Effects of a 3D motion recognition-based virtual training system on balance and gait performance in older adults

This study examined the effects of a 3D motion-recognition-based virtual training system on balance and gait in older adults.

Thirty older adults ( ≥ 60 years) were randomly assigned to the experimental group (n = 15) and the control group (n = 15). The experimental group underwent 3D motion-recognition-based virtual training for 8 weeks, while the control group performed a conventional exercise program without 3D motion-recognition-based virtual training. Balance measures (surface area, weight distribution, and limit of stability) and gait measures (cadence, gait speed, and stride length) were assessed before and after the intervention. Data were analyzed using paired t-tests and analysis of covariance (ANCOVA).

After the intervention, the experimental group showed significant improvements in all balance and gait parameters (p < 0.05), whereas the control group demonstrated significant improvements in balance and gait parameters except for surface area (p < 0.05). Notably, weight distribution, limit of stability, cadence, and gait velocity showed significantly greater improvements in the experimental group compared with the control group (p < 0.05). However, no significant between-group differences were observed for surface area and stride length.

The 3D motion-recognition-based virtual training system is an effective intervention for improving balance and gait function in older adults, contributing to enhanced mobility and balance ability. Future studies should further investigate the long-term effects of this intervention and work toward optimizing the training protocols.