forced vibration stimulated by simple harmonic force using an atomic force microscope (AFM) system integrated with a piezoelectric transducer as the substrate vibrator. The corresponding theoretical model containing the three mechanical properties is derived and used to perform simulations and calculations. Living and fixed human embryonic kidney 293 (HEK 293) cells were subjected to indentation and vibration to measure and compare their mechanical parameters and verify the proposed approach. Results: The results that the fixed sample cells are more viscous and elastic than the living sample cells and the measured mechanical properties of cell are consistent within, but not outside of the central region of the cell, are in accordance with the previous studies.Conclusion: This work provides an approach to simultaneous measurement of the multiple mechanical properties of single cells using an integrated AFM system based on the principle force vibration and thickness-corrected Hertz model. Significance: This study should contribute to progress in biomedical engineering, cytobiology, medicine, early diagnosis, specific therapy and cell-powered robots.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Living-Skin Classification via Remote-PPG
    • Authors: Wenjin Wang;Sander Stuijk;Gerard de Haan;
      Pages: 2781 - 2792
      Abstract: Detecting living-skin tissue in a video on the basis of induced color changes due to blood pulsation is emerging for automatic region of interest localization in remote photoplethysmography (rPPG). However, the state-of-the-art method performing unsupervised living-skin detection in a video is rather time consuming, which is mainly due to the high complexity of its unsupervised online learning for pulse/noise separation. In this paper, we address this issue by proposing a fast living-skin classification method. Our basic idea is to transform the time-variant rPPG-signals into signal shape descriptors called “multiresolution iterative spectrum,” where pulse and noise have different patterns enabling accurate binary classification. The proposed technique is a proof-of-concept that has only been validated in lab conditions but not in real clinical conditions. The benchmark, including synthetic and realistic (nonclinical) experiments, shows that it achieves a high detection accuracy better than the state-of-the-art method, and a high detection speed at hundreds of frames per second in MATLAB, enabling real-time living-skin detection.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Non-invasive Fetal ECG Signal Quality Assessment for Multichannel Heart
           Rate Estimation
    • Authors: Fernando Andreotti;Felix Gräßer;Hagen Malberg;Sebastian Zaunseder;
      Pages: 2793 - 2802
      Abstract: Objective: The noninvasive fetal ECG (NI-FECG) from abdominal recordings offers novel prospects for prenatal monitoring. However, NI-FECG signals are corrupted by various nonstationary noise sources, making the processing of abdominal recordings a challenging task. In this paper, we present an online approach that dynamically assess the quality of NI-FECG to improve fetal heart rate (FHR) estimation. Methods: Using a naive Bayes classifier, state-of-the-art and novel signal quality indices (SQIs), and an existing adaptive Kalman filter, FHR estimation was improved. For the purpose of training and validating the proposed methods, a large annotated private clinical dataset was used. Results: The suggested classification scheme demonstrated an accuracy of Krippendorff's alpha $ = {text{0.65}}$ in determining the overall quality of NI-FECG signals. The proposed Kalman filter outperformed alternative methods for FHR estimation achieving ${text{75.6}%}$ accuracy. Conclusion: The proposed algorithm was able to reliably reflect changes of signal quality and can be used in improving FHR estimation. Significance: NI-ECG signal quality estimation and multichannel information fusion are largely unexplored topics. Based on previous works, multichannel FHR estimation is a field that could strongly benefit from such methods. The developed SQI algorithms as well as resulting classifier were made available under a GNU GPL open-source license and contributed to the FECGSYN toolbox.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Structured Learning for 3-D Perivascular Space Segmentation Using Vascular
    • Authors: Jun Zhang;Yaozong Gao;Sang Hyun Park;Xiaopeng Zong;Weili Lin;Dinggang Shen;
      Pages: 2803 - 2812
