Journal of Healthcare Engineering / 2020 / Article / Tab 4 / Research Article
Design of a Machine Learning-Assisted Wearable Accelerometer-Based Automated System for Studying the Effect of Dopaminergic Medicine on Gait Characteristics of Parkinson’s Patients Table 4 5 split cross-validation.
Performance (%) KNN SVM NB Decision tree Accuracy test set 1 82.11 81.36 84.52 86.28 Sensitivity test set 1 0.8746 0.7801 0.8225 0.9152 Specificity test set 1 0.8452 0.725 0.8654 0.8833 Accuracy test set 2 83.64 84.25 81.20 84.31 Sensitivity test set 2 0.8055 0.8139 0.8558 0.8631 Specificity test set 2 0.8519 0.8687 0.8411 0.8551 Accuracy test set 3 86.32 84.93 85.31 82.28 Sensitivity test set 3 0.9025 0.8755 0.9032 0.8111 Specificity test set 3 0.8947 0.9054 0.8748 0.8364 Accuracy test set 4 85.57 87.23 84.41 88.46 Sensitivity test set 4 0.9125 0.9189 0.8956 0.9286 Specificity test set 4 0.8836 0.8997 0.8735 0.9091 Accuracy test set 5 87.26 84.39 79.32 87.32 Sensitivity test set 5 0.8568 0.8793 0.8178 0.9025 Specificity test set 5 0.9034 0.8998 0.8227 0.9131