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  Subjects -> ENGINEERING (Total: 2277 journals)
    - CHEMICAL ENGINEERING (191 journals)
    - CIVIL ENGINEERING (184 journals)
    - ELECTRICAL ENGINEERING (103 journals)
    - ENGINEERING (1203 journals)
    - ENGINEERING MECHANICS AND MATERIALS (381 journals)
    - HYDRAULIC ENGINEERING (55 journals)
    - INDUSTRIAL ENGINEERING (69 journals)
    - MECHANICAL ENGINEERING (91 journals)

ENGINEERING (1203 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 7)
3D Research     Hybrid Journal   (Followers: 18)
AAPG Bulletin     Hybrid Journal   (Followers: 7)
AASRI Procedia     Open Access   (Followers: 15)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
ACS Nano     Full-text available via subscription   (Followers: 246)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 2)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 7)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 6)
Advanced Science     Open Access   (Followers: 5)
Advanced Science Focus     Free   (Followers: 3)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Engineering Software     Hybrid Journal   (Followers: 26)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 10)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 22)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 26)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 29)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in OptoElectronics     Open Access   (Followers: 5)
Advances in Physics Theories and Applications     Open Access   (Followers: 12)
Advances in Polymer Science     Hybrid Journal   (Followers: 41)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 39)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 2)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 5)
AIChE Journal     Hybrid Journal   (Followers: 32)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access  
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 28)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 11)
American Journal of Engineering Education     Open Access   (Followers: 9)
American Journal of Environmental Engineering     Open Access   (Followers: 17)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
Analele Universitatii Ovidius Constanta - Seria Chimie     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Regional Science     Hybrid Journal   (Followers: 8)
Annals of Science     Hybrid Journal   (Followers: 7)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 6)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 16)
Applied Clay Science     Hybrid Journal   (Followers: 5)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 8)
Applied Network Science     Open Access   (Followers: 1)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 3)
Applied Sciences     Open Access   (Followers: 2)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 7)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ASEE Prism     Full-text available via subscription   (Followers: 3)
Asia-Pacific Journal of Science and Technology     Open Access  
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 1)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 8)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Current Engineering & Maths     Open Access  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Avances en Ciencias e Ingeniería     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Batteries     Open Access   (Followers: 6)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 23)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 4)
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Biofuels Engineering     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 10)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 17)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 33)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 9)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomedizinische Technik - Biomedical Engineering     Hybrid Journal  
Biomicrofluidics     Open Access   (Followers: 4)
BioNanoMaterials     Hybrid Journal   (Followers: 2)
Biotechnology Progress     Hybrid Journal   (Followers: 39)
Boletin Cientifico Tecnico INIMET     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 14)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 13)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 27)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 45)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 8)
Case Studies in Thermal Engineering     Open Access   (Followers: 4)
Catalysis Communications     Hybrid Journal   (Followers: 6)
Catalysis Letters     Hybrid Journal   (Followers: 2)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 8)
Catalysis Science and Technology     Free   (Followers: 7)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 8)
CEAS Space Journal     Hybrid Journal   (Followers: 1)
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal   (Followers: 1)
CFD Letters     Open Access   (Followers: 6)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencias Holguin     Open Access   (Followers: 1)
CienciaUAT     Open Access  
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Full-text available via subscription   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Full-text available via subscription   (Followers: 14)
City, Culture and Society     Hybrid Journal   (Followers: 23)
Clay Minerals     Full-text available via subscription   (Followers: 10)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 5)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 1)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 13)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 27)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 265)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 190)
Composites Part B : Engineering     Hybrid Journal   (Followers: 260)
Composites Science and Technology     Hybrid Journal   (Followers: 185)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 15)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 7)
Computer Science and Engineering     Open Access   (Followers: 17)
Computers & Geosciences     Hybrid Journal   (Followers: 28)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 6)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 4)
Computers and Geotechnics     Hybrid Journal   (Followers: 10)
Computing and Visualization in Science     Hybrid Journal   (Followers: 5)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 31)
Conciencia Tecnologica     Open Access  
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 7)
Control and Dynamic Systems     Full-text available via subscription   (Followers: 9)
Control Engineering Practice     Hybrid Journal   (Followers: 43)
Control Theory and Informatics     Open Access   (Followers: 8)
Corrosion Science     Hybrid Journal   (Followers: 25)
CT&F Ciencia, Tecnologia y Futuro     Open Access   (Followers: 1)
CTheory     Open Access  