      Abstract: Objective: The goal of this paper is to automatically segment perivascular spaces (PVSs) in brain from high-resolution 7T magnetic resonance (MR) images. Methods: We propose a structured-learning-based segmentation framework to extract the PVSs from high-resolution 7T MR images. Specifically, we integrate three types of vascular filter responses into a structured random forest for classifying voxels into two categories, i.e., PVS and background. In addition, we propose a novel entropy-based sampling strategy to extract informative samples in the background for training an explicit classification model. Since the vascular filters can extract various vascular features, even thin and low-contrast structures can be effectively extracted from noisy backgrounds. Moreover, continuous and smooth segmentation results can be obtained by utilizing patch-based structured labels. Results: The performance of our proposed method is evaluated on 19 subjects with 7T MR images, with the Dice similarity coefficient reaching 66%. Conclusion: The joint use of entropy-based sampling strategy, vascular features, and structured learning can improve the segmentation accuracy. Significance: Instead of manual annotation, our method provides an automatic way for PVS segmentation. Moreover, our method can be potentially used for other vascular structure segmentation because of its data-driven property.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Numerical Model Study of In Vivo Magnetic Nanoparticle
           Tumor Heating
    • Authors: John A. Pearce;Alicia A. Petryk;P. Jack Hoopes;
      Pages: 2813 - 2823
      Abstract: Iron oxide nanoparticles are currently under investigation as heating agents for hyperthermic treatment of tumors. Major determinants of effective heating include the biodistribution and minimum iron oxide loading required to achieve adequate heating at practically achievable magnetic field strengths. These inter-related criteria ultimately determine the practicality of this approach to tumor treatment. Further, in our experience the currently used treatment assessment criterion for hyperthermia treatment—cumulative equivalent minutes at 43 °C, CEM43 —provides an inadequate description of the expected treatment effectiveness. Objectives: Couple numerical models to experimental measurements to study the relative heating effectiveness described by cell death predictions. Methods: FEM numerical models were applied to increase the understanding of a carefully calibrated series of experiments in mouse mammary adenocarcinoma. Results: The numerical model results indicate that minimum tumor loadings between approximately 1.3 to 1.8 mg of Fe per cm3 of tumor tissue are required to achieve the experimentally observed temperatures in magnetic field strengths of 32 kA/m (rms) at 162 kHz. Conclusion: We show that including multiple cell death processes operating in parallel within the numerical models provides valuable perspective on the likelihood of successful treatment.Significance: We show and believe that these assessment methods are more accurate than a single assessment figure of merit based only on the comparison of thermal histories, such as the CEM method.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • 3-D-Gaze-Based Robotic Grasping Through Mimicking Human Visuomotor
           Function for People With Motion Impairments
    • Authors: Songpo Li;Xiaoli Zhang;Jeremy D. Webb;
      Pages: 2824 - 2835
      Abstract: Objective: The goal of this paper is to achieve a novel 3-D-gaze-based human–robot-interaction modality, with which a user with motion impairment can intuitively express what tasks he/she wants the robot to do by directly looking at the object of interest in the real world. Toward this goal, we investigate 1) the technology to accurately sense where a person is looking in real environments and 2) the method to interpret the human gaze and convert it into an effective interaction modality. Looking at a specific object reflects what a person is thinking related to that object, and the gaze location contains essential information for object manipulation. Methods: A novel gaze vector method is developed to accurately estimate the 3-D coordinates of the object being looked at in real environments, and a novel interpretation framework that mimics human visuomotor functions is designed to increase the control capability of gaze in object grasping tasks. Results: High tracking accuracy was achieved using the gaze vector method. Participants successfully controlled a robotic arm for object grasping by directly looking at the target object. Conclusion: Human 3-D gaze can be effectively employed as an intuitive interaction modality for robotic object manipulation. Significance: It is the first time that 3-D gaze is utilized in a real environment to command a robot for a practical application. Three-dimensional gaze tracking is promising as an intuitive alternative for human–robot interaction especially for disabled and elderly people who cannot handle the conventional interaction modalities.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Reference-Free Adjustment of Respiratory Inductance Plethysmography for
