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Table 4 Fall-risk assessment model type, validation method, accuracy, specificity, and sensitivity

From: Review of fall risk assessment in geriatric populations using inertial sensors

Author Model Model validation Accuracy (%) Specificity (%) Sensitivity (%)
Caby et al., 2011* [41] Radial basis function neural network, support vector, k-nearest neighbour, and naive Bayesian classifiers Leave-one-out cross-validation 75-100 40-100 93-100
Giansanti et al., 2008*† [48] Multi-layer perceptron neural network 47:53 split (Train:Test) 97 97 98
Giansanti et al., 2006*† [46] Mahalanobis cluster analysis 47:53 split (Train:Test) 93.5-94.5 93-94 93.9-94.9
Giansanti et al., 2008*† [47] Multi-layer perceptron neural network 47:53 split (Train:Test) 88-91 88-92 88-91
Gietzelt et al., 2009* [49] Decision tree Not specified 90.5 91.0 89.4
Ganea et al., 2011* [45] Logistic regression, ROC curve Not specified - 35-88 55-92
Weiss et al., 2011† [74] Logistic regression Not specified 63.4-87.8 50.0-83.3 65.2-91.3
Liu et al., 2011* [57] Linear regression, linear discriminant classifier Leave-one-out cross-validation 71 98.3 88.9
Marschollek et al., 2011‡ [61] Logistic regression, decision tree Stratified ten-times ten-fold cross validation 78-80 82-96 58-74
Marschollek et al., 2008* [59] Logistic regression, classifier Stratified ten-times ten-fold cross validation 65.5-89.1 15.4-60.4 78.5-99.0
Marschollek et al., 2009† [60] Decision tree Not possible due to limited sample size 90 100 57.7
Schwesig et al., 2012‡ [71] Binary logistic regression, ROC curve Not specified - 42-61 63-100
Moe-Nilssen et al., 2005† [65] Linear regression, ROC curve Not specified 80 85 75
Bautmans et al., 2011† [40] Logistic regression, ROC curve Not specified 77 78 78
Greene et al., 2010† [50] Logistic regression 80:20 split (Train:Test) 76.8 75.9 77.3
Doi et al., 2013‡ [44] Logistic regression, ROC curve Not specified - 84.2 68.8
Marschollek et al., 2011‡ [62] Logistic regression, classifier Stratified ten-times ten-fold cross validation 70 78 58
Greene et al., 2012† [51] Support vector machine Ten-fold cross validation 71.5 68.4 65.4
Kojima et al., 2008† [53] Regression, canonical discriminant classifier Not specified 62.1 68.2 61.1
Senden et al., 2012* [72] Linear regression, ROC curve Not specified AUC: 0.67-0.85 - -
  1. AUC, Area under curve, ROC, receiver operating characteristic, Criterion classification method: *Clinical assessment, †Retrospective fall history, ‡Prospective fall history.