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24 February 2023

Acceptability, Feasibility, and Effectiveness of Immersive Virtual Technologies to Promote Exercise in Older Adults: A Systematic Review and Meta-Analysis

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1
Department of Rehabilitation, Faculty of Medicine, Laval University, Quebec, QC G1V 0A6, Canada
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Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre Intégré Universitaire de Santé et de Services Sociaux de la Capitale Nationale (CIUSSS-CN), Quebec, QC G1M 2S8, Canada
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Alborea, Quebec, QC G1V 0A6, Canada
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Author to whom correspondence should be addressed.
Sensors2023, 23(5), 2506;https://doi.org/10.3390/s23052506
This article belongs to the Special Issue Development of Virtual and Augmented Reality Systems for Health and Clinical Assessment
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Abstract

Context: This review aimed to synthesize the literature on the acceptability, feasibility, and effectiveness of immersive virtual technologies to promote physical exercise in older people. Method: We performed a literature review, based on four databases (PubMed, CINAHL, Embase, and Scopus; last search: 30 January 2023). Eligible studies had to use immersive technology with participants aged 60 years and over. The results regarding acceptability, feasibility, and effectiveness of immersive technology-based interventions in older people were extracted. The standardized mean differences were then computed using a random model effect. Results: In total, 54 relevant studies (1853 participants) were identified through search strategies. Concerning the acceptability, most participants reported a pleasant experience and a desire to use the technology again. The average increase in the pre/post Simulator Sickness Questionnaire score was 0.43 in healthy subjects and 3.23 in subjects with neurological disorders, demonstrating this technology’s feasibility. Regarding the effectiveness, our meta-analysis showed a positive effect of the use of virtual reality technology on balance (SMD = 1.05; 95% CI: 0.75–1.36; p < 0.001) and gait outcomes (SMD = 0.7; 95% CI: 0.14–0.80; p < 0.001). However, these results suffered from inconsistency and the number of trials dealing with these outcomes remains low, calling for further studies. Conclusions: Virtual reality seems to be well accepted by older people and its use with this population is feasible. However, more studies are needed to conclude its effectiveness in promoting exercise in older people.

1. Introduction

According to the World Health Organization, the number of people aged 60 years and over will reach 2 billion by 2050, while those aged 80 years and above are expected to grow from 125 million (in 2018) to 434 million in 2050 [1]. This accelerated aging currently observed in most industrialized countries is causing an increase in the prevalence of people with functional limitations related to mobility and fall risks. Indeed, aging results in a progressive decline of different body functions, leading to a higher risk of morbidity [2] and recurrent balance and walking disorders. Over the age of 65 years, more than a third of people fall at least once a year [3] as gait and balance disorders increase with age [4]. Given their prevalence and the physical, physiological, and psychological impact in older people, falls are a significant concern for health systems. Falls are predictors of decreased social participation [5]. It is therefore critical to find effective avenues for helping older people to prevent falls and rehabilitate balance disorders in order to maintain their independence in daily activities.
Many studies, as summarized in [6,7], have shown that rehabilitation can play a fundamental role in reducing the consequences related to balance disorders while improving the efficiency of the health system [8]. Among other rehabilitation interventions, physiotherapy, with interventions aimed at improving balance and strength, offers promising features in the prevention of falls in populations at risk [9]. However, while studies have shown that conventional exercises could reduce the risk of falling by 21% in older people, this still requires a certain amount of practice (at least three hours per week) to be effective. Reducing the risk of falling through conventional physiotherapy therefore demands time, availability, great treatment adherence, and frequent visits to the hospital or rehabilitation center [10]. Recent technological developments such as virtual and augmented reality technologies might be a solution to these needs. This technology provides interesting potential to increase treatment intensity and deliver remote or unsupervised rehabilitation for patients who do not have access to healthcare systems, for economic or geographical reasons.
Virtual reality (VR) is often defined as immersive or non-immersive according to the devices used to submerse users’ senses. In immersive VR, the immersion is created through the use of a head-mounted display or a cave automatic virtual environment (CAVE). VR must also be distinguished from mixed reality systems such as augmented reality (AR), where real-world elements are being included into the virtual environment [11]. In this review, immersive VR and AR were categorized as immersive technologies.
Immersive virtual technologies have emerged as effective tools to perform exercises aimed at improving balance and strength in the community-dwelling adults [12,13]. These technologies also appear beneficial for promoting engagement and motivation in physical activity interventions. VR and AR can be used at different stages of the physical rehabilitation process, i.e., for assessment, treatment, or research purposes [14]. Such technologies offer interesting possibilities for neurorehabilitation using tridimensional environments, multisensorial stimulations, and precise measures of kinematics [15]. As an example, these devices can be used as a relevant means to deliver interventions for improving walking in a Parkinson’s disease (PD) population [16], as well as to assess the displacement of the center of gravity and balance functions in both healthy older people and people with disability [17]. Immersive VR and AR can also be used to establish and tailor interventions according to the severity of gait and balance issues. Furthermore, as shown by Canning et al. [18], such technology offers potential to better understand the physiological mechanisms responsible for neurological diseases and to measure indicators of fall risk in the older people [19].
Although immersive technologies were found to be effective in numerous areas, their integration into clinical practice remains a challenge [20], with unknown evidence regarding their feasibility, acceptability, and effectiveness in older people. To the best of our knowledge, no systematic review has investigated all of these three main aspects through a single summarized literature review. In this paper, we, therefore, propose a new systematic review aiming to summarize the evidence on the feasibility and acceptability, and to evaluate the effectiveness of VR and AR in older people.

2. Materials and Methods

2.1. Search Strategy

This review has been performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [21]. The search strategy was mainly directed toward finding published articles using four wide databases (MEDLINE via the PubMed platform, CINAHL Plus with Full Text via the EBSCOhost platform, Embase, and Scopus). Our search strategy was based on a mixture of indexed and free vocabulary keywords (Appendix A).