           Measurements during Physical Exercise
    • Authors: Heike Leutheuser;Christian Heyde;Kai Roecker;Albert Gollhofer;Bjoern M. Eskofier;
      Pages: 2836 - 2846
      Abstract: Objective: Respiratory inductance plethysmography (RIP) provides an unobtrusive method for measuring breathing characteristics. Accurately adjusted RIP provides reliable measurements of ventilation during rest and exercise if data are acquired via two elastic measuring bands surrounding the rib cage (RC) and abdomen (AB). Disadvantageously, the most accurate reported adjusted model for RIP in literature—least squares regression—requires simultaneous RIP and flowmeter (FM) data acquisition. An adjustment method without simultaneous measurement (reference-free) of RIP and FM would foster usability enormously. Methods: In this paper, we develop generalizable, functional, and reference-free algorithms for RIP adjustment incorporating anthropometric data. Further, performance of only one-degree of freedom (RC or AB) instead of two (RC and AB) is investigated. We evaluate the algorithms with data from 193 healthy subjects who performed an incremental running test using three different datasets: training, reliability, and validation dataset. The regression equation is improved with machine learning techniques such as sequential forward feature selection and 10-fold cross validation. Results: Using the validation dataset, the best reference-free adjustment model is the combination of both bands with 84.69% breaths within $pm$  20% limits of equivalence compared to 43.63% breaths using the best comparable algorithm from literature. Using only one band, we obtain better results using the RC band alone. Conclusion: Reference-free adjustment for RIP reveals tidal volume differences of up to 0.25 l when comparing to the best possible adjustment currently present which needs the simultaneous measurement of RIP and FM. Si-nificance: This demonstrates that RIP has the potential for usage in wide applications in ambulatory settings.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Quantitative Comparison of Spherical Deconvolution Approaches to Resolve
           Complex Fiber Configurations in Diffusion MRI: ISRA-Based vs L2L0 Sparse
    • Authors: Alfonso Mastropietro;Paola Scifo;Giovanna Rizzo;
      Pages: 2847 - 2857
      Abstract: Objective: To quantitatively compare different spherical deconvolution (SD) approaches (ISRA-based and sparse L2L0 algorithms) to resolve crossing fiber in diffusion MRI. The purpose of this comparison is to address the area of application in which each approach could better perform. Methods: Image Space Reconstruction Algorithm (ISRA)-based [Richardson–Lucy (RL), damped-RL] and sparse L2L0 algorithms were implemented and evaluated on both simulated data and in vivo datasets. Simulations were performed at different crossing angles (30°–90°), b-values (1000–3000 s/mm2), SNR (10–30), number of fibers (1–3). Isotropic compartments and different fiber volume fractions were included to obtain more realistic configurations. In vivo datasets were acquired to confirm simulated results. Results: A decrease of SNR or b-value reduces the performances of both approaches. L2L0 methods have better performances at low crossing angles (30°–45°) whereas ISRA methods slightly prevail at high crossing angles (>70°). In the medium crossing angle range, the performance depends on the b-value. In the case of single and 3 fibers configurations as well as in complex scenarios (isotropic components, different partial volumes), ISRA algorithms were able to resolve fiber crossing more accurately and they outperform sparse L2L0 methods. In vivo results confirmed simulated trends. Conclusion: Both classes of algorithms can effectively resolve fiber crossing. L2L0 methods are more effective at low crossing angles whereas ISRA approaches have better performances at high angl-s and are more robust in more realistic configurations. Significance: This work provides useful indications to select the best performing SD algorithm depending on the specific application.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Accurate 3-D Profile Extraction of Skull Bone Using an Ultrasound Matrix
