Disease recognition and classification from movement patterns

In this paper, a motion capture system consisting of tags attached to the body is used to capture the movement pattern of the people. A classifier is trained so that it is used to classify the user's movement into various categories namely Normal, Parkinson disease, Hemiplegia, Leg pain and Back pain. The five different techniques are applied for the classification 1.) Decision tree classifier, 2.) K-Nearest Neighbor, 3.) Neural Networks Algorithm, 4.) Naïve Bayes classifier and 5.) Support Vector Machine.