2.2. Eligibility Criteria

Studies were included if they reported results (1) addressing acceptability, feasibility, and/or effectiveness; (2) of immersive VR or AR technology in the physical therapy or rehabilitation context; (3) on adults with a mean age of 60 years or older (as defined by the United Nations); and (4) that were published in English or French, with no limit on the date. Systematic reviews with or without meta-analysis, reviews, conference or congress papers, and case report studies were excluded. Pre-post interventional studies assessing the effectiveness of immersive VR or AR in older adults and providing sufficient data to analyze changes in outcomes were included in the meta-analysis.

2.3. Study Selection

References retrieved from MEDLINE, CINAHL, Embase, and Scopus were exported into the Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia. Available at www.covidence.org) [22]. In addition, two independent reviewers carefully reviewed the references list of relevant systematic reviews and meta-analyses to further extend the identification of potential articles according to the inclusion and exclusion criteria. The study selection was first carried out separately by two independent reviewers, with respect to the eligibility criteria described above. A consensus meeting was organized to resolve any discrepancy. This happened when reviewers differed in their respective decisions, or if one of them had doubts about the potential inclusion of a study. If the disagreement persisted, a third independent reviewer, blinded to the selections of the first two reviewers, was invited to screen and resolve the issue as a final decision.

2.4. Data Extraction

Two independent reviewers extracted the data from the included studies. Each reviewer had half of the articles selected to read. All relevant data were combined in a single Excel table (Microsoft 365). For each study, the following information was retrieved: the date of publication, the country in which the study took place, the population and its main characteristics (type of population, mean age, time since diagnosis of the pathology, degree of impairment if applicable, sample size, sex distribution), the experimentation performed (type of experimentation, duration of exposure in immersive environment, presence or absence of supervision, brand of immersive headset used if applicable), and the results and assessment methods for the three targeted outcomes (acceptability, feasibility, and effectiveness), as well as the authors’ conclusions.

2.5. Methodological Quality Assessment of the Selected Studies

Following the selection and the data extraction, each reviewer assessed the methodological quality of the randomized control trials using the PEDro scale [23]. This 11-item scale, containing up to 10 scoring criteria, was applied to determine the quality of each study’s methodology. However, in our review, criteria 5 and 6, related to the blinding of all subjects and blinding of all therapists who administered the intervention, respectively, were removed since it is impossible for subjects and therapists to be blinded in studies using such technologies. Therefore, the highest possible score for an article was 8, given that the first criteria was not designed to be scored [24].
Afterward, the score of each study was interpreted as suggested by Foley et al. [24], in which a score of 9 or 10 indicates an excellent methodological quality, a score of 6 to 8 means a good methodological quality, a score of 4 or 5 is considered as an acceptable methodological quality, and a score of <4 indicates poor methodological quality. As presented in Cashin et al. [25], this scoring method has demonstrated not only a moderate to excellent inter-rater reliability for clinical trials related to physiotherapy interventions but also a good convergent validity.
Regarding the non-randomized experimental studies, the National Institute of Health Quality Assessment Tool was used to assess their methodological quality, whereas for qualitative studies, the grid of the Centre for Evidence-Based Medicine (CEBM) for Critical Appraisal of Qualitative Studies [26] was used. This tool allows for the evaluation of the reliability, importance, and applicability of the reported clinical evidence. Finally, the evidence levels of the studies dealing with the effectiveness of the immersive technologies were determined using the Jovell and Navarro-Rubio scale [27]. In this scale, the study design is specified as one of 9 levels, in descending orders of strength (see Table 1 in [28]).

2.6. Statistical Analysis

Meta-analyses were considered when at least four studies provided quantitative measures of effect for the same outcome. The changes induced by VR and AR were computed from the included studies. For each relevant outcome, the following information was introduced into the RevMan 5.3 software: pre- and post-intervention mean scores ± standard deviation and the total number of participants. This enabled us to generate forest plots, underlining the treatment effectiveness. When different scales were used for one outcome, the standardized mean difference (SMD) and 95% confidence interval were calculated for each study. The magnitude of the effect was interpreted according to Cohen’s guidelines: small for SMD ≤ 0.5, medium for 0.5 < SMD ≤ 0.8, and large for SMD > 0.8 [29]. The I2 statistical test was also considered to estimate results’ heterogeneity. As suggested by the Cochrane Handbook, heterogeneity was defined as non-significant for I2 < 30%, moderate for 30% ≤ I2 < 50%, substantial for 50% ≤ I2 < 75%, and considerable for I2 ≥ 75%. In case of heterogeneity, a random effect model was always considered. Outlier study removal was always motivated by a sensitivity analysis. Subgroup analyses were considered to assess the influence of time (studies published after 2020 vs. before 2020), the type of device (AR vs. VR), and the participants’ health status (healthy older adults vs. older adults with any pathology) on immersive technologies effectiveness when at least 10 studies were included in the analysis.
The strength of the body of evidence was evaluated according to the GRADE approach. The certainty of the evidence was consequently established depending on the risk of bias of the included studies, the number of participants, the statistical heterogeneity, the effect size, and the design of the studies.

3. Results

The electronic search strategy in the MEDLINE, CINAHL, Embase, and Scopus databases yielded 2542 records. Handsearching led to 41 additional articles (Figure 1). As a result, a total of 2583 articles were exported into the Covidence software [22]. After removing the duplicates, 2070 titles and abstracts were screened. A total of 54 different studies (1853 participants) were finally selected. These studies were issued from 23 different countries (Table 1). The years of publication ranged from 2006 to 2022. In total, 91% of the included studies were published after 2015 and 67% were published in 2020 or later. In the next subsections, we report the most important findings.
Figure 1. Flow chart diagram of included studies.
Table 1. Characteristics of the included studies.

