Falls severely affect older adults and are emerging as a global health and financial burden for public health care systems. Multiple studies have validated the use of virtual reality (VR) to prevent falls and reduce the risk of falls among older adults with cognitive deficits. Therefore, we evaluated the effectiveness of VR-based cable car simulation (CCS) using a Nintendo Wii Balance Board (WBB) to assess balance and profile individuals based on fall risk and age, and validated using the Biodex Balance System. Center of pressure (COP) displacement and mean velocity (MV) metrics obtained from the WBB were used for balance assessment.
Methods:
A total of 23 young participants (10 females; M = 29.9, SD = 5.0) were recruited from the Agência Regional para o Desenvolvimento da Investigação, Tecnologia e Inovação, and 25 older participants (19 females; M = 71.2, SD = 7.8) were recruited from a local senior gymnasium in Funchal, Portugal. All participants took part in a repeated-measures study design. Results indicated that young adults exhibited greater COP displacement than older adults in the anterior–posterior (AP) direction.
Results:
Significant differences were found in COP displacement between the groups, confirming age-related variations in balance performance. However, no significant differences were observed in MV. Discriminant analysis models were employed using COP displacement and MV to classify participants by age and fall risk. The best classification performance was achieved for the CCS at 77%, with average turns at 80%, average speeds at 86%, and 83% for the combined features using stepwise regression.
Discussion:
The selected features included the COP displacement for speeds and turning angles in both AP and medial–lateral (M-L) directions, as well as the mean values of speeds and turns for both AP and M-L. The system can accurately differentiate balance patterns across age groups and risk categories, indicating a reliable and ecologically valid assessment method.
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