    • Authors: Mehdi Hajian;Robert Gaspar;Roman Gr. Maev;
      Pages: 2858 - 2871
      Abstract: The present study investigates the feasibility, accuracy, and precision of 3-D profile extraction of the human skull bone using a custom-designed ultrasound matrix transducer in Pulse-Echo. Due to the attenuative scattering properties of the skull, the backscattered echoes from the inner surface of the skull are severely degraded, attenuated, and at some points overlapped. Furthermore, the speed of sound (SOS) in the skull varies significantly in different zones and also from case to case; if considered constant, it introduces significant error to the profile measurement. A new method for simultaneous estimation of the skull profiles and the sound speed value is presented. The proposed method is a two-folded procedure: first, the arrival times of the backscattered echoes from the skull bone are estimated using multi-lag phase delay (MLPD) and modified space alternating generalized expectation maximization (SAGE) algorithms. Next, these arrival times are fed into an adaptive sound speed estimation algorithm to compute the optimal SOS value and subsequently, the skull bone thickness. For quantitative evaluation, the estimated bone phantom thicknesses were compared with the mechanical measurements. The accuracies of the bone thickness measurements using MLPD and modified SAGE algorithms combined with the adaptive SOS estimation were 7.93% and 4.21%, respectively. These values were 14.44% and 10.75% for the autocorrelation and cross-correlation methods. Additionally, the Bland–Altman plots showed the modified SAGE outperformed the other methods with –0.35 and 0.44 mm limits of agreement. No systematic error that could be related to the skull bone thickness was observed for this method.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Refined Composite Multiscale Dispersion Entropy and its Application to
           Biomedical Signals
    • Authors: Hamed Azami;Mostafa Rostaghi;Daniel Abásolo;Javier Escudero;
      Pages: 2872 - 2879
      Abstract: Objective: We propose a novel complexity measure to overcome the deficiencies of the widespread and powerful multiscale entropy (MSE), including, MSE values may be undefined for short signals, and MSE is slow for real-time applications. Methods: We introduce multiscale dispersion entropy (DisEn—MDE) as a very fast and powerful method to quantify the complexity of signals. MDE is based on our recently developed DisEn, which has a computation cost of O(N), compared with O(N2) for sample entropy used in MSE. We also propose the refined composite MDE (RCMDE) to improve the stability of MDE. Results: We evaluate MDE, RCMDE, and refined composite MSE (RCMSE) on synthetic signals and three biomedical datasets. The MDE, RCMDE, and RCMSE methods show similar results, although the MDE and RCMDE are faster, lead to more stable results, and discriminate different types of physiological signals better than MSE and RCMSE. Conclusion: For noisy short and long time series, MDE and RCMDE are noticeably more stable than MSE and RCMSE, respectively. For short signals, MDE and RCMDE, unlike MSE and RCMSE, do not lead to undefined values. The proposed MDE and RCMDE are significantly faster than MSE and RCMSE, especially for long signals, and lead to larger differences between physiological conditions known to alter the complexity of the physiological recordings. Significance : MDE and RCMDE are expected to be useful for the analysis of physiological signals thanks to their ability to distinguish different types of dynamics. The MATLAB codes used in this paper are freely available at
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Synergistic Effects of Nanodrug, Ultrasound Hyperthermia, and Thermal
           Ablation on Solid Tumors—An Animal Study
    • Authors: Li-Chen Chiu;Sheng-Kai Wu;Win-Li Lin;Gin-Shin Chen;
      Pages: 2880 - 2889
