The Role of Virtual Reality-Based Balance Training Versus Conventional Balance Exercise in Reducing Risk of Fall Among OA Patients
DOI:
https://doi.org/10.61919/8qfh7n60Keywords:
Osteoarthritis, Virtual Reality, Balance Training, Fall Risk, Functional Mobility, Pain ManagementAbstract
Background: Osteoarthritis (OA) is a prevalent degenerative joint disorder among older adults, often resulting in pain, impaired balance, and increased risk of falls. Traditional balance training programs may be limited by patient adherence and lack of dynamic engagement. Virtual reality-based balance training (VR-BBT) has emerged as a novel therapeutic approach offering interactive, feedback-driven rehabilitation with the potential to enhance outcomes in OA management. Objective: To compare the effectiveness of VR-BBT versus conventional balance exercises (CBE) in reducing fall risk, improving balance, and alleviating pain in patients with osteoarthritis. Methods: This randomized controlled trial included 60 OA patients aged 50–70 years, randomized into VR-BBT (n=30) and CBE (n=30) groups. Both groups received 12 weeks of supervised intervention. Outcomes were assessed using the Timed Up and Go (TUG) test, Berg Balance Scale (BBS), and Visual Analog Scale (VAS) at baseline, 6 weeks, and 12 weeks. Data were analyzed using paired t-tests and ANCOVA to evaluate within- and between-group changes. Results: The VR-BBT group showed significantly greater improvement across all outcomes. Mean post-treatment pain scores were lower in VR-BBT (2.40) than CBE (4.77; p=0.002). VR-BBT demonstrated higher BBS scores (3.10 vs 1.43; p<0.001) and faster TUG times (1.47 vs 1.83; p=0.002). Effect sizes were large, indicating clinically meaningful benefits. Conclusion: VR-BBT is superior to conventional balance training in reducing fall risk, improving functional mobility, and relieving pain among patients with OA. These findings support the integration of immersive technologies into routine rehabilitation for older adults with musculoskeletal impairments
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Copyright (c) 2025 Muhammad Danial Baig Chughtai, Baseerat Iqbal, Sonia Kumari Ahuja, Mariam Tariq, Anam Hamid, Hanan Azfar, Maidah Bashir, Hafiz Ali Bin Asim (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.