Gait Abnormality Classification in Clinical Field 
S. Sophia1, K.Sowmiya2, P. Vinesha3, S. Rajarajeshwari4, A. Athithya Janani5
1Dr.S.Sophia*, Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India.
2Sowmiya.K, Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India.
3Vinesha.P, Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India.
4Rajarajeshwari.S, Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India .
5Athithya Janani.A, Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India .
Manuscript received on April 05, 2020. | Revised Manuscript received on April 25, 2020. | Manuscript published on April 30, 2020. | PP: 128-131 | Volume-9 Issue-4, April 2020. | Retrieval Number: C6388029320/2020©BEIESP | DOI: 10.35940/ijeat.C6388.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents a novel technique of classifying the abnormalities in gait. Determining or analyzing the different movements in the limbs of human beings, gait assessment can be made. Gait prediction plays a dynamic role in the clinical field to improve the outcome of the treatment. By predicting the type of abnormalities of gait, the patients can be provided with the proper treatment and thus improving the quality of life. In the proposed method, convolutional neural network and support vector machine algorithm have been used in classifying the various abnormalities of gait such as freezing of gait, brady kinesia, Tremor, Ataxic gait, myopathic gait and muscle atrophy. This method provides greater accuracy and thus helpful in diagnosis of various abnormalities of gait.
Keywords: Gait prediction, convolution neural network, Support vector machine, freezing of gait, Brady kinesia, Tremor, Ataxic gait, myopathic gait, muscle atrophy.