      Abstract: Objective: Delivery barriers of nanodrug in large tumors due to heterogeneous blood supply, elevated interstitial pressure, and long transport distances can degrade the efficacy of cancer treatment. In this study, we proposed a therapeutic strategy to improve the tumor growth inhibition by injecting pegylated liposomal doxorubicin (PLD), and then applying a short time of ultrasound hyperthermia (HT) on the entire solid tumor, and inflicting ultrasound thermal ablation (Ab) in the low-perfused tumor region. Methods: BALB/c female mice with an average weight of 20 g were adopted and murine breast cancer cells 4T1 were subcutaneously implanted into the flank. A 1.0-MHz planar and a 0.47-MHz focused ultrasound transducers were used, respectively, for the HT and Ab treatment. Results: For a PLD dose of 5 mg/kg, the PLD + HT(42 °C, 10 min) group caused a significant decrease in the tumor size as compared with the control and the PLD group, but there were no significant differences between the PLD + HT group and the PLD + Ab(56 °C, 49 s) + HT group. For a PLD dose of 3 mg/kg, the tumor sizes among the four groups were mutually significant. The level of reduction in tumor was PLD + Ab + HT > PLD + HT > PLD > control. Conclusion: The combination of anticancer nanodrug and ultrasound thermal treatment could remarkably suppress cancer tumor growth with a minimum compromise of side effects. Significance: The strategy of using thermal Ab in locations that are not reached by nanodrug w-th mild HT shows a promising potential for the entire tumor treatment.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • A Framework for Patient State Tracking by Classifying Multiscalar
           Physiologic Waveform Features
    • Authors: Benjamin Vandendriessche;Mustafa Abas;Thomas E. Dick;Kenneth A. Loparo;Frank J. Jacono;
      Pages: 2890 - 2900
      Abstract: Objective: state-of-the-art algorithms that quantify nonlinear dynamics in physiologic waveforms are underutilized clinically due to their esoteric nature. We present a generalizable framework for classifying multiscalar waveform features, designed for patient-state tracking directly at the bedside. Methods: an artificial neural network classifier was designed to evaluate multiscale waveform features against a fingerprint database of multifractal synthetic time series. The results are mapped into a physiologic state space for near real-time patient-state tracking. Results: the framework was validated on cardiac beat-to-beat dynamics processed with the multiscale entropy algorithm, and assessed using PhysioNet databases. We then applied our algorithm to predict 28-day mortality for sepsis patients, and found it had greater prognostic accuracy than standard clinical severity scores. Conclusion: we developed a novel framework to classify multiscale features of beat-to-beat dynamics, and performed an initial clinical validation to demonstrate that our approach generates a robust quantification of a patient's state, compatible with real-time bedside implementations. Significance: the framework generates meaningful and actionable patient-specific information, and could facilitate the dissemination of a new class of “always-on” diagnostic tools.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Gland Instance Segmentation Using Deep Multichannel Neural Networks
    • Authors: Yan Xu;Yang Li;Yipei Wang;Mingyuan Liu;Yubo Fan;Maode Lai;Eric I-Chao Chang;
      Pages: 2901 - 2912
      Abstract: Objective: A new image instance segmentation method is proposed to segment individual glands (instances) in colon histology images. This process is challenging since the glands not only need to be segmented from a complex background, they must also be individually identified. Methods: We leverage the idea of image-to-image prediction in recent deep learning by designing an algorithm that automatically exploits and fuses complex multichannel information—regional, location, and boundary cues—in gland histology images. Our proposed algorithm, a deep multichannel framework, alleviates heavy feature design due to the use of convolutional neural networks and is able to meet multifarious requirements by altering channels. Results: Compared with methods reported in the 2015 MICCAI Gland Segmentation Challenge and other currently prevalent instance segmentation methods, we observe state-of-the-art results based on the evaluation metrics. Conclusion: The proposed deep multichannel algorithm is an effective method for gland instance segmentation. Significance: The generalization ability of our model not only enable the algorithm to solve gland instance segmentation problems, but the channel is also alternative that can be replaced for a specific task.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Dual-Channel Active Contour Model for Megakaryocytic Cell Segmentation in
           Bone Marrow Trephine Histology Images
    • Authors: Tzu-Hsi Song;Victor Sanchez;Hesham EIDaly;Nasir M. Rajpoot;
      Pages: 2913 - 2923
