## 4 Discussion
The stabilometry is sensitive and useful in showing changes in balance in longitudinal studies, but the impact that these measures have in predicting fall events is not yet clear. It has been observed that some parameters, such as the postural sway and the amplitudes of medium-lateral oscillations of the CoP at OE can provide useful information in predicting future or recurrent fall events, even though great uncertainty persists. In another study [60] it has been remarked that stabilometry can discriminate faller and non-faller subjects through the study of medio-lateral oscillations. These oscillations could be indicators of a fall event. Little information has been investigated about the other parameters such as the sway area and the path length. The TUG [61] as well as other performance tests (Performed Oriented Mobility Assessment, POMA, and St. Thomas's Risk Assessment Tool in Falling Elderly Inpatients, STRATIFY) appear to be correlated with fall events, but, at the same time, lack sensitivity and accuracy [62; 63]. In fact, they do not seem able to follow changes in the balance over time. Some studies have highlighted the possible usefulness of the TUG as a predictor of fracture in the elderly related to fall events [64]. However, our results suggest that the duration of the TUG test can be considered as a predictor of fall events. In addition, the TUG can predict the performance threshold associated with the condition of frailty. Using the accelerometer, it is possible to calculate the speed and duration of rotation, considered indices of dynamic instability of subjects [65; 66; 67], which in our sample were statistically different in the able and frail groups and fall and no fall groups. Together with the TUG, the 6 MWT distance could also be a predictor of the condition of frailty. In the literature it has been shown that the 10 MWT has a good correlation with disability [61; 68] thus, a lower walking speed leads to a limitation of independence and could be predictor of fall events, even though, based on our data, it cannot be considered a valid predictor of fall events. Although the evidence shows that the spatio-temporal parameters of gait recorded by accelerometer can differentiate faller from non-faller subjects in the elderly [68], we did not observe such dependence probably due to the different range of cognitive and motor skills in our sample. Regarding the bioimpedance analysis (BIA) data, no differences or predictive values were found among groups. This result disagrees with the literature; although no predictivity was demonstrated in the present study, the body mass index (BMI) should be correlated with falls [69; 70]. Using the Spearman correlation index, a statistically significant relationship was found between the increase in BMI and body fat and a reduction in rotation speed at the TUG test. Furthermore, the BMI correlates directly with the duration of the TUG. Therefore, BMI indirectly impacts on the stability of subjects. Our study has some limitations. The results that we found could be confirmed with a larger sample size. Moreover, we checked for fall events after a year from the tests and geriatric exams. Therefore, we lack a follow-up and instrumental parameters comparison before and after the fall event.