        1 2 3 4 5 6 7 | Last

Journal Cover Biomedical Engineering Letters
  [SJR: 0.339]   [H-I: 8]   [5 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 2093-9868 - ISSN (Online) 2093-985X
   Published by Springer-Verlag Homepage  [2354 journals]
  • Spectrum analysis for assessing red blood cell aggregation using
           high-frequency ultrasound array transducer
    • Authors: Changhan Yoon
      Pages: 273 - 279
      Abstract: The purpose of this study is to investigate a spectrum analysis technique for detecting and monitoring red blood cell (RBC) aggregation using a high-frequency array transducer. To assess the feasibility of this approach, the backscattered radio-frequency signal from non-aggregated and aggregated RBC samples with two hematocrit levels were acquired by using a 30-MHz linear array transducer and analyzed in frequency domain. Three parameters such as spectral slope, midband fit and Y intercept were extracted in a static condition. Fresh porcine blood was used and degrees of aggregation were changed by diluting plasma concentration. From the experiments, it was demonstrated that the spectral slope related to a size of scatterer progressively declined as the level of aggregation increased; its mean values at hematocrit of 40% were 1.10 and −0.22 dB/MHz for RBCs suspended in isotonic phosphate buffered saline and solution with 70% plasma concentrations, respectively. For the midband fit and Y intercept, the mean values were increased by 9.1 and 46.4 dB, respectively. These results indicated that the spectrum analysis technique is useful for monitoring RBC aggregation and can be potentially developed for assessing aggregation in clinical applications.
      PubDate: 2017-11-01
      DOI: 10.1007/s13534-017-0034-3
      Issue No: Vol. 7, No. 4 (2017)
       
  • Flickering exercise video produces mirror neuron system (MNS) activation
           and steady state visually evoked potentials (SSVEPs)
    • Authors: Hyunmi Lim; Jeonghun Ku
      Pages: 281 - 286
      Abstract: The action of observing can be used as an effective rehabilitation paradigm, because it activates the mirror neuron system. However, it is difficult to fully use this paradigm because it is difficult to get patients to engage in watching video clips of exercise. In this study, we proposed a steady state visually evoked potential (SSVEP) based paradigm that could be used in a Brain Computer Interface, and examined its feasibility by investigating whether flickering video could activate the mirror neuron system and evoke SSVEPs at the same time. Twenty subjects were recruited and asked to watch the flickering videos at a rate of 20 Hz of upper limb motion and visual white noise, while an EEG signal was recorded. The mu rhythm (8–13 Hz) suppression and the SSVEP (19–21 Hz) evocation were analyzed from recorded EEG. The results showed that SSVEPs, evoked by the flickering stimulus, was observed in both conditions on O1 and O2, but the mu rhythm suppression on C3 and C4 was observed only in the exercise video condition. These results could signify that the flickering video is applicable for the BCI rehabilitation game, activating the mirror neuron system at the same time.
      PubDate: 2017-11-01
      DOI: 10.1007/s13534-017-0035-2
      Issue No: Vol. 7, No. 4 (2017)
       
