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Significant biomarkers from spatiotemporal gait features are obtained based on the correlation, and the normal distribution of the gait dataset is assessed using the Shapiro-Wilk test. Subsequently, four supervised machine learning algorithms, namely, K-nearest neighbours (KNN), Naive Bayes (N, Ensemble classifier (EC) and Support vector machine (SVM) are used to rate the severity level of PD according to the Hoehn and Yahr (HY) scale. The performance of the classifiers, assessed using the confusion matrix and parallel coordinate
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