Bannari Amman Institute of Technology, Sathyamanglam
Abstract
Personal mobility is primarily affected by neurodegenerative diseases. Characteristics of the disease are stiffness of the muscle and abnormal gait movement. Impairment of motor activity is a common characteristic indicative of patients with neurodegenerative (ND) disease, which can disrupt the pathway from the cerebrum to the muscle and thereby cause movement disorders.In order to differentiate normal gait from normal gait, we proposed a machine learning based approach. Where we analysed various classification algorithms and achieved an overall accuracy of 86.35% with 10 features. Conventional methods including high tech lab setup cameras sensors can be avoided since the proposed system is effective and wearable. Using manually labeled features, for algorithms such as K-nearest neighbour, Support Vector Machines, and Decision Trees, multiple feature sets are used to classify, and the performance of these algorithms is then recorded. This research introduces a real-time method for the mentioned disorders with an accuracy of more than 85%.
M, M., R, M. P., J, M. A. J., & S, M. (2021). Machine Learning Based Approach to Identify Neuro-Degenarative Disease using Gait Analysis. Int. J. of Aquatic Science, 12(3), 1705-1711.
MLA
Mr.Kalimuthu M; Mrs.Gayathri priyadarshini R; Mr.Nikhil Amala Jerrin J; Mr.Kishore S. "Machine Learning Based Approach to Identify Neuro-Degenarative Disease using Gait Analysis". Int. J. of Aquatic Science, 12, 3, 2021, 1705-1711.
HARVARD
M, M., R, M. P., J, M. A. J., S, M. (2021). 'Machine Learning Based Approach to Identify Neuro-Degenarative Disease using Gait Analysis', Int. J. of Aquatic Science, 12(3), pp. 1705-1711.
VANCOUVER
M, M., R, M. P., J, M. A. J., S, M. Machine Learning Based Approach to Identify Neuro-Degenarative Disease using Gait Analysis. Int. J. of Aquatic Science, 2021; 12(3): 1705-1711.
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