  • Real-time biofeedback device for gait rehabilitation of post-stroke
           patients
    • Authors: I-Hung Khoo; Panadda Marayong; Vennila Krishnan; Michael Balagtas; Omar Rojas; Katherine Leyba
      Pages: 287 - 298
      Abstract: In this work, we develop a device, called ‘Walk-Even’, that can provide real-time feedback to correct gait asymmetry commonly exhibited in post-stroke survivors and persons with certain neurological disorders. The device computes gait parameters, including gait time, swing time, and stance time of each leg, to detect gait asymmetry and provide corresponding real-time biofeedback by means of auditory and electrotactile stimulation to actively correct the user’s gait. The system consists of customized force-sensor-embedded insoles adjustable to fit any shoe size, electrotactile and auditory feedback circuits, microcontroller, and wireless XBee transceivers. The device also offers data saving capability. To validate its accuracy and reliability, we compared the gait measurements from our device with a commercial gait and balance assessment device, Zeno Walkway. The results show good correlation and agreement in a validity study with six healthy subjects and reliability study with seventeen healthy subjects. In addition, preliminary testing on six post-stroke patients after an 8-week training shows that the Walk-Even device helps to improve gait symmetry, foot pressure and forefoot loading of the affected side. Thus, initial testing indicates that the device is accurate in measuring the gait parameters and effective in improving gait symmetry using real-time feedback. The device is portable and low cost and has the potential for use in a non-clinical setting for patients that can walk independently without assistance. A more extensive testing with stroke patients is still ongoing.
      PubDate: 2017-11-01
      DOI: 10.1007/s13534-017-0036-1
      Issue No: Vol. 7, No. 4 (2017)
       
  • Novel tailoring algorithm for abrupt motion artifact removal in
           photoplethysmogram signals
    • Authors: Limeng Pu; Pedro J. Chacon; Hsiao-Chun Wu; Jin-Woo Choi
      Pages: 299 - 304
      Abstract: Photoplethysmogram (PPG) signals are widely used for wearable electronic devices nowadays. The PPG signal is extremely sensitive to the motion artifacts (MAs) caused by the subject’s movement. The detection and removal of such MAs remains a difficult problem. Due to the complicated MA signal waveforms, none of the existing techniques can lead to satisfactory results. In this paper, a new framework to identify and tailor the abrupt MAs in PPG is proposed, which consists of feature extraction, change-point detection, and MA removal. In order to achieve the optimal performance, a data-dependent frame-size determination mechanism is employed. Experiments for the heart-beat-rate-measurement application have been conducted to demonstrate the effectiveness of our proposed method, by a correct detection rate of MAs at 98% and the average heart-beat-rate tracking accuracy above 97%. On the other hand, this new framework maintains the original signal temporal structure unlike the spectrum-based approach, and it can be further applied for the calculation of blood oxygen level (SpO2).
      PubDate: 2017-11-01
      DOI: 10.1007/s13534-017-0037-0
      Issue No: Vol. 7, No. 4 (2017)
       
  • Sex differences of cognitive load effects on object-location binding
           memory
    • Authors: Jinsick Park; Ga In Shin; Young Min Park; In Young Kim; Dong Pyo Jang
      Pages: 305 - 309
      Abstract: In this study, we investigated where the sex differences of object-location binding memory performance were influenced by the cognitive load. We used the fractal objects version of the ‘What was where'’ task to measure object memory, location memory and objection-location binding memory. Cognitive load was controlled by task difficulty presented two sessions: one session randomly displayed three or four fractal objects (Session 34) and the other session four or five objects (Session 45). The results showed that females outperformed males on object-location binding memory. Interestingly, even when the four object trials were compared between Session 34 and Session 45, in which we believed that the level of difficulty was similar while cognitive load varied, the swap error of males was significantly increased in Session 45 compared to females. In conclusion, there may be sex differences in object-location binding memory and the males could be more sensitive about the cognitive load than females.
      PubDate: 2017-11-01
      DOI: 10.1007/s13534-017-0038-z
      Issue No: Vol. 7, No. 4 (2017)
       
  • Transscleral LED illumination pen
    • Authors: Christian Lingenfelder; Frank Koch; Philipp Koelbl; Pia Klante; Martin Hessling
      Pages: 311 - 315
      Abstract: Existing light sources for intraocular illumination are often bulky and expensive and pose a risk for the patient, because light guides are inserted in the eye through incisions and if the tip of these light guides get too close to the retina, the retina can be damaged photochemically within minutes or even seconds. Therefore a new, safe and simple device for intraocular illumination is developed and evaluated for its thermal and photochemical risks to the patient. It consists of a white LED which is integrated into a pen like holder. This device is pressed against the sclera by the physician who seeks for illumination during surgery or for diagnostic purposes. The LED light is transmitted through the sclera without the need for an incision. Considering the relevant standards, the device poses no harm to the patient, and in tests with the authors’ own eyes a sufficient intraocular illumination is reached. The proposed device is quite simple but easy to handle and very gentle for the patient.
      PubDate: 2017-11-01
      DOI: 10.1007/s13534-017-0039-y
      Issue No: Vol. 7, No. 4 (2017)
       
