To date, there has been no systematic reviews that we are aware of that have synthesized the available evidence on the effectiveness of computer-based interventions in terms of balance and mobility outcomes during rehabilitation. Less is known about the effectiveness of computer-based technology in other populations due to lack of quality randomized controlled trials (8, 10, 18). In turn, this may assist with improved adherence to such therapy programmes.Ĭurrent evidence has demonstrated positive effects of virtual-reality rehabilitation in people with upper limb impairments post stroke (16, 17). It is also thought that this technology may be more engaging and fun for patients as they can interact with programmes and may be less likely to focus on their health condition. This may be important, given that visual and proprioceptive feedback are important components of balance control (14, 15). The advantage of such gaming and other virtual-reality systems is that they provide visual or other forms of feedback through a screen or a head-mounted device, which allows the user to interact with virtual environments to simulate balance and functional tasks at intensities that may be greater than traditional therapies (11–13). The Nintendo Wii alone has been adapted for rehabilitation across health settings in many countries, with reports of 61% of urban stroke rehabilitation centres owning a console in Australia (9, 10). The use of technology through interactive gaming and virtual-reality is becoming increasingly popular with clinicians to create stimulating and challenging environments to improve balance and mobility within therapy sessions. These exercise programmes may be undertaken within a home or clinical setting (7, 8). Indeed, it has been shown that up to 42% of falls in older people living in the community can be prevented by well-designed exercise programmes that provide a moderate-to-high challenge to balance, that are undertaken for at least 2 hours per week (6, 7). Exercise programmes are often prescribed to improve balance, with the aim of reducing falls. Poor balance is an important risk factor for falls (3–5). The impact of falls also has a significant cost for health services, with the annual cost of falls-related injury in Australia expected to rise almost 3-fold to AUD 1.4 billion by 2051 (2). This has significant implications for the individual in terms of injury, reduced mobility and independence at home and in the community. E-mail: Epub ahead of print Oct 7, 2014įalls are a major issue affecting older people, with one-third of people aged 65 years and over falling at least once each year (1). Mahoneys Road & Burwood Highway, Burwood East Victoria, 3151, Australia. Guarantor’s address: Amy Dennett, Department of Physiotherapy, Peter James Centre, Cnr. Key words: falls balance mobility virtual-reality meta-analysis.
There was low-to-moderate-quality evidence that computerized devices have no significant effect on mobility, falls efficacy and falls risk in community-dwelling older adults, and people with a neurological condition compared with physiotherapy.ĬONCLUSION:There is high-quality evidence that computerized devices that provide feedback may be useful in improving balance in people with neurological conditions compared with no therapy, but there is a lack of evidence supporting more meaningful changes in mobility and falls risk. There was high-quality evidence that computerized devices can improve dynamic balance in people with a neurological condition compared with no therapy. Risk of bias for individual trials was assessed with the (Physiotherapy Evidence Database) PEDro scale.ĭATA SYNTHESIS: Thirty trials were included. The GRADE approach was used to summarize the level of evidence for each completed meta-analysis. OBJECTIVE: To determine the effectiveness of computer-based electronic devices that provide feedback in improving mobility and balance and reducing falls.ĭATA SOURCES:Randomized controlled trials were searched from the earliest available date to August 2013.ĭATA EXTRACTION: Standardized mean differences were used to complete meta-analyses, with statistical heterogeneity being described with the I-squared statistic.
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