      Abstract: Assessment of morphological features of megakaryocytes (MKs) (special kind of cells) in bone marrow trephine biopsies play an important role in the classification of different subtypes of Philadelphia-chromosome-negative myeloproliferative neoplasms (Ph-negative MPNs). In order to aid hematopathologists in the study of MKs, we propose a novel framework that can efficiently delineate the nuclei and cytoplasm of these cells in digitized images of bone marrow trephine biopsies. The framework first employs a supervised machine learning approach that utilizes color and texture features to delineate megakaryocytic nuclei. It then employs a novel dual-channel active contour model to delineate the boundary of megakaryocytic cytoplasm by using different deconvolved stain channels. Compared to other recent models, the proposed framework achieves accurate results for both megakaryocytic nuclear and cytoplasmic delineation.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Bipolar Microsecond Pulses and Insulated Needle Electrodes for Reducing
           Muscle Contractions During Irreversible Electroporation
    • Authors: Chenguo Yao;Shoulong Dong;Yajun Zhao;Yanpeng Lv;Hongmei Liu;Lingyu Gong;Jianhao Ma;Haifeng Wang;Yinghao Sun;
      Pages: 2924 - 2937
      Abstract: Objective: To minimize the effect of muscle contractions during irreversible electroporation (IRE), this paper attempts to research the ablation effect and muscle contractions by applying high-frequency IRE (H-FIRE) ablation to liver tissue in vivo. Methods: An insulated needle electrode was produced by painting an insulating coating on the outer surface of the needle electrode tip. A series of experiments were conducted using insulated needle electrodes and traditional needle electrodes to apply H-FIRE pulses and traditional monopolar IRE pulses to rabbit liver tissues. The finite element model of the rabbit liver tissue was established to determine the lethal thresholds of H-FIRE in liver tissues. Muscle contractions were measured by an accelerometer. Results: With increased constitutive pulse width and pulse voltage, the ablation area and muscle contraction strength are also increased, which can be used to optimize the ablation parameters of H-FIRE. Under the same pulse parameters, the ablation areas are similar for the two types of electrodes, and the ablation region has a clear boundary. H-FIRE and insulated needle electrodes can mitigate the extent of muscle contractions. The lethal thresholds of H-FIRE in rabbit liver tissues were determined. Conclusion: This paper describes the relationships between the ablation area, muscle contractions, and pulse parameters; the designed insulated needle electrodes can be used in IRE for reducing muscle contraction. Significance: The study provides guidance for treatment planning and reducing muscle contractions in the clinical application of H-FIRE.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • A Computational Study of Vocal Fold Dehydration During Phonation
    • Authors: Liang Wu;Zhaoyan Zhang;
      Pages: 2938 - 2948
      Abstract: While vocal fold dehydration is often considered an important factor contributing to vocal fatigue, it still remains unclear whether vocal fold vibration alone is able to induce severe dehydration that has a noticeable effect on phonation and perceived vocal effort. A three-dimensional model was developed to investigate vocal fold systemic dehydration and surface dehydration during phonation. Based on the linear poroelastic theory, the model considered water resupply from blood vessels through the lateral boundary, water movement within the vocal folds, water exchange between the vocal folds and the surface liquid layer through the epithelium, and surface fluid accumulation and discharge to the glottal airway. Parametric studies were conducted to investigate water loss within the vocal folds and from the surface after a 5-min sustained phonation under different permeability and vibration conditions. The results showed that the dehydration generally increased with increasing vibration amplitude, increasing epithelial permeability, and reduced water resupply. With adequate water resupply, a large-amplitude vibration can induce an overall systemic dehydration as high as 3%. The distribution of water loss within the vocal folds was non-uniform, and a local dehydration higher than 5% was observed even under conditions of a low overall systemic dehydration (
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Stiffness Perception During Active Ankle and Knee Movement
    • Authors: Alejandro F. Azocar;Elliott J. Rouse;
      Pages: 2949 - 2956