3.1. Characteristics of the Experiment Designed in the Selected Studies

As shown in Table 1, 43 of the 54 studies used a VR headset. In total, 19 studies [31,32,35,37,38,42,47,49,54,59,60,62,63,64,65,66,67,68] had used the HTC Vive, 8 studies [16,34,39,41,46,52,58,61,71] used the Oculus Rift, 3 studies [51,55,56] used the Glasstron LDI-100B, 3 studies used the Oculus Quest [36,43,69], and 3 studies [30,33,45] used the Samsung Gear VR. The remaining studies used the following headsets: Revelation 3D VR Headset with a Lumia 930 phone [53], University of Ulster’s Virtual Reality Rehabilitation (UUVRR) System [40], Valve Index [48], VR GLASS [70], and Balance Rehabilitation Unit (BRU) [57]. Jung et al. [44] did not mention the type of VR headset used in their study. The following AR headsets were also used in different studies: AIRO II [72], Glasstron PLM-5700 [76], Laster WAVƎ [73], Microsoft Kinect [74,78], NEURO RAR [79], Portable Exergame Platform for Elderly (PEPE) [75], Microsoft HoloLens [67], UNICARE HEALTH [77], and i-visor FX601 [81].
Table 1 also reports the different types of populations groups, as well as the average age, the time since diagnosis, and the severity of illness when available in the selected paper. In total, 1 study [30] (using VR technology) included subjects with mild to moderate dementia, 6 studies included participants with Parkinson’s disease (5 VR and 1 AR [72]), 29 articles (22 VR, 7 AR, and 1 CAVE [82]) included healthy older people, 7 studies (3 VR and 4 AR) included people with stroke, 3 VR studies included patients with pain affecting their daily activities, 2 VR studies included patients with vestibular impairments, 2 VR studies included subjects at risk of falling, 3 VR studies included patients with cognitive impairments, 1 VR study [55] included a patient with a total knee replacement, 1 VR study [71] included a patient suffering from functional incapacities, 1 VR study [62] included a patient with hypertension, and 1 VR study [52] included a patient with a distal radius fracture.
In total, 10 studies (9 VR and 1 CAVE [82]) exposed their participants for no more than 15 min per session. In 18 studies using an immersive technology, the participants were exposed to a maximum of 30 min per session, whereas 10 studies (8 VR and 2 AR) exposed their participants to more than 30 min per session. Furthermore, 13 studies (9 VR and 5 AR) did not mention the exposure duration. As reported in Table 1, 30 studies (24 VR and 6 AR) exposed participants to several VR sessions. In 45 studies (36 VR, 10 AR, and 1 CAVE [82]), the participants were supervised during their experimentation. Finally, 9 studies (7 VR and 2 AR) did not report whether supervision was provided to participants while exposed to the virtual environment.

3.2. Methodological Quality Assessment

Table 2, Table 3 and Table 4 present the methodological quality assessment of the different studies included in this review. According to the PEDro scale (Table 2), 16 studies (14 VR and 2 AR) showed good quality and 14 studies (10 VR and 4 AR) showed acceptable quality. Regarding the non-experimental studies, the results are presented in Table 3. Based on the CEBM scale (Table 4), four qualitative studies (three VR and one CAVE) could be classified as of good methodological quality. However, the small sample sizes of these studies limit the generalizability of their respective findings.
Table 2. PEDro scale rating for experimental articles.
Table 3. NIH Quality Assessment tool.
Table 4. CEBM scale rating for qualitative studies.

3.3. Findings on the Acceptability, Feasibility, and Effectiveness

3.3.1. Acceptability

Twenty-one articles (Table 5) have addressed the acceptability of VR [16,30,32,33,36,39,41,42,48,49,50,52,57,62,64,66,67,80,82]). Syed-Abdul et al. [64] indicated that the headset (HTC Vive) was comfortable for the participants. Appel et al. [30] and Benham et al. [32] indicated that the participants found the immersive VR experience enjoyable (via a home questionnaire showing a high satisfaction rate). Brown [33], De Keersmaecker et al. [16], and Syed-Abdul et al. [64] also reported that their participants enjoyed the experience. In Appel et al. [30] and Brown [33], the participants reported that they would be willing to repeat the experience in the future if they had the opportunity. Benham et al. [32] showed that older people were very keen to try this new technology and Phu et al. [57] observed a similar rate of treatment adherence between the conventional exercise group and the immersive VR group, contrary to Cikajlo and Peterlin Potisk [39] and Syed-Abdul et al. [64] who reported a higher motivation towards the treatment in the VR groups compared to the conventional treatment groups.
Table 5. Results and author’s conclusions on the acceptability of immersive technologies with a geriatric population.
Janeh et al. [42] highlighted a moderate level of immersion and low fear of physical contact with the real environment during immersion. Syed-Abdul et al. [64] concluded that older people consider using a technology based on its ease and usefulness. Indeed, the enjoyment obtained during the experiences, as well as the perception of their participants, provided positive attitudes concerning the use of this new technology. No study has evaluated the acceptability of AR-based interventions and only one study addressed the acceptability of the CAVE system. Pedroli et al. [82] found that their participants were highly engaged when immersed in the CAVE environment. Accordingly, it appears that most participants reported that they forgot the training context, which could be responsible for their increasing implication in rehabilitation.

