# A Virtual Reality-Based Simulation Tool for Assessing the Risk of Falls in Older Adults
## 5 Discussion  
The main goal of our study was to assess the feasibility of using a KAVE-based VR platform combining simulations of Levadas and a cable car to perform a balanced assessment and profiling of the older adult population for high risk of falls and the related user experience. Overall, the participants reported high presence scores in the ITC-SOPI questionnaire, suggesting the validity of the ecological functional simulation and good usability scores with the SUS. The participants' level of familiarity with VR technology may impact the assessment. We did not record the participant's VR familiarity experience; however, VR simulation sickness was monitored. The simulation sickness was classified into three categories: None, Moderate, and High. A total of 79% of participants reported no VR simulation sickness, and the rest experienced only a moderate level, indicating low simulation sickness overall. To evaluate the feasibility and sensitivity of the system as a profiling method capable of detecting users with a high risk of falls, we used the BBS as a gold-standard reference for balance assessment and predicting the risk of falls. In addition, two senior fitness tests (2 MST and 30 SCST) were also implemented together with the CSS. The CCS COP data show that CCS trajectory angles and speeds impacted the participant's balance in AP and ML directions. Significant differences in CoP metrics were observed for the higher speeds (5 m/s and 7 m/s) and turning angles (90 and \(-\)90). In addition, numerous features from the CCS were correlated with BBS features, which supports the validity of our CCS to induce behavioral responses and for balance assessment. The performance of DA models was evaluated to classify participants as high-risk and low-risk falls. We achieved excellent results from the classification using a step-wise feature selection. A linear DA on the selected features rendered a classification accuracy of 100%, indicating that our VR simulation of ecological and functional activities is precise in identifying the risk of falls in older adults. This also suggests that immersive VR environments can be used to implement standard procedures for fitness and balance assessments, proposing alternatives to traditional and expensive laboratory setups and creating custom environments based on functional activities with higher ecological validity. The classical functional tests (e.g., timed-up-and-go) are considered objective assessment tools without using certain equipment to acquire reliable data. These tests are not accurate in detecting minute changes because of the ceiling effect [59]. In contrast, the force platforms are commonly used for the balance assessment. However, they are time-consuming, require a laboratory setup, and cannot be used in clinical environments [59; 60]. Previous research reported 86% accuracy with a WBB-based exergame to assess the physical independence of the participants. A 30-s sit-stand test was used as a reference to compare the results [61]. [PERSON] et al. developed a balance ability diagnosis system for the elderly for balance assessment using a WII balance board. The stability index (SI) algorithm was implemented, and the center of pressure parameter was used to predict the stability index of the balance system (Biodex SD). High accuracy was observed for the SI algorithm, and the linear regression model confirmed that the R-values ranged between 0.943 and 0.983 [62]. Similarly, another study evaluated the effect of virtual reality exercises on balance and fall in older adults. The instruments used in this study included a demographic questionnaire, the Berg Balance Scale (BBS), the Timed Up and Go (TUG)