      Abstract: Objective: Recently, human joint impedance—the instantaneous mechanical response to a perturbation—has been quantified during gait, providing new insight beyond the traditional biomechanical descriptions of kinetics and kinematics. However, the role of joint impedance in neuromotor control and the development of exoskeletons and other wearable robotic systems remains unknown. One approach to studying the role of impedance in neuromotor control involves characterizing the human ability to discriminate changes in external impedance properties. Thus, the purpose of this work is to quantify the minimum detectable change in the stiffness component of impedance when interacting with an external mechanical impedance at the human ankle or knee. Methods: A dynamometer coupled to subjects’ right ankle or knee rendered the dynamics of a virtual rotational spring-mass-damper system. The minimum detectable change, or just noticeable difference, was determined via a weighted up–down staircase method in which subjects compared the stiffness values of two different controller configurations. Results: We found that subjects could reliably detect stiffness changes of at least 12% at the ankle and 13% at the knee. Conclusion: Stiffness errors or variations produced by an external mechanical device will be undetected if they remain below the 12–13% threshold. Significance: Our results provide novel insight into how the sensorimotor system senses joint impedance, information that may improve the design and control of impedance-based wearable robotic technologies.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Model-Based Estimation of Respiratory Parameters from Capnography, With
           Application to Diagnosing Obstructive Lung Disease
    • Authors: Abubakar Abid;Rebecca J. Mieloszyk;George C. Verghese;Baruch S. Krauss;Thomas Heldt;
      Pages: 2957 - 2967
      Abstract: Objective: We use a single-alveolar-compartment model to describe the partial pressure of carbon dioxide in exhaled breath, as recorded in time-based capnography. Respiratory parameters are estimated using this model, and then related to the clinical status of patients with obstructive lung disease. Methods: Given appropriate assumptions, we derive an analytical solution of the model, describing the exhalation segment of the capnogram. This solution is parametrized by alveolar CO2 concentration, dead-space fraction, and the time constant associated with exhalation. These quantities are estimated from individual capnogram data on a breath-by-breath basis. The model is applied to analyzing datasets from normal (n = 24) and chronic obstructive pulmonary disease (COPD) (n = 22) subjects, as well as from patients undergoing methacholine challenge testing for asthma (n = 22). Results: A classifier based on linear discriminant analysis in logarithmic coordinates, using estimated dead-space fraction and exhalation time constant as features, and trained on data from five normal and five COPD subjects, yielded an area under the receiver operating characteristic curve (AUC) of 0.99 in classifying the remaining 36 subjects as normal or COPD. Bootstrapping with 50 replicas yielded a 95% confidence interval of AUCs from 0.96 to 1.00. For patients undergoing methacholine challenge testing, qualitatively meaningful trends were observed in the parameter variations over the course of the test. Significance: A simple mechanistic model allows estimation of underlying respiratory parameters from the capnogram, and may be applied to diagnosis and monitoring of chronic and reversible obstructive lung disease.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Automatic Identification of Human Blastocyst Components via Texture
    • Authors: Parvaneh Saeedi;Dianna Yee;Jason Au;Jon Havelock;
      Pages: 2968 - 2978
      Abstract: Choosing the most viable embryo during human in vitro fertilization (IVF) is a prime factor in maximizing pregnancy rate. Embryologists visually inspect morphological structures of blastocysts under microscopes to gauge their health. Such grading introduces subjectivity amongst embryologists and adds to the difficulty of quality control during IVF. In this paper, we introduce an algorithm for automatic segmentation of two main components of human blastocysts named: Trophectoderm (TE) and inner cell mass (ICM). We utilize texture information along with biological and physical characteristics of day-5 human embryos (blastocysts) to identify TE or ICM regions according to their intrinsic properties. Both these regions are highly textured and very similar in the quality of their texture, and they often look connected to each other when imaged. These attributes make their automatic identification and separation from each other a difficult task even for an expert embryologist. By automatically identifying TE and ICM regions, we offer the opportunity to perform more detailed assessment of blastocysts. This could help in analyzing, in a quantitative way, various visual/geometrical characteristics of these regions that when combined with the pregnancy outcome can determine the predictive values of such attributes. Our work aids future research in understanding why certain embryos have higher pregnancy success rates. This paper is tested on a set of 211 blastocyst images. We report an accuracy of 86.6% for identification of TE and 91.3% for ICM.