  • Dielectrophoretic force measurement of red blood cells exposed to
           oxidative stress using optical tweezers and a microfluidic chip
    • Authors: Hee-Jae Jeon; Hyungbeen Lee; Dae Sung Yoon; Beop-Min Kim
      Pages: 317 - 323
      Abstract: Red blood cell (RBC) dysfunction is often associated with a pathological intervention, and it has been proposed as a critical risk factor for certain lethal diseases. Examining the cell viability of RBCs under various physiological conditions is essential and of importance for precise diagnosis and drug discovery in the field of medicine and pharmacy. In this paper, we report a new analytical method that employs dielectrophoretic (DEP) force measurements in absolute units to assess the viability, and potentially the functionality of RBCs. We precisely quantify the frequency-dependent DEP forces of the RBCs by using a micro-electrode embedded chip combined with optical tweezers. DEP characteristics are known to be well-correlated with the viability of biological cells, and DEP forces are measured in both fresh and long-term stored RBCs to investigate the effect that the storage period has on the cell viability. Moreover, we investigate the DEP behavior of RBCs when exposed to oxidative stress and verify whether EDTA protects the RBCs from an oxidant. From the experiments, it is found that the fresh RBCs without oxidative stress display very high DEP forces over the entire frequency range, exhibiting two cutoff frequencies. However, both the RBCs stored for the long-term period and exposed to oxidative stress reveals that there exist no significant DEP forces over the frequency range. The results indicate that the DEP forces can serve as a useful parameter to verify whether the RBCs in certain blood are fresh and not exposed to oxidative stress. Therefore, it is believed that our system can be applied to a diagnostic system to monitor the cell viability of the RBCs or other types of cells.
      PubDate: 2017-11-01
      DOI: 10.1007/s13534-017-0041-4
      Issue No: Vol. 7, No. 4 (2017)
       
  • ECG arrhythmia classification using time frequency distribution techniques
    • Authors: Safa Sultan Qurraie; Rashid Ghorbani Afkhami
      Pages: 325 - 332
      Abstract: In this paper, we focus on classifying cardiac arrhythmias. The MIT-BIH database is used with 14 original classes of labeling which is then mapped into 5 more general classes, using the Association for the Advancement of Medical Instrumentation standard. Three types of features were selected with a focus on the time–frequency aspects of ECG signal. After using the Wigner–Ville distribution the time–frequency plane is split into 9 windows considering the frequency bandwidth and time duration of ECG segments and peaks. The summation over these windows are employed as pseudo-energy features in classification. The “subject-oriented” scheme is used in classification, meaning the train and test sets include samples from different subjects. The subject-oriented method avoids the possible overfitting issues and guaranties the authenticity of the classification. The overall sensitivity and positive predictivity of classification is 99.67 and 98.92%, respectively, which shows a significant improvement over previous studies.
      PubDate: 2017-11-01
      DOI: 10.1007/s13534-017-0043-2
      Issue No: Vol. 7, No. 4 (2017)
       
  • Design of a stimulation protocol to predict temperature distribution in
           subcutaneous tissue using the finite element model
    • Authors: Hyoun-Seok Myoung; Dong-Hyun Kim; Han-Sung Kim; Kyoung-Joung Lee
      Pages: 261 - 266
      Abstract: Moxibustion is a traditional Oriental medicine therapy that treats the symptoms of a disease with thermal stimulation. However, it is difficult to control the strength of the thermal or chemical stimulus generated by the various types and amounts of moxa and to prevent energy loss through the skin. To overcome these problems, we previously developed a method to efficiently provide RF thermal stimulation to subcutaneous tissue. In this paper, we propose a finite element model (FEM) to predict temperature distributions in subcutaneous tissue after radio-frequency thermal stimulation. To evaluate the performance of the developed FEM, temperature distributions were obtained from the FEM, and in vivo experiments were conducted using the RF stimulation system at subcutaneous tissue depths of 5 and 10 mm in the femoral region of a rabbit model. High correlation coefficients between simulated and actual temperature distributions—0.98 at 5 mm and 0.99 at 10 mm—were obtained, despite some slight errors in the temperature distribution at each depth. These results demonstrate that the FEM described here can be used to determine thermal stimulation profiles produced by RF stimulation of subcutaneous tissue.
      PubDate: 2017-08-01
      DOI: 10.1007/s13534-017-0029-0
      Issue No: Vol. 7, No. 3 (2017)
       
