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Reseach Article

Classification of EMG based Diseases using Fuzzy Logic at Second Level

by Heena, Babita Pandey
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 3
Year of Publication: 2014
Authors: Heena, Babita Pandey
10.5120/15862-4788

Heena, Babita Pandey . Classification of EMG based Diseases using Fuzzy Logic at Second Level. International Journal of Computer Applications. 91, 3 ( April 2014), 25-33. DOI=10.5120/15862-4788

@article{ 10.5120/15862-4788,
author = { Heena, Babita Pandey },
title = { Classification of EMG based Diseases using Fuzzy Logic at Second Level },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 3 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 25-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number3/15862-4788/ },
doi = { 10.5120/15862-4788 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:13:04.422931+05:30
%A Heena
%A Babita Pandey
%T Classification of EMG based Diseases using Fuzzy Logic at Second Level
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 3
%P 25-33
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Intelligent diagnosis systems plays very important role in the medical field and particularly in diagnosis and classification of neuromuscular diseases (NMD). In such a field where uncertainty is always present, classical techniques of classification show a lack of efficiency thus leading to erroneous results. Fuzzy logic proved to be a suitable method for classification problems, particularly in NMDs. This paper aims to present a fuzzy logic based system for the classification of seven types of neuromuscular diseases at first level and classification of eight types of muscular dystrophy diseases at second level. The obtained results have shown good performance of the designed classifier.

References
  1. R. B. Mishra, R. S. Rao, A heuristic pattern detection algorithm for assessment of EMG signals, Indian Journal of the Institution of Engineers 76 (1997) 52–58.
  2. B. Pandey, R. B. Mishra, Case-based reasoning and data mining integrated method for the diagnosis of some neuromuscular disease, Int. J. Medical Engineering and Informatics 3(1) (2011) 1–15.
  3. B. Pandey, R. B. Mishra, An integrated intelligent computing model for the interpretation of EMG based neuromuscular diseases, Expert System with Application 36 (5) (2009) 9201-9213.
  4. A. MESSAOUD, M. B. MESSAOUD, A. KACHOURI and F. SELLAMI, Fuzzy logic based system for classification of atrial fibrillation cardiac arrhythmias, IEEE, 2006, pp. 347-350
  5. A. Subasi, Medical decision support system for diagnosis of neuromuscular disorders using DWT and fuzzy support vector machines, Computers in Biology and Medicine archive Volume 42 Issue 8, August, 2012,Pages 806-815.
  6. A. P. Picon, R. S. Ortega, R. Watari, C. Sartor, I. C. N. Sacco, Classifiction of diabetic neuropathy: a new approach taking uncertainity into account using fuzzy logic, Clinics, 2012, 67(2):151-156.
  7. B. Pandey, R. B. Mishra, Data Mining Approaches for the EMG absed classification of neuromuscular diseases, National conference on Artificial Intelligence and Agents(2011),136-148.
  8. B. Pandey, R. B. Mishra,Performance index assessment of intelligent computing methods in EMG-based neuromuscular diseases. IJKESDP, 4(1):42-71(2013).
  9. B. Pandey, R. B. Mishra , An Intelligent Method Model For two level diagnoses of Neuromuscular Diseases,IJKESDP, (2014),(accepted)
Index Terms

Computer Science
Information Sciences

Keywords

Intelligent diagnosis system neuromuscular diseases fuzzy logic classification.