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JCR Impact Factor: 1.221
JCR 5-Year IF: 0.961
SCOPUS CiteScore: 2.5
Issues per year: 4
Current issue: Aug 2021
Next issue: Nov 2021
Avg review time: 89 days


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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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2021-Jun-30
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2021-Jun-06
SCOPUS published the CiteScore for 2020, computed by using an improved methodology, counting the citations received in 2017-2020 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2020 is 2.5, better than all our previous results.

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2020-Jun-29
Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

2020-Jun-11
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  1/2013 - 7

 HIGH-IMPACT PAPER 

Parkinson's disease Assessment using Fuzzy Expert System and Nonlinear Dynamics

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, TURCU, C. O. See more information about  TURCU, C. O. on SCOPUS See more information about  TURCU, C. O. on SCOPUS See more information about TURCU, C. O. on Web of Science, GRAUR, A. See more information about GRAUR, A. on SCOPUS See more information about GRAUR, A. on SCOPUS See more information about GRAUR, A. on Web of Science
 
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Download PDF pdficon (719 KB) | Citation | Downloads: 876 | Views: 4,177

Author keywords
Parkinson's disease, assessment, tremor symptom, fuzzy, expert systems, nonlinear dynamics

References keywords
fuzzy(12), tremor(10), inson(9), disease(8), analysis(7), system(5), geman(5), systems(4), signal(4), expert(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-02-28
Volume 13, Issue 1, Year 2013, On page(s): 41 - 46
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.01007
Web of Science Accession Number: 000315768300007
SCOPUS ID: 84875335626

Abstract
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Full text preview
This paper proposes a new screening system for quantitative evaluation and analysis, designed for the early stage detection of Parkinson disease. This has been carried out in the view of improving the diagnosis currently established upon a basis of subjective scores. Parkinsons disease (PD) appears as a result of dopamine loss, a chemical mediator that is responsible for the bodys ability to control movements. The symptoms reflect the loss of nerve cells, due to an unknown. The input parameters of the system are represented by amplitude, frequency, the spectral characteristic and trembling localization. The main symptoms include trembling of hand, arms, movement difficulties, postural instability, disturbance of coordination and equilibrium, sleep disturbance, difficulties in speaking, reducing of voice volume. The medical knowledge in PD field is characterized by imprecision, uncertainty and vagueness. The proposed system (fuzzy expert systems) is non-invasive and, easy to use by both physicians and patients at home.


References | Cited By  «-- Click to see who has cited this paper

[1] Dorsey E.R., Constantinescu R., Thompson J.P., et al., "Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030", Neurology, Vol. 68, pp. 384-386, 2007
[CrossRef] [PubMed] [Web of Science Times Cited 1364] [SCOPUS Times Cited 1461]


[2] Less A.J., Hardy A., Revesz T., "Parkinson's disease", Lancet, pp. 2055-2066, 2009.
[CrossRef] [Web of Science Times Cited 1372] [SCOPUS Times Cited 1464]


[3] National Institute of Neurological Disorders and Stroke, Parkinson's Disease, [Online] Available: Temporary on-line reference link removed - see the PDF document (2012)

[4] Movement Disorder Society Task Force on Rating Scales for Parkinson's Disease, "The Unified Parkinson's Disease Rating Scale (UPSRS): Status and Recommendations", Movement Disorders, Vol. 18, No. 7, pp. 738-750, 2003.
[CrossRef] [PubMed] [Web of Science Times Cited 975] [SCOPUS Times Cited 1064]


[5] Lemoyne R, "Implementation of an iPhone for characterizing Parkinson's disease tremor through a wireless accelerometer application", 32 Annual Conference of the IEEE EMBS, pp. 4954-4958, 2010.
[CrossRef] [Web of Science Times Cited 59] [SCOPUS Times Cited 98]


[6] Coroian C., Lemoyne R., "The merits of artificial proprioception, with applications in biofeedback gait rehabilitation concepts and movement disorder characterization", Biomedical Engineering, ISBN 978-953-307-013-1, pp.165-198, 2009.

[7] Costin H., Rotariu C., "Automatic evaluation of neuro-motor disorder using image analysis of handwriting", Medical-Surgical Journal, Vol. 105, No.2, pp. 386-390, Iasi, Romania, 2001.

[8] Costin H., Rotariu C., "Tremor assessment by means of handscript analysis and fuzzy logic", Biomedical Softcomputing & Human Sciences Journal, Vol. 7, No.1, pp. 39-45, Japan, 2001.

[9] Neshat M., Yaglobi, M. "Designing a Fuzzy Expert System of Diagnosing the Hepatitis B Intensity Rate and Comparing it with Adaptive Neural Network Fuzzy System", Proceedings of the World Congress on Engineering and Computer Science, San Francisco, USA, Vol. II:346-352, ISBN:978-988-18210-2-7, 2009.