  • First demonstration of velocity selective recording from the pig vagus
           using a nerve cuff shows respiration afferents
    • Authors: B. W. Metcalfe; T. N. Nielsen; N. de N. Donaldson; A. J. Hunter; J. T. Taylor
      Abstract: Neural interfaces have great potential to treat disease and disability by modulating the electrical signals within the nervous system. However, whilst neural stimulation is a well-established technique, current neural interfaces are limited by poor recording ability. Low signal amplitudes necessitate the use of highly invasive techniques that divide or penetrate the nerve, and as such are unsuitable for chronic implantation. In this paper, we present the first application of the velocity selective recording technique to the detection of respiration activity in the vagus nerve, which is involved with treatments for epilepsy, depression, and rheumatoid arthritis. Further, we show this using a chronically implantable interface that does not divide the nerve. We also validate our recording setup using electrical stimulation and we present an analysis of the recorded signal amplitudes. The recording interface was formed from a cuff containing ten electrodes implanted around the intact right vagus nerve of a Danish Landrace pig. Nine differential amplifiers were connected to adjacent electrodes, and the resulting signals were processed to discriminate neural activity based on conduction velocity. Despite the average single channel signal-to-noise ratio of − 5.8 dB, it was possible to observe distinct action potentials travelling in both directions along the nerve. Further, contrary to expectation given the low signal-to-noise ratio, we have shown that it was possible to identify afferent neural activity that encoded respiration. The significance of this is the demonstration of a chronically implantable method for neural recording, a result that will transform the capabilities of future neuroprostheses.
      PubDate: 2017-11-22
      DOI: 10.1007/s13534-017-0054-z
       
  • A computational model of ureteral peristalsis and an investigation into
           ureteral reflux
    • Authors: G. Hosseini; C. Ji; D. Xu; M. A. Rezaienia; E. Avital; A. Munjiza; J. J. R. Williams; J. S. A. Green
      Abstract: The aim of this study is to create a computational model of the human ureteral system that accurately replicates the peristaltic movement of the ureter for a variety of physiological and pathological functions. The objectives of this research are met using our in-house fluid-structural dynamics code (CgLes–Y code). A realistic peristaltic motion of the ureter is modelled using a novel piecewise linear force model. The urodynamic responses are investigated under two conditions of a healthy and a depressed contraction force. A ureteral pressure during the contraction shows a very good agreement with corresponding clinical data. The results also show a dependency of the wall shear stresses on the contraction velocity and it confirms the presence of a high shear stress at the proximal part of the ureter. Additionally, it is shown that an inefficient lumen contraction can increase the possibility of a continuous reflux during the propagation of peristalsis.
      PubDate: 2017-11-18
      DOI: 10.1007/s13534-017-0053-0
       
