NDLI: Classification of ALS disease using support vector machines

Content Provider	IEEE Xplore Digital Library
Author	Kucuk, H. Eminoglu, I.
Copyright Year	2015
Description	Author affiliation: Biyomedikal Arastirma Lisansustu Laboratuari: (BAL-Lab.), Ondokuz Mayis Univ., Samsun, Turkey (Kucuk, H.; Eminoglu, I.)
Abstract	In this study, SVM (Support Vector Machine) algorithm is used for the diagnosis of ALS which is the most common type of motor neuron disease. Before classification of EMG data with SVM (Support Vector Machine); pre-processing, segmentation, feature extraction and clustering stages of data are completed. In the stage of clustering, hybrid and hierarchical clustering methods are employed. After that, feature vectors in time and frequency domains and their different combinations (a total of 11 feature vectors) are fed to the SVM and the obtained results are observed. It is understood that the advantages of clustering methods dependent on the feature vectors; multiple feature vectors provide high performance in the diagnosis of ALS disease and exhibit much lower discrepancy.
Starting Page	1664
Ending Page	1667
File Size	326657
Page Count	4
File Format	PDF
ISBN	9781467373869
DOI	10.1109/SIU.2015.7130171
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-16
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Clustering methods ALS hierarchical clustering Electromyography SVM Mathematical model MATLAB Bioinformatics EMG Diseases
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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