3.3.2. Feasibility

Twelve studies [16,35,36,37,38,41,46,48,53,56,61,64] used the Simulator Sickness Questionnaire (SSQ) [83] to assess the feasibility of immersive technology (Table 6). This questionnaire was administered before and after VR exposure. Saldana et al. [61] administered the SSQ questionnaire over two sessions and observed a decrease in the total score among the group using VR at the second assessment session. Indeed, the difference before and after exposure to the technology were −1.38 ± 2.29 at the first session and −0.25 ± 1.91 at the second session, indicating that fewer symptoms were present at the second visit. However, other studies [16,46,53,55] showed that, for a healthy population, the score averaged from 7.78 (2.39–16.45) before exposure to VR to 10.23 (1.36–15.21) after exposure to the technology, which, compared to populations with various health conditions, indicates an increase in the symptoms of discomfort related to the simulation. Across the papers addressing feasibility, while other works reported a decrease in the experienced side effects [42], opposite trends (an increase after immersion) were observed in [46].
Table 6. Results and author(s)’ conclusions on the feasibility of immersive technologies with a geriatric population.
Appel et al. [30] carried out VR testing in which the data were collected during pre/post-intervention. They concluded that there were no negative side effects to using the VR technology in the neurologically impaired population. Most of the participants had positive feedback and felt more relaxed, with a decrease in anxiety (1.96 ± 1.55 to 1.81 ± 1.51), stress (1.94 ± 1.5 to 1.86 ± 1.55), tension (1.48 ± 1.11 to 1.34 ± 0.83), and feeling upset (1.82 ± 1.25 to 1.42 ± 1.12).
With a home-built questionnaire evaluating the usability and engagement in AR, Bank et al. [72] reported a mean score of 69.3 ± 13.7 out of 100 for the usability section, indicating that the use of such technology was possible, and a mean score of 3.8 ± 0.5 out of 5 for engagement, which could be considered as moderate engagement. The ease of use and realism in manipulating objects are elements that may affect this sense of engagement. They concluded that AR is well tolerated and participants’ augmented experiences were close to real experiences. Crosbie et al. [40] assessed the physical demands of using VR with the Borg scale [84], ranging from 0 to 10. The perceived exertion score in the virtual environment was 5.6 ± 2.22 in the stroke group and 1.6 ± 1.24 in the healthy group, indicating that performing tasks in the virtual environment appeared to be more difficult for people with a stroke than healthy people. However, both groups reported favorable experiences with VR, even though the stroke group faced greater physical demands with completing the same tasks.

3.3.3. Effectiveness

Meta-Analysis
There was sufficient data (n ≥ 4) to quantify the effect of VR and AR on older adults’ balance and gait functions. Thirteen studies used instrumental measures to assess balance outcomes. These were the ABC scale, the Mini-BESTest, the Berg Balance Scale, the Tinetti Balance Test, the One-Leg Standing Balance Test, and the limits of stability (a posturography index). As underlined in Figure 2, AR and VR led to significant improvements in the balance function (SMD = 1.05; 95% CI: 0.75–1.36; p < 0.001) with a large magnitude of effect (SMD > 0.8). However, the heterogeneity between the studies was found to be moderate (I2 = 42%). According to the GRADE approach, owing to the limited number of studies and sample size, the potential risk of bias, and the significant heterogeneity of these results, the strength of the body of evidence was decreased by two and therefore considered as low.
Figure 2. Forest plot of effects of intervention using immersive technologies on balance.
Subgroup analyses revealed that the effect of immersive technologies on balance outcomes was not influenced by the years (p = 0.53). The studies published before 2021 (SMD = 0.89; 95% CI: 0.22–1.55; p = 0.009) led to similar balance benefits as the studies published between 2010 and 2020 (SMD = 1.13; 95% CI: 0.78–1.47; p < 0.001).
Fourteen studies used instrumental measures of gait outcomes. These were the gait speed, six-minute walk test, and Timed Up and Go test. As underlined in Figure 3, immersive technologies were found to significantly improve the outcome (SMD = 0.47; 95% CI: 0.14–0.80; p < 0.006). The effect size was considered as moderate (0.2 < SMD < 0.8) and the heterogeneity between the studies was found to be substantial (I2 = 61%). Given the low number of included studies, the potential risk of bias, the moderate effect size, and the substantial heterogeneity, the certainty of evidence was considered as very low.
Figure 3. Forest plot of effects of intervention using immersive technologies on gait speed.
Subgroup analyses revealed that immersive VR led to significant gait speed improvements (SMD = 0.37; 95% CI: 0.14–0.59; p = 0.001), whereas AR did not significantly enhance the gait outcomes (SMD = 1.11; 95% CI = −0.36–2.59; p = 0.14). However, as underlined by Appendix B, the effect of these technologies substantially differed according to the pathology.
Studies Results
Kim et al. [46] used the Mini-BESTest to assess the balance in healthy participants and people with Parkinson’s disease. For the healthy population, the pre-intervention balance score of 23 ± 4 changed to 25 ± 3 after experimentation with VR, while in participants with Parkinson’s, the score increased from 21 ± 4 to 23 ± 4, with the change being statistically significant in each group (F (2,30) = 5.33, p < 0.05). They also reported a gait speed improvement after VR exposure. The participants walked significantly faster after exposure, from 1.08 ± 0.34 m/s to 1.12 ± 0.27 m/s and from 1.16 ± 0.18 m/s to 1.20 ± 0.18 m/s, respectively, for healthy adults and people with Parkinson’s disease. Yoo et al. [81] also reported that AR contributed to a positive change in gait parameters, balance, and fall risk in older people after AR exposure.
Phu et al. [81] also investigated the gait speed in relation to the use of the BRU. This VR platform resulted in a significant 12% improvement in walking speed. The authors also observed a significant decrease in the risk of falling after the use of BRU. Indeed, the Falls Efficacy Scale–International (FES-I) post-exposure score decreased by 11.3 points, while the Five Times Sit-to-Stand (FTSTS) showed a significant decrease of 26.69% in the time required to complete the five repetitions. These two results led to the conclusion that BRU might be effective at reducing the risk of falls in older people. Two other studies [44,53] used the Activities-specific Balance Confidence scale (ABC) to quantify balance in people with vestibular impairment [53] and stroke [44] and observed a significant improvement in the performance with the ABC mean scores changing from 62.54 ± 4.8 to 71.36 ± 4.24 [53]. Jung et al. [44] reported an improvement of 9.5% ± 6.0%. It appears that VR training can improve the perception of balance in people with health problems. The researchers also used the Timed Up and Go (TUG) test to evaluate the potential effects of VR. They reported a mean decrease of 2.7 ± 1.9 sec in the time to complete the test after exposure to VR, showing an improvement in gait balance.
Janeh et al. [42] used the GAIT-Rite system to analyze different walking parameters before and after the use of a VR device. The length of the shortest step increased from 58.34 ± 8.27 cm to 60.45 ± 8.16 cm after exposure, while the walking symmetry varied from 1.05 ± 0.04% to 1.01 ± 0.06%. In this study, the cadence before exposure to VR was 102.81 ± 8.19 steps/min and this changed to 97.41 ± 9.9 steps/min after exposure to VR. The cadence parameter was also used by Yoo et al. [81] to document the effects of AR. The cadence before exposure to AR was 100.79 ± 9.92 steps/min and this increased to 116.73 ± 8.81 steps/min after exposure, indicating an increase in the walking cadence. It can therefore be suggested that, unlike the immersive VR used by Janeh et al. [42], AR leads to an increase in the walking cadence. Yoo et al.’s study [81] also found a significant increase in the Berg Balance Scale scores (47.60 ± 5.36 before and 53.50 ± 2.30 after exposure to AR).
Benham et al. [32] used VR to address pain. The Numeric Pain Rating Scale (NPRS) score showed a significant decrease, with pain scores changing from 3.5 ± 1.73 to 0.9 ± 1.62 after exposure to VR. Their outcomes also included the World Health Organization Quality of Life Scale Brief Version (WHOQOL-BREF), where no effect was reported. In conclusion, we can note that there is a significant improvement in pain via the distraction provided by VR.
Furthermore, as presented in Table 7, some papers (VR [39,57], AR [72,76]) focused on the upper limbs. Phu et al. [57] investigated the grip strength and found that there was a significant improvement in the grip strength in the immersive VR users. Indeed, the BRU group reported a significant increase (p = 0.027) of 6.82% over the initial score [57]. Fischer et al. [76] used AR coupled with a pneumatic orthosis for the upper limb. This study reported a significant increase in the task performance on the Wolf Motor Function Test (WMFT), which was illustrated by a 12.9-point decrease (p = 0.02). However, they did not report a significant change in the biomechanical measures of hand or grip strength (p > 0.20) but reported that the AR would allow faster transitions between tasks and more opportunities to practice gripping objects that would not be available in the conventional clinical environment.
Table 7. Results and author’s conclusions on the effectiveness of immersive technologies with a geriatric population.
Lastly, Kanyilmaz et al. have assessed the effect of immersive VR on older adults suffering from dizziness [45]. The results of this work showed that the combination of immersive VR and vestibular rehabilitation offers greater vertigo improvements at 6 months post-intervention than vestibular rehabilitation alone.