  • Elastography for portable ultrasound
    • Authors: Bonghun Shin; Soo Jeon; Jeongwon Ryu; Hyock Ju Kwon
      Abstract: Portable wireless ultrasound has been emerging as a new ultrasound device due to its unique advantages including small size, lightweight, wireless connectivity and affordability. Modern portable ultrasound devices can offer high quality sonogram images and even multiple ultrasound modes such as color Doppler, echocardiography, and endovaginal examination. However, none of them can provide elastography function yet due to the limitations in computational performance and data transfer speed of wireless communication. Also phase-based strain estimator (PSE) that is commonly used for conventional elastography cannot be adopted for portable ultrasound, because ultrasound parameters such as data dumping interval are varied significantly in the practice of portable ultrasound. Therefore, this research aims to propose a new elastography method suitable for portable ultrasound, called the robust phase-based strain estimator (RPSE), which is not only robust to the variation of ultrasound parameters but also computationally effective. Performance and suitability of RPSE were compared with other strain estimators including time-delay, displacement-gradient and phase-based strain estimators (TSE, DSE and PSE, respectively). Three types of raw RF data sets were used for validation tests: two numerical phantom data sets modeled by an open ultrasonic simulation code (Field II) and a commercial FEA (Abaqus), and the one experimentally acquired with a portable ultrasound device from a gelatin phantom. To assess image quality of elastograms, signal-to-noise (SNRe) and contrast-to-noise (CNRe) ratios were measured on the elastograms produced by each strain estimator. The computational efficiency was also estimated and compared. Results from the numerical phantom experiment showed that RPSE could achieve highest values of SNRe and CNRe (around 5.22 and 47.62 dB) among all strain estimators tested, and almost 10 times higher computational efficiency than TSE and DSE (around 0.06 vs. 5.76 s per frame for RPSE and TSE, respectively).
      PubDate: 2017-10-27
      DOI: 10.1007/s13534-017-0052-1
       
  • Performance of machine learning methods in diagnosing Parkinson’s
           disease based on dysphonia measures
    • Authors: Salim Lahmiri; Debra Ann Dawson; Amir Shmuel
      Abstract: Parkinson’s disease (PD) is a widespread degenerative syndrome that affects the nervous system. Its early appearing symptoms include tremor, rigidity, and vocal impairment (dysphonia). Consequently, speech indicators are important in the identification of PD based on dysphonic signs. In this regard, computer-aided-diagnosis systems based on machine learning can be useful in assisting clinicians in identifying PD patients. In this work, we evaluate the performance of machine learning based techniques for PD diagnosis based on dysphonia symptoms. Several machine learning techniques were considered and trained with a set of twenty-two voice disorder measurements to classify healthy and PD patients. These machine learning methods included linear discriminant analysis (LDA), k nearest-neighbors (k-NN), naïve Bayes (NB), regression trees (RT), radial basis function neural networks (RBFNN), support vector machine (SVM), and Mahalanobis distance classifier. We evaluated the performance of these methods by means of a tenfold cross validation protocol. Experimental results show that the SVM classifier achieved higher average performance than all other classifiers in terms of overall accuracy, G-mean, and area under the curve of the receiver operating characteristic plot. The SVM classifier achieved higher performance measures than the majority of the other classifiers also in terms of sensitivity, specificity, and F-measure statistics. The LDA, k-NN and RT achieved the highest average precision. The RBFNN method yielded the highest F-measure.; however, it performed poorly in terms of other performance metrics. Finally, t tests were performed to evaluate statistical significance of the results, confirming that the SVM outperformed most of the other classifiers on the majority of performance measures. SVM is a promising method for identifying PD patients based on classification of dysphonia measurements.
      PubDate: 2017-10-12
      DOI: 10.1007/s13534-017-0051-2
       
  • Computer-assisted brain tumor type discrimination using magnetic resonance
           imaging features
    • Authors: Sajid Iqbal; M. Usman Ghani Khan; Tanzila Saba; Amjad Rehman
      Abstract: Medical imaging plays an integral role in the identification, segmentation, and classification of brain tumors. The invention of MRI has opened new horizons for brain-related research. Recently, researchers have shifted their focus towards applying digital image processing techniques to extract, analyze and categorize brain tumors from MRI. Categorization of brain tumors is defined in a hierarchical way moving from major to minor ones. A plethora of work could be seen in literature related to the classification of brain tumors in categories such as benign and malignant. However, there are only a few works reported on the multiclass classification of brain images where each part of the image containing tumor is tagged with major and minor categories. The precise classification is difficult to achieve due to ambiguities in images and overlapping characteristics of different type of tumors. In the current study, a comprehensive review of recent research on brain tumors multiclass classification using MRI is provided. These multiclass classification studies are categorized into two major groups: XX and YY and each group are further divided into three sub-groups. A set of common parameters from the reviewed works is extracted and compared to highlight the merits and demerits of individual works. Based on our analysis, we provide a set of recommendations for researchers and professionals working in the area of brain tumors classification.
      PubDate: 2017-10-04
      DOI: 10.1007/s13534-017-0050-3
       