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Effects of Flexible Dry Electrode Design on Electrodermal Activity
           Stimulus Response Detection
    • Authors: Peter A. Haddad;Amir Servati;Saeid Soltanian;Frank Ko;Peyman Servati;
      Pages: 2979 - 2987
      Abstract: Objective: The focus of this research is to evaluate the effects of design parameters including surface area, distance between and geometry of dry flexible electrodes on electrodermal activity (EDA) stimulus response detection. Methods: EDA is a result of the autonomic nervous system being stimulated, which causes sweat and changes the electrical characteristics of the skin. Standard silver/silver chloride (Ag/AgCl) EDA electrodes are rigid and lack conformability in contact with skin. In this study, flexible dry Ag/AgCl EDA electrodes were fabricated on a compliant substrate, used to monitor EDA stimulus responses and compared to results simultaneously collected by rigid dry Ag/AgCl electrodes. Results: A repeatable fabrication process for flexible Ag/AgCl electrodes has been established. Surface area, distance between and geometry of electrodes are shown to affect the detectability of the EDA response and the minimum number of sweat glands to be covered by the electrodes has been estimated at 140, or more, in order to maintain functionality. The optimal flexible EDA electrode is a serpentine design with a 0.15 cm2 surface area and a 0.20 cm distance with an average Pearson correlation coefficient of $text{0.979} pm text{0.015}$ . Conclusion: Fabrication of flexible electrodes is described and an understanding of the effects of electrode designs on the EDA stimulus response detection has been established and is potentially related to the coverage of sweat glands. Significance: This work presents a novel systematic approach to understand the effects of electrode designs on monitoring EDA which is of importance for the design of wearable EDA monitoring devices.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • Quantifying and Characterizing Tonic Thermal Pain Across Subjects From EEG
           Data Using Random Forest Models
    • Authors: Vishal Vijayakumar;Michelle Case;Sina Shirinpour;Bin He;
      Pages: 2988 - 2996
      Abstract: Objective: Effective pain assessment and management strategies are needed to better manage pain. In addition to self-report, an objective pain assessment system can provide a more complete picture of the neurophysiological basis for pain. In this study, a robust and accurate machine learning approach is developed to quantify tonic thermal pain across healthy subjects into a maximum of ten distinct classes. Methods: A random forest model was trained to predict pain scores using time–frequency wavelet representations of independent components obtained from electroencephalography (EEG) data, and the relative importance of each frequency band to pain quantification is assessed. Results: The mean classification accuracy for predicting pain on an independent test subject for a range of 1–10 is 89.45%, highest among existing state of the art quantification algorithms for EEG. The gamma band is the most important to both intersubject and intrasubject classification accuracy. Conclusion: The robustness and generalizability of the classifier are demonstrated. Significance: Our results demonstrate the potential of this tool to be used clinically to help us to improve chronic pain treatment and establish spectral biomarkers for future pain-related studies using EEG.
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • BSN 2018 Body Sensor Networks Conference
    • Pages: 2997 - 2997
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • BHI-2018 IEEE International Conference on Biomedical and Health
    • Pages: 2998 - 2998
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
  • IEEE International Symposium on Biomedical Imaging
    • Pages: 2999 - 2999
      PubDate: Dec. 2017
      Issue No: Vol. 64, No. 12 (2017)
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