[10] Saritas I., Allahverdi N., Unal Sert I., "A Fuzzy Expert System Design for Diagnosis of Prostate Cancer", International Conference on Computer Systems and Technologies - COMPSYSTECH'2003, pp. 1202-1219, 2003.

[11] Lingmei, J. Wang, Ruoxia Y., "Classification of Parkinson and essential tremor using empirical mode decomposition and support vector machine", Digital Signal Process., pp. 245-263, 2011.

[12] Plamena A., Ognyan M., "Fuzzy Multi-Criteria Decision Making Method for Diagnostic Selection", ECAI 2005 - International Conference, Electronics, Computers and Artificial Intelligence, Romania, pp. 398-403, 2005.

[13] Geman O., Zamfir C., "Using Wavelet for Early Detection of Pathological Tremor", EUSIPCO 2012 - 20th European Signal Processing Conference, pp. 1723-1727, ISSN 2076-1465, 2012.

[14] Costin H., Rotariu C., "Medical image analysis and representation using a fuzzy and rule-based hybrid approach", Int. Journal of Computers, Communications & Control, pp. 156-162, 2006.

[15] Geman O., "A Fuzzy Expert Systems Design for Diagnosis of Parkinson's Disease", EHB'2011 E-Health and Bioengineering Conference, pp. 122-126, ISBN: 978-1-4577-0292-1, 2011.

[16] Geman O., "Data Processing for Parkinson's Disease Tremor, Speech and Gait Signal Analysis", EHB'2011 E-Health and Bioengineering Conference, pp. 53-57, ISBN: 978-1-4577-0292-1, 2011.

[17] Dobrea D.M., Teodorescu H.N., "A new type of non-contact 2D multimodal interface to track and acquire hand position and tremor signal", 8th Biennial Baltic Electronics Conference, Tallin, pp. 359-362, 2002.

[18] Marimorita M., Iizuka T., Takeuchi A., Shirataka M., Ikeda N., "Development of a System for Measurement and Analysis of Tremor Using a Three-axis Accelerometer", Methods Inf. Med., Vol. 6, pp. 589-594, 2009.
[CrossRef] [PubMed] [Web of Science Times Cited 29] [SCOPUS Times Cited 34]


[19] Teodorescu H.N., Chelaru M., Kandel A., Tofan I., Irimia M., "Fuzzy methods in tremor assessment, prediction, and rehabilitation". Artificial Intelligence in Medicine, Vol. 21(1-3), pp. 107—130, 2001.
[CrossRef] [Web of Science Times Cited 21] [SCOPUS Times Cited 25]


[20] Geman (Voroneanu) O., Teodorescu H.N., Zamfir C., "Nonlinear Analysis and Selection of Relevant Parameters in Assessing the Treatment Results of reducing Tremor, using DBS procedure", International Joint Conference on Neural Networks IJCNN'2004, Budapest, Hungary, pp. 1207-1216, 2004.

[21] Teodorescu H.N., Geman (Voroneanu) O., "Selection of Relevant Nonlinear Parameters in Assessing the DBS Treatment Results of the Tremor," European Conference on Intelligent Systems and Technologies ECIT'2004, pp. 62-70, 2004.

[22] Chaos Data Analyzer (CDA), [Online] Available: Temporary on-line reference link removed - see the PDF document (2012)

[23] Nonlinear Analysis in Real Time (Nlyzer), [Online] Available: Temporary on-line reference link removed - see the PDF document (2012)

[24] Precup R.E., Hellendoom H., "A survey on industrial applications of fuzzy control", Computers and Industry, Vol. 62, No. 3, pp. 213-225, 2011.
[CrossRef] [Web of Science Times Cited 325] [SCOPUS Times Cited 378]


[25] Schipor O., Pentiuc G., Schipor D., "Toward Automatic Recognition of Children's Affective State Using Physiological Parameters and Fuzzy Model of Emotions", Advances in Electrical and Computer Engineering, Volume 12, No. 2, pp. 47 - 50, ISSN: 1582-7445, e-ISSN: 1844-7600,
[CrossRef] [Full Text] [Web of Science Times Cited 7] [SCOPUS Times Cited 4]


[26] D'Urso P., Massari R., "Fuzzy clustering of human activity", Fuzzy Sets and Systems, Vol 215, No.16, pp. 29-54, 2013.
[CrossRef] [Web of Science Times Cited 42] [SCOPUS Times Cited 47]


[27] Zaharia M.H., Leon F., "Speech Therapy Based on Expert System", Advances in Electrical and Computer Engineering, Vol. 9, No. 1, pp. 74-77, ISSN: 1582-7445, e-ISSN: 1844-7600, 2009.
[CrossRef] [Full Text] [Web of Science Times Cited 7] [SCOPUS Times Cited 6]




References Weight

Web of Science® Citations for all references: 4,201 TCR
SCOPUS® Citations for all references: 4,581 TCR

Web of Science® Average Citations per reference: 150 ACR
SCOPUS® Average Citations per reference: 164 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-09-15 01:50 in 75 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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