4. Discussion

This review summarized what is currently known about the use of immersive VR and AR technologies in older people. The following subsections discuss the results regarding the main research purpose, such as the acceptability, the feasibility, and the effectiveness of VR. We also highlight the limitations of the present study.

4.1. Acceptability

Our review identified 21 articles addressing the acceptability of immersive technology in older adults (Table 5). The results emphasize that, when compared to conventional repetitive treatment, immersive technology allows for greater interest, enjoyment, and motivation [16,39,42,57,64]. In addition, different authors [30,39,64] reported that participants, namely older people with mild to moderate dementia, people with Parkinson’s disease, or healthy older people had a pleasant experience with the VR. This can be explained by the feelings of relaxation and adventure that were present, as well as the reduction in anxiety, stress, and pain that was observed after exposure. This hypothesis is supported by recent studies demonstrating a stress and anxiety reduction among adults immersed into the VR environment [85,86]. Furthermore, a high level of interest and excitement about the VR technology before trying may have also contributed to these positive feelings reported after immersion. For instance, Appel et al. [30] and Brown [33] found that participants in their study wanted to use the immersive technology again in the future and would recommend it to a friend (Table 5). In most cases, the participants said that the headset they used (e.g., HTC Vive) was comfortable [64]. However, further studies are needed to confirm the acceptability of different types of immersive technology devices.
During the immersive experiences, some studies have focused on the environments that older people preferred to visit. Appel et al. [30] and Brown [33] showed that older people were interested in dynamic, social, and familiar real-world scenes (e.g., real places in the world, past or present). The authors suggested that the geriatric population would like to share these experiences with loved ones such as their grandchildren for narrative purposes or in order to explore places they no longer have the physical or psychological capacity to visit [33]. In addition to exploration and tourism, including mental relaxation, it should be noted that older people would also be open to other experiences with VR [64]. However, the environment in which a user is navigating significantly influences his or her desire to use VR [32].
Contrastingly, most commercial applications could be too complex and difficult to be used by older adults [39], especially for those with less experience with new technologies [33]. This may have decreased the acceptability of such devices in this population [64] and therefore may make further experiences less enjoyable. Moreover, there could be an increased feeling of isolation and loneliness for some people with physical or cognitive limitations [33]. Those feelings could subsequently promote depressive or anxious feelings and thus produce the opposite of the desired effect. Nevertheless, as suggested by Brown in their study [33], these concerns can be addressed with users prior to experimentation in an immersive environment.

