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In order to accurately distinguish healthy people from Parkinson\u2019s disease patients, a cost-sensitive support vector machine (CS-SVM) method is designed in this paper, which is used to construct the model for classification of gait signals between Kinson\u2019s disease patients and healthy individuals. Gait data for the entire subject was extracted from a real U-shaped electronic walkway. The extracted features are converted to a dimensionless form, the classification performance can be improved. 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