Detection of Movement Disorders Using Multi SVM

A. Athisakthi; Dr.M.Pushparani

Detection of Movement Disorders Using Multi SVM

A. Athisakthi * §

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Dr.M.Pushparani ‡

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§ Mother Teresa Womens University

‡ Mother Teresa Women's University

Detection of Movement Disorders Using Multi SVM

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Abstract

Gait analysis is very significant for early diagnosis of gait diseases and treatment assessment. Gait analysis is used to assess, plan and to treat the individuals with conditions affecting their ability to walk. In recent years, doctors gain more clarity and exact disease assessment by means of machine learning technologies and this has gained much application of gait analysis. The patients suffering from movement disorders such as Parkinson’s disease (PD), Huntington’s disease (HD), and Amyotrophic Lateral Sclerosis (ALS) can best be diagnosed by gait analysis. For these reasons, analysis of the above said diseases are taken into consideration. In this paper we propose an effective method for detection of movement disorders using multi SVM technique.

References

15 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

A. Athisakthi, Dr.M.Pushparani. . "Detection of Movement Disorders Using Multi SVM". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 13 (GJCST Volume 13 Issue G1).

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GJCST Volume 13 Issue G1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

amyotrophic lateral sclerosis huntington’s disease parkinson’s disease

Classification

GJCST-G Classification G.1.2

Submission ReceivedDecember 10, 2012
Peer Review Double Blind
Handling Editor
Accepted January 4, 2013
Published January 15, 2013

Version of record

v1.2

Language

English

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Article Matrices

Total Score: 107

Country: India

Subject: Global Journal of Computer Science and Technology - G: Interdisciplinary

Authors: A. Athisakthi, Dr.M.Pushparani (PhD/Dr. count: 1)

View Count (all-time): 474

Total Views (Real + Logic): 9398

Total Downloads (simulated): 767

Publish Date: 2013 01, Tue

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Total Views: 9.4K

Total Downloads: 767

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