As an alternative to conventional balance training, virtual reality rehabilitation (VRR) has increasingly been used. As a biomechanical strategy for maintaining balance, the individual tries to maintain his or her center of gravity on his or her support base using all possible means of doing so ( 12- 14).Ĭonventional balance exercises are one of the most preferred exercise options for improving balance in geriatric populations. These responses are related to the integrity of range of motion, muscle strength and proprioception ( 11). Since one in three elderly individuals suffer falls, it is necessary to develop interventions to promote the maintenance of postural balance in this population ( 10).īalancing is an extremely complex process that involves the proper functioning of the vestibular, visual and central and peripheral nervous systems, as well as the responses of the musculoskeletal system to sensory stimuli. Approximately 30% of falls result in severe injuries in the elderly, and there is a relationship between age and the frequency of episodes of postural imbalance ( 9). Falls increase rates of morbidity, mortality and hospitalization and can cause injuries that are costly to treat ( 7, 8). Falls are defined as episodes of imbalance that can cause the elderly to come into accidental contact with the ground or nearby surfaces ( 5, 6). Therefore, possible repercussions, such as falls, can occur frequently in the elderly population.
In this scenario, the growth of the elderly population has become a public health concern because aging brings with it a series of physiological and anatomical changes that predispose people to chronic diseases and functional limitations ( 1- 4). The elderly population -those aged 60 years or older- is expected to more than double by 2050 and more than triple by 2100, from 962 million worldwide in 2017 to 2.1 billion in 2050 and 3.1 billion in 2100 ( 1). Globally, the number of elderly individuals is growing faster than all of the younger age groups. This improvement is evident when evaluating the changes using the BBS. The KS is able to promote improvements in static and dynamic postural balance in the elderly, who reached a condition close to what was observed in young adults. However, the elderly showed a balance gain according to the BBS scores between the pre- and post-treatment evaluations (P = 0.005), which did not occur in the younger adults (P = 0.31). The elderly scored lower on the BBS than the younger adults both before and after treatment (P = 0.0001 and P = 0.0006, respectively). The initial and final evaluations included the Berg Balance Scale (BBS), the Timed Up and Go (TUG) test and the tandem Romberg test.Īfter treatment with the KS, the elderly required a longer time to perform the TUG test and had lower static balance results in the tandem Romberg test compared to younger adults however, there were no significant differences between the pre- and post-treatment values for these two tests within either group (P > 0.05). The period between the evaluations was five weeks, and the sessions were held three times per week. Each session involved muscle stretching and motor coordination exercises, as well as use of the KS.
This was a non-randomized controlled clinical trial in which 10 elderly subjects and 10 younger adults underwent a 10-session rehabilitation protocol lasting 20 minutes per session.
This study was conducted to evaluate the effectiveness of a rehabilitation program using the Kinect sensor (KS) on the postural balance of the elderly. The use of virtual rehabilitation, i.e., rehabilitation using electronic platforms, has been increasing due to the increased treatment adherence observed with these methods.
Taking into consideration the inversion of the age pyramid in the coming years and the limitations and diseases that predispose the elderly to episodes of falling, it is necessary to develop resources that can address postural balance in this population.