  • PID controller design to generate pulsatile flow rate for in vitro
           experimental studies of physiological flows
    • Authors: Mohammad Reza Najjari; Michael W. Plesniak
      Abstract: Producing accurate pulsatile flow rates is essential for many in vitro experimental studies in biofluid dynamics research. A controller system was developed to control a flow loop to produce easily adjustable pulsatile flow rates with sufficient accuracy. An Arduino board is used as a micro-controller to control a pump to produce various pulsatile flow rates, and an open-source proportional-integral-derivative (PID) control algorithm is developed for this purpose. Four non-trivial pulsatile waveforms were produced by the PID controller, as well as an iterative controller, and the performance of both controllers was evaluated. Both the PID and iterative controllers were able to successfully produce slowly-varying signals (single and multi-harmonic low frequency sine waves), but for high frequency signals where the flow has strong acceleration/deceleration (e.g. for physiological waveforms) the iterative controller exhibited significant undershoot. The comparison of PID and iterative controllers suggests that if the desired flow rate is a low frequency, simple waveform then the iterative controller is preferred due to simplicity of implementation. However, if the desired signal is rapidly changing and more complicated then the PID controller achieves better results. This system can be implemented in many flow loops due to its simplicity and low cost, and does not require a mathematical model of the system.
      PubDate: 2017-09-30
      DOI: 10.1007/s13534-017-0049-9
       
  • Gastrointestinal polyp detection in endoscopic images using an improved
           feature extraction method
    • Authors: Mustain Billah; Sajjad Waheed
      Abstract: Gastrointestinal polyps are treated as the precursors of cancer development. So, possibility of cancers can be reduced at a great extent by early detection and removal of polyps. The most used diagnostic modality for gastrointestinal polyps is video endoscopy. But, as an operator dependant procedure, several human factors can lead to miss detection of polyps. In this peper, an improved computer aided polyp detection method has been proposed. Proposed improved method can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention. Color wavelet features and convolutional neural network features are extracted from endoscopic images, which are used for training a support vector machine. Then a target endoscopic image will be given to the classifier as input in order to find whether it contains any polyp or not. If polyp is found, it will be marked automatically. Experiment shows that, color wavelet features and convolutional neural network features together construct a highly representative of endoscopic polyp images. Evaluations on standard public databases show that, proposed system outperforms state-of-the-art methods, gaining accuracy of 98.34%, sensitivity of 98.67% and specificity of 98.23%. In this paper, the strength of color wavelet features and power of convolutional neural network features are combined. Fusion of these two methodology and use of support vector machine results in an improved method for gastrointestinal polyp detection. An analysis of ROC reveals that, proposed method can be used for polyp detection purposes with greater accuracy than state-of-the-art methods.
      PubDate: 2017-09-07
      DOI: 10.1007/s13534-017-0048-x
       
  • Variations in gait features in elderly adults during walking considering
           their balance
    • Authors: Hyuk-Jae Choi; Han-Sung Kim; Jeicheong Ryu; Gyoosuk Kim; Chang-Yong Ko
      Abstract: The aim of this study was to evaluate the influence of balance on the spatiotemporal features, lower-limb kinematics, and center of mass (COM) of the non-faller elderly during walking. In this study, 20 healthy elderly women (age, 76.2 ± 5.6 years; height, 150.1 ± 3.2 cm; weight, 55.8 ± 9.0 kg) were enrolled. Based on the Berg balance scale (BBS), the elderly were classified into two groups: poor balance (PB; BBS scores <46; n = 10; 43.8 ± 1.8) and good balance (GB; BBS scores ≥46; n = 10; 50.4 ± 2.5). The two groups had no differences in terms of the spatiotemporal features and range of motion (ROM) of the vertical COM (all p > 0.05). The ROM of the mediolateral COM was greater in PB than in GB. Hip transversal movements in the two groups were different. The impairment of the lateral balance function might contribute to an increase in the incidence of fall events in the elderly with poor balance.
      PubDate: 2017-09-04
      DOI: 10.1007/s13534-017-0045-0
       