4.2. Feasibility

The most commonly reported measure for determining the feasibility of a VR technology was the use of the Simulator Sickness Questionnaire (SSQ) [83]. The SSQ was developed to measure sickness that can occur when using VR technology (Table 6). It consists of side effects similar to those of motion-induced sickness [87]. These side effects may be caused by the visual conflict created by the immersive headset [32]. For example, after VR exposure, it has been reported that a side effect such as postural instability could significantly affect the Mini-BESTest score [46]. Moreover, owing to their medication or non-motor symptoms related to their condition [46], people with Parkinson’s disease may have a higher score on the SSQ questionnaire even before immersion [42]. Thereby, the use of immersive technology can generate increasing variation in the participants’ scores. However, some studies [46,55] showed that these changes were generally mild (with transient symptoms such as nausea, eye discomfort, disorientation, etc.) or not significant; although, in young and healthy adults, a longer duration of exposure seems to lead to more intense symptoms [88]. Further research would therefore be needed to generalize these observations to the geriatric population.
People with physical limitations may have to make more effort to succeed in virtual task completion, potentially limiting the treatment adherence and inducing some stress [40]. In addition, although dynamic activities such as walking seem to reduce the symptoms among healthy young adults [88], it is worth noting that for an older person performing walking movements during VR immersion, there is a higher risk of feeling stress [33,42,55,56]. Consequently, a familiarization period with the VR or AR equipment might be recommended prior to the interventions. This would ensure the comfort and feasibility of the experience and limit the unpleasant effects [33]. Moreover, the decrease in vision loss that occurs with ageing might be another barrier to the use of VR. Nevertheless, studies have provided recommendations for its use in people with vision loss [89,90]. First, VR applications should offer their users the possibility to modify the virtual visual field and light intensity according to their vision possibilities. Second, visual cues can be provided during the game to direct users’ attention towards important information that would be displayed in their affected field of view. Lastly, the use of prism in AR should be considered to optically shift objects from outside the vision field.
The types of headsets used (Table 1) are essential during an immersive experience since they can have a great impact on the occurrence of side effects. Indeed, modern headsets such as the Oculus Rift or the HTC Vive can decrease the occurrence and severity of the side effects due to a better refresh rate, larger field-of-view, and better head tracking compared to older or lower quality immersive headsets [16,46]. This may result in less intense and transient symptoms. However, the use of controllers is challenging for older people, especially if they are not familiar with the new technologies [33]. Additional difficulties that can negatively affect the use of immersive technology comprise the controller’s calibration and connection with the headset [33]. To overcome these difficulties, several systems have now developed hand-tracking technology, which allows for the use of a VR headset without using controllers. Indeed, hand-tracking enables one to generate a virtual model of hands and fingers into the VR environment by recording and identifying the movements of these body parts using infrared cameras. These methods have already been used and validated among patients with stroke and healthy older adults [91].

4.3. Effectiveness

The most important results of this systematic review also concern the effectiveness of the VR technology among the community-dwelling older adults (Table 7). The results on the effectiveness can be summarized in three main aspects.
First, as shown in Table 7 and Figure 2, VR can be used to improve balance in older people and reduce the risk of falls. Indeed, this technology could achieve results similar to conventional exercises, but in half the time, with an intensity of 2 sessions of 30 min per week for 6 weeks in healthy subjects [57]. A significant improvement was also observed with the Mini-BESTest scores in people with Parkinson’s disease [46], as well as the Activities-specific Balance Confidence (ABC) Scale and the TUG among participants with stroke [44]. VR can also promote a more personalized approach for the user, allowing for greater specificity in the treatment of balance deficits, thus improving gains and adherence [57]. In fact, the VR method proposed in [51,56] has been shown to significantly decrease anterior trunk rotations, keeping the center of mass within the base of stability and thus reducing the incidence of falls [92]. By using the Falls Efficacy Scale (FES-I) in a study involving healthy subjects, Phu et al. [57] showed that the use of VR led to a small but significant decrease in the fear of falling.
Second, VR can be used to correct the gait pattern. Indeed, thanks to the screen embedded in the headset, the participant’s virtual foot appears to take a larger step in contrast to reality, exaggerating the decrease in the step length on the more affected side and thus forcing the user to take more symmetric steps on both sides [42]. Thus, the stance and swing times appeared to be more symmetrical after exposure to VR. This leads to the regularization of the cadence of the more affected side and a more symmetrical overall gait pattern [42]. However, larger randomized studies over a longer period are needed to confirm this effectiveness.
Third, Benham et al. [32] have shown a significant (p < 0.05) decrease in pain among participants after one session of VR. This decrease in the pain can be attributed to the distraction provided by the immersion. In fact, several studies have suggested that the immersive aspect of VR might be responsible for the reduced subjective experience of pain as the interaction with the real-world cues are being limited by the use of HMD [93]. This effect might be enhanced by the engaging, pleasant, and multisensorial feature of the immersive VR environment [93].
The effect of VR was also shown for other outcomes. VR resulted in fine motor skills improvements in a group of participants with Parkinson’s and a slight improvement in the Unified Parkinson’s Disease Rating Scale (UPDRS) [39]. An improvement in the grip strength was also observed in healthy subjects with the use of BRU [41]. Micarelli et al. [53] concluded that the addition of VR resulted in a significant improvement of the vestibulo-ocular reflex by increasing the frequency of visuo-vestibular conflicts. However, this study was conducted with a small sample of older people with mild cognitive impairments.

4.4. Perspectives

The results reported in this work provide several perspectives for the use of immersive technologies among older adults. While these technologies (VR and AR) are not yet implemented in our daily life, their increasing popularity, the decrease in their price, and their potential in terms of realism, interaction, and communication might reverse the situation. For instance, with the development of the metaverse, a parallel immersive virtual world intended to supplant the internet, it could be that rehabilitation is delivered remotely more often [94,95]. Such environments might also be of interest to improve older people’s social participation as it allows for realistic multi-user interactions. Given such perspectives, we believe that, in the future, VR will be used as a mean to deliver effective remote rehabilitation to complement therapy and increase treatment adherence and intensity.
Moreover, VR devices (and metaverse development) also hold potential to deliver rehabilitation and promote activity among people who have no/few access to healthcare services, such as in low-income countries. Several studies have demonstrated the feasibility of implementing such interventions in developing countries [96,97].

4.5. Limitations

Despite the positive effects of VR reported in different studies and summarized here, the generalization of these results ais limited by the small number of articles available for each population and for each type of outcome, as discussed above. The overall low methodological quality of the articles included in this review potentially reduces the strength of the reported conclusions. Despite these limitations, this first systematic review shows encouraging results for further research and decisions in clinical settings.

5. Conclusions

Virtual reality is well accepted by older people and provides an enjoyable experience. The results suggest that the use among this population is feasible since few symptoms were reported and the increased SSQ scores were not significant in most cases. Currently, despite the several advantages described above, it is impossible to conclude on the effectiveness of VR in relation to different pathologies and deficiencies since few studies with good methodological quality and sufficiently large sample sizes are available. However, the beneficial effects have been observed regarding balance, risk of falling, and gait pattern in studies with acceptable methodological quality.

Author Contributions

Conceptualization, C.S.B., G.E., B.D. and A.G.; methodology, B.D., A.G., G.E., J.C.A. and C.S.B.; validation, C.S.B.; formal analysis, G.E., B.D. and A.G.; investigation, G.E., B.D., A.G. and J.C.A.; data curation, B.D., A.G. and G.E.; writing—original draft preparation, B.D., A.G., J.C.A. and G.E.; writing—review and editing, G.E., A.A., N.R. and C.S.B.; supervision, C.S.B.; project administration, C.S.B.; funding acquisition, C.S.B. All authors have read and agreed to the published version of the manuscript.

Funding

G.E. received a scholarship grant from the Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris). J.C.A. and A.A. received scholarship grant from MITACS.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No new data were created in this review study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Search strategy in each database.
Table A1. Search strategy in each database.
MEDLINE (PubMed)
S1aged[MeSH Terms]
S2Elderly[Title/Abstract] OR Aged[Title/Abstract] OR Older[Title/Abstract] OR Elder[Title/Abstract] OR Geriatric*[Title/Abstract]
S3S1 OR S2
S4Virtual reality[MeSH Terms]
S5(Immersive[Title/Abstract] AND technolog*[Title/Abstract]) AND (“virtual realit*”[Title/Abstract]) OR VR[Title/Abstract] OR “Augmented realit*”[Title/Abstract] OR “HTC VIVE”[Title/Abstract] OR Oculus[Title/Abstract] OR “simulated environment*”[Title/Abstract] OR “artificial environment*”[Title/Abstract] OR “computer* simulat*”[Title/Abstract]
S6S4 OR S5
S7(Sports[MeSH Terms]) AND (Exercise[MeSH Terms])
S8“Physical activit*”[Title/Abstract] OR exercice*[Title/Abstract] OR sport*[Title/Abstract]
S9S7 OR S8
S10S3 AND S6 AND S9
CINAHL Plus with Full Text (EBSCOhost)
S1(MH « Aged+ »)
S2TI(Elderly OR Aged OR Older OR Elder OR Geriatric*) OR AB (Elderly OR Aged OR Older OR Elder OR Geriatric*)
S3S1 OR S2
S4(MH “Virtual Reality”) OR (MH “Augmented Reality”)
S5TI((Immersive AND technolog*) OR “virtual realit*” OR VR OR “Augmented realit*” OR “HTC VIVE” OR Oculus OR “simulated environment*” OR “artificial environment*” or “computer* simulat*”) OR AB ((Immersive AND technolog*) OR “virtual realit*” OR VR OR “Augmented realit*” OR “HTC VIVE” OR Oculus OR “simulated environment*” OR “artificial environment*” or “computer* simulat*”)
S6S4 OR S5
S7(MH “Physical Activity”) OR (MH “Sports+”) OR (MH “Exercise+”)
S8TI(« Physical activit* » OR exercice* OR sport*) OR AB (« Physical activit* » OR exercice* OR sport*)
S9S7 OR S8
S10S3 AND S6 AND S9
Embase
S1‘aged’/exp OR ‘aged’:ti,ab,kw OR ‘aged patient’:ti,ab,kw OR ‘aged people’:ti,ab,kw OR ‘aged person’:ti,ab,kw OR ‘aged subject’:ti,ab,kw OR ‘elderly’:ti,ab,kw OR ‘elderly patient’:ti,ab,kw OR ‘elderly people’:ti,ab,kw OR ‘elderly person’:ti,ab,kw OR ‘elderly subject’:ti,ab,kw OR ‘senior citizen’:ti,ab,kw OR ‘geriatric’/exp OR geriatric
S2‘virtual reality’/exp OR ‘virtual reality’:ti,ab,kw OR ‘augmented reality’/exp OR ‘augmented reality’:ti,ab,kw OR ‘virtual reality system’/exp OR ‘vr interface’:ti,ab,kw OR ‘vr system (virtual reality)’:ti,ab,kw OR ‘virtual reality interface’:ti,ab,kw OR ‘virtual reality system’:ti,ab,kw OR ‘htc vive’/exp OR ‘htc vive’ OR oculus:ti,ab OR ‘artificial environment’:ti,ab OR ‘simulated environment’:ti,ab OR ‘computer simulation’/exp OR ‘computer simulation’:ti,ab,kw OR ‘computer-based simulation’:ti,ab,kw
S3‘sport’/exp OR ‘sport’:ti,ab,kw OR ‘sports’:ti,ab,kw OR ‘exercise’/exp OR ‘effort’:ti,ab,kw OR ‘exercise’:ti,ab,kw OR ‘exercise performance’:ti,ab,kw OR ‘exercise training’:ti,ab,kw OR ‘fitness training’:ti,ab,kw OR ‘fitness workout’:ti,ab,kw OR ‘physical conditioning, human’:ti,ab,kw OR ‘physical effort’:ti,ab,kw OR ‘physical exercise’:ti,ab,kw OR ‘physical work-out’:ti,ab,kw OR ‘physical workout’:ti,ab,kw OR ‘physical activity’/exp OR ‘activity, physical’:ti,ab,kw OR ‘physical activity’:ti,ab,kw
S4S1 AND S2 AND S3
Scopus
S1(TITLE-ABS-KEY (“aged”) OR TITLE-ABS-KEY (“elder*”) OR TITLE-ABS-KEY (“older”) OR TITLE-ABS-KEY (“geriat*”))
S2(TITLE-ABS-KEY (“virtual reality”) OR TITLE-ABS-KEY (“VR”) OR
TITLE-ABS-KEY (“computer simulation”) OR TITLE-ABS-KEY (“Oculus”) OR TITLE-ABS-KEY (“htc vive”) OR TITLE-ABS-KEY (“augmented reality”))
S3(TITLE-ABS-KEY (“sport*”) OR TITLE-ABS-KEY (“physical activity”) OR TITLE-ABS-KEY (“exercise*”)
S4S1 AND S2 AND S3

Appendix B

Sensors 23 02506 g0a1
Figure A1. Forest-plot of effects of interventions using immersive technologies on gait speed—subgroup analyses to observe the influence of pathology.

References

  1. World Heath Organization. Ageing and Health. Available online: https://www.who.int/fr/news-room/fact-sheets/detail/ageing-and-health (accessed on 18 November 2020).
  2. Kirkwood, T.B. A systematic look at an old problem. Nature 2008, 451, 644–647. [Google Scholar] [CrossRef] [PubMed]
  3. Ambrens, M.; Tiedemann, A.; Delbaere, K.; Alley, S.; Vandelanotte, C. The effect of eHealth-based falls prevention programmes on balance in people aged 65 years and over living in the community: Protocol for a systematic review of randomised controlled trials. BMJ Open 2020, 10, e031200. [Google Scholar] [CrossRef]
  4. Osoba, M.Y.; Rao, A.K.; Agrawal, S.K.; Lalwani, A.K. Balance and gait in the elderly: A contemporary review. Laryngoscope Investig. Otolaryngol. 2019, 4, 143–153. [Google Scholar] [CrossRef] [PubMed]
  5. Pin, S.; Spini, D. Impact of falling on social participation and social support trajectories in a middle-aged and elderly European sample. SSM Popul. Health 2016, 2, 382–389. [Google Scholar] [CrossRef] [PubMed]
  6. Alatawi, S.F. A scoping review of the nature of physiotherapists’ role to avoid fall in people with Parkinsonism. Neurol. Sci. 2021, 42, 3733–3748. [Google Scholar] [CrossRef] [PubMed]
  7. Regauer, V.; Seckler, E.; Müller, M.; Bauer, P. Physical therapy interventions for older people with vertigo, dizziness and balance disorders addressing mobility and participation: A systematic review. BMC Geriatr. 2020, 20, 494. [Google Scholar] [CrossRef]
  8. Mbada, C.; Olawuyi, A.; Oyewole, O.O.; Odole, A.C.; Ogundele, A.O.; Fatoye, F. Characteristics and determinants of community physiotherapy utilization and supply. BMC Health Serv. Res. 2019, 19, 168. [Google Scholar] [CrossRef]
  9. Karinkanta, S.; Piirtola, M.; Sievänen, H.; Uusi-Rasi, K.; Kannus, P. Physical therapy approaches to reduce fall and fracture risk among older adults. Nat. Rev. Endocrinol. 2010, 6, 396–407. [Google Scholar] [CrossRef]
  10. Sherrington, C.; Michaleff, Z.A.; Fairhall, N.; Paul, S.S.; Tiedemann, A.; Whitney, J.; Cumming, R.G.; Herbert, R.D.; Close, J.C.T.; Lord, S.R. Exercise to prevent falls in older adults: An updated systematic review and meta-analysis. Br. J. Sport. Med. 2017, 51, 1750–1758. [Google Scholar] [CrossRef]
  11. Huygelier, H.; Mattheus, E.; Abeele, V.V.; van Ee, R.; Gillebert, C.R. The use of the term virtual reality in post-stroke rehabilitation: A scoping review and commentary. Psychol. Belg. 2021, 61, 145. [Google Scholar] [CrossRef]
  12. Eisapour, M.; Cao, S.; Boger, J. Participatory design and evaluation of virtual reality games to promote engagement in physical activity for people living with dementia. J. Rehabil. Assist. Technol. Eng. 2020, 7, 2055668320913770. [Google Scholar] [CrossRef]
  13. McClure, C.; Schofield, D. Running virtual: The effect of virtual reality on exercise. J. Hum. Sport Exerc. 2019, 15, 861–870. [Google Scholar] [CrossRef]
  14. Schultheis, M.; Rizzo, A. The application of virtual reality technology in rehabilitation. Rehabil. Psychol. 2001, 46, 296–311. [Google Scholar] [CrossRef]
  15. Montana, J.I.; Tuena, C.; Serino, S.; Cipresso, P.; Riva, G. Neurorehabilitation of Spatial Memory Using Virtual Environments: A Systematic Review. J. Clin. Med. 2019, 8, 1516. [Google Scholar] [CrossRef] [PubMed]
  16. De Keersmaecker, E.; Lefeber, N.; Serrien, B.; Jansen, B.; Rodriguez-Guerrero, C.; Niazi, N.; Kerckhofs, E.; Swinnen, E. The Effect of Optic Flow Speed on Active Participation During Robot-Assisted Treadmill Walking in Healthy Adults. IEEE Trans. Neural Syst. Rehabil. Eng. A Publ. IEEE Eng. Med. Biol. Soