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JCR Impact Factor: 0.459
JCR 5-Year IF: 0.442
Issues per year: 4
Current issue: Feb 2017
Next issue: May 2017
Avg review time: 75 days


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
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2017-Apr-04
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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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2016-Dec-17
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2016-Jun-14
Thomson Reuters published the Journal Citations Report for 2015. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.459, and the JCR 5-Year Impact Factor is 0.442.

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  1/2014 - 20

Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy Classifier

GEMAN, O. See more information about GEMAN, O. on SCOPUS See more information about GEMAN, O. on IEEExplore See more information about GEMAN, O. on Web of Science, COSTIN, H. See more information about COSTIN, H. on SCOPUS See more information about COSTIN, H. on SCOPUS See more information about COSTIN, H. on Web of Science
 
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Download PDF pdficon (741 KB) | Citation | Downloads: 413 | Views: 1,972

Author keywords
adaptive neuro-fuzzy classifier, artificial neural networks, handwriting analysis, nonlinear dynamics, tremor

References keywords
parkinson(11), disease(10), system(6), tremor(5), geman(5), analysis(5), processing(4), link(4), data(4), costin(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-02-28
Volume 14, Issue 1, Year 2014, On page(s): 133 - 138
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.01020
Web of Science Accession Number: 000332062300020
SCOPUS ID: 84894623357

Abstract
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Neurological diseases like Alzheimer, epilepsy, Parkinson's disease, multiple sclerosis and other dementias influence the lives of patients, their families and society. Parkinson's disease (PD) is a neurodegenerative disease that occurs due to loss of dopamine, a neurotransmitter and slow destruction of neurons. Brain area affected by progressive destruction of neurons is responsible for controlling movements, and patients with PD reveal rigid and uncontrollable gestures, postural instability, small handwriting and tremor. Commercial activity-promoting gaming systems such as the Nintendo Wii and Xbox Kinect can be used as tools for tremor, gait or other biomedical signals acquisitions. They also can aid for rehabilitation in clinical settings. This paper emphasizes the use of intelligent optical sensors or accelerometers in biomedical signal acquisition, and of the specific nonlinear dynamics parameters or fuzzy logic in Parkinson's disease tremor analysis. Nowadays, there is no screening test for early detection of PD. So, we investigated a method to predict PD, based on the image processing of the handwriting belonging to a candidate of PD. For classification and discrimination between healthy people and PD people we used Artificial Neural Networks (Radial Basis Function - RBF and Multilayer Perceptron - MLP) and an Adaptive Neuro-Fuzzy Classifier (ANFC). In general, the results may be expressed as a prognostic (risk degree to contact PD).


References | Cited By

Cited-By ISI Web of Science

Web of Science® Times Cited: 9 [View]
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Cited-By CrossRef

SCOPUS® Times Cited: 11
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Cited-By CrossRef

[1] Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease, Drotár, Peter, Mekyska, Jiří, Rektorová, Irena, Masarová, Lucia, Smékal, Zdenek, Faundez-Zanuy, Marcos, Computer Methods and Programs in Biomedicine, ISSN 0169-2607, Issue 3, Volume 117, 2014.
Digital Object Identifier: 10.1016/j.cmpb.2014.08.007
[CrossRef]

[2] Deep brain stimulation efficiency and Parkinson's disease stage prediction using Markov models, Geman, Oana, Chiuchisan, Iuliana, 2015 E-Health and Bioengineering Conference (EHB), ISBN 978-1-4673-7544-3, 2015.
Digital Object Identifier: 10.1109/EHB.2015.7391433
[CrossRef]

[3] Joint EEG — EMG signal processing for identification of the mental tasks in patients with neurological diseases, Geman, Oana, Chiuchisan, Iuliana, Covasa, Mihai, Eftaxias, Konstantinos, Sanei, Saeid, Madeira, Jonni Guiller Ferreira, Boloy, Ronney Arismel Mancebo, 2016 24th European Signal Processing Conference (EUSIPCO), ISBN 978-0-9928-6265-7, 2016.
Digital Object Identifier: 10.1109/EUSIPCO.2016.7760518
[CrossRef]

[4] NeuroParkinScreen — A health care system for Neurological Disorders Screening and Rehabilitation, Chiuchisan, Iuliana, Geman, Oana, Chiuchisan, Iulian, Iuresi, Andrei Coriolan, Graur, Adrian, 2014 International Conference and Exposition on Electrical and Power Engineering (EPE), ISBN 978-1-4799-5849-8, 2014.
Digital Object Identifier: 10.1109/ICEPE.2014.6969966
[CrossRef]

[5] Challenges and trends in Ambient Assisted Living and intelligent tools for disabled and elderly people, Geman, Oana, Sanei, Saeid, Costin, Hariton-Nicolae, Eftaxias, Konstantinos, Vysata, Oldrich, Prochazka, Ales, Lhotska, Lenka, 2015 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM), ISBN 978-1-4673-8457-5, 2015.
Digital Object Identifier: 10.1109/IWCIM.2015.7347088
[CrossRef]

[6] Towards an inclusive Parkinson's screening system, Geman, Oana, Sanei, Saeid, Chiuchisan, Iuliana, Graur, Adrian, Prochazka, Ales, Vysata, Oldrich, 2014 18th International Conference on System Theory, Control and Computing (ICSTCC), ISBN 978-1-4799-4601-3, 2014.
Digital Object Identifier: 10.1109/ICSTCC.2014.6982461
[CrossRef]

[7] A comparison between healthy and neurological disorders patients using nonlinear dynamic tools, Aldea, Roxana Toderean, Geman, Oana, Chiuchisan, Iuliana, Lazar, Anca Mihaela, 2016 International Conference and Exposition on Electrical and Power Engineering (EPE), ISBN 978-1-5090-6129-7, 2016.
Digital Object Identifier: 10.1109/ICEPE.2016.7781351
[CrossRef]

[8] Tremor analysis in neurological disorders using intelligent clothes, Hagan, Marius, Constantinescu, Aurora, Geman, Oana, 2015 E-Health and Bioengineering Conference (EHB), ISBN 978-1-4673-7544-3, 2015.
Digital Object Identifier: 10.1109/EHB.2015.7391406
[CrossRef]

[9] Real-time health status monitoring system based on a fuzzy agent model, Ivascu, Todor, Aritoni, Ovidiu, 2015 E-Health and Bioengineering Conference (EHB), ISBN 978-1-4673-7544-3, 2015.
Digital Object Identifier: 10.1109/EHB.2015.7391502
[CrossRef]

[10] Automatic analysis of the fetal heart rate variability and uterine contractions, Rotariu, Cristian, Pasarica, Alexandru, Andruseac, Gladiola, Costin, Hariton, Nemescu, Dragos, 2014 International Conference and Exposition on Electrical and Power Engineering (EPE), ISBN 978-1-4799-5849-8, 2014.
Digital Object Identifier: 10.1109/ICEPE.2014.6969970
[CrossRef]

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Copyright ©2001-2017
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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