  • Deep-learning-based automatic computer-aided diagnosis system for diabetic
           retinopathy
    • Authors: Romany F. Mansour
      Abstract: The high-pace rise in advanced computing and imaging systems has given rise to a new research dimension called computer-aided diagnosis (CAD) system for various biomedical purposes. CAD-based diabetic retinopathy (DR) can be of paramount significance to enable early disease detection and diagnosis decision. Considering the robustness of deep neural networks (DNNs) to solve highly intricate classification problems, in this paper, AlexNet DNN, which functions on the basis of convolutional neural network (CNN), has been applied to enable an optimal DR CAD solution. The DR model applies a multilevel optimization measure that incorporates pre-processing, adaptive-learning-based Gaussian mixture model (GMM)-based concept region segmentation, connected component-analysis-based region of interest (ROI) localization, AlexNet DNN-based highly dimensional feature extraction, principle component analysis (PCA)- and linear discriminant analysis (LDA)-based feature selection, and support-vector-machine-based classification to ensure optimal five-class DR classification. The simulation results with standard KAGGLE fundus datasets reveal that the proposed AlexNet DNN-based DR exhibits a better performance with LDA feature selection, where it exhibits a DR classification accuracy of 97.93% with FC7 features, whereas with PCA, it shows 95.26% accuracy. Comparative analysis with spatial invariant feature transform (SIFT) technique (accuracy—94.40%) based DR feature extraction also confirms that AlexNet DNN-based DR outperforms SIFT-based DR.
      PubDate: 2017-08-31
      DOI: 10.1007/s13534-017-0047-y
       
  • Automatic heart activity diagnosis based on Gram polynomials and
           probabilistic neural networks
    • Authors: Francesco Beritelli; Giacomo Capizzi; Grazia Lo Sciuto; Christian Napoli; Francesco Scaglione
      Abstract: The paper proposes a new approach to heart activity diagnosis based on Gram polynomials and probabilistic neural networks (PNN). Heart disease recognition is based on the analysis of phonocardiogram (PCG) digital sequences. The PNN provides a powerful tool for proper classification of the input data set. The novelty of the proposed approach lies in a powerful feature extraction based on Gram polynomials and the Fourier transform. The proposed system presents good performance obtaining overall sensitivity of 93%, specificity of 91% and accuracy of 94%, using a public database of over 3000 heart beat sound recordings, classified as normal and abnormal heart sounds. Thus, it can be concluded that Gram polynomials and PNN prove to be a very efficient technique using the PCG signal for characterizing heart diseases.
      PubDate: 2017-08-22
      DOI: 10.1007/s13534-017-0046-z
       
  • Unified principles of thalamo-cortical processing: the neural switch
    • Authors: Urs Ribary; S. M. Doesburg; L. M. Ward
      Abstract: It has been reported that cross-frequency interactions may play an important role in local processing within thalamus and neocortex, as well as information transfer between subcortical and cortico-cortical brain regions. Strong commonalities in rhythmic network properties have been observed across recording techniques and task demands, but strong neuroscientific theories to situate such observations within a unified framework with direct relevance to explain neuropathologies remain scarce. Based on a comprehensive review of animal and human literature, we probe and introduce a neurophysiological framework to explain how coordinated cross-frequency and interregional oscillatory cortical dynamics underlie typical and atypical brain activation, and the formation of distributed functional ensembles supporting cortical networks underpinning perception and cognition. We propose that local regional activation by an external stimulus via a sensory pathway entails (1) attenuated alpha (8–14 Hz) and increased theta (4–8 Hz) and gamma (30–50 Hz) oscillatory activity, and (2) increased interactions among theta and gamma rhythms. These local dynamics also mediate the integration of activated neural populations into large-scale functional assemblies through neuronal synchronization. This comprehensive perspective into the animal and human literature indicates a further thinking beyond synchrony and connectivity and the readiness for more hypothesis-driven research and modeling toward unified principles of thalamo-cortical processing. We further introduced such a possible framework: “The ATG switch”. We also discussed evidence that alpha–theta–gamma dynamics emerging from thalamocortical interactions may be implicated and disrupted in numerous neurological and neuropsychiatric conditions.
      PubDate: 2017-05-02
      DOI: 10.1007/s13534-017-0033-4
       
 
 
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