## 4 Discussion  
The aim of this study was to set a prevention and screening protocol predictive of fall risk and frailty condition in the elderly. Despite the preventable nature of fall events, falls are experienced by a growing number of older adults. Having a history of fall generates fear of a second fall, even if the first experience did not lead to fatal or serious injuries. Interventions directed to the improvement of physical aspects such as gait and balance can reduce the falling risk; however, a preliminary assessment is needed to quantify risk factors and screening of the targeted population with the highest falling risk. Based on recent research [55], screening tests alone can be predictive of falling risk with low-to-moderate ability and various degrees of sensitivity and specificity. Therefore, screening tools should be more accurate. On the other hand, frailty further increases the vulnerability of older adults and, as with fall events, this can be assessed and prevented. However, frailty remains an ambiguous concept and its testing in clinical practice is still limited [56]. In this context, the proposed model of screening for falls and frailty in the elderly is a multicomponent approach evaluating risk factors for both conditions through geriatric assessment and functional tests. The literature demonstrates the usefulness of wearable technologies to evaluate different aspects of elderly daily living. As for the risk of falling, previous research highlighted the accuracy of sensor-based assessment and related values in detecting an early risk [57]. However, sensor-based technology alone is not sufficient in order to prevent fall events and the frailty condition, which together could indeed be recognized with a combined methodology--or screening protocol--including functional tests and geriatric exams. According to the results of this study, posture and gait analysis highlighted significant differences among groups of our sample, identifying frail subjects and/or with high falling risk. Both stabilometric and gait parameters can be predictive of fall events, whereas TUG test and 6 MWT can in particular predict frailty. \begin{table}
\begin{tabular}{c c c c c c} \hline  & & **BMI** & **TUG\_Duration** & **TUG\_Lift\_Acc** & **TUG\_FR** \\ \hline BMI & Pearson’s r & — & & & \\  & \(p\)-value & — & & & \\  & Spearman’s rho & — & & & \\  & \(p\)-value & — & & & \\ TUG\_Duration & Pearson’s r & \(-\)0.057 & — & & \\  & \(p\)-value & 0.705 & — & & \\  & Spearman’s rho & 0.299 & — & & \\  & \(p\)-value & 0.041  & — & & \\ TUG\_Lift\_Acc & Pearson’s r & \(-\)0.311 & \(-\)0.576 & — & \\  & \(p\)-value & 0.033  & \(<\)0.001  & — \\  & Spearman’s rho & \(-\)0.037 & \(-\)0.772 & — & \\  & \(p\)-value & 0.01  & \(<\)0.001  & — \\ TUG\_FR & Pearson’s r & \(-\)0.15 & \(-\)0.679 & 0.582 & — \\  & \(p\)-value & 0.313 & \(<\)0.001  & \(<\)0.001  & — \\  & Spearman’s rho & \(-\)0.257 & \(-\)0.651 & 0.501 & — \\  & \(p\)-value & 0.081 & \(<\)0.001  & — \\ \hline \end{tabular}
\end{table} 
Table 5: Correlation matrix. Related to the stabilometry, path length, sway area, and the maximum path velocity are predictors of fall event when they are performed at OE (conversely, we found no differences at CE). Although sight generally contributes to maintaining stability, our sample of elderly had vision-independent behaviour to control their upright stability. This behavioural phenomenon often occurs with aging, maybe due to reductions in visual acuity, alterations in the perception of contrast, conditions like presbyopia, cataracts, and maculopathy, that are factors correlated with the increased risk of falling. Falling can be related to various and subjective factors, however, poor balance has been associated with the increased occurrence of falls in older people [58]. Previous studies [59] highlighted how the balance tests obtained with stabilizer platforms are sensitive in differentiating performance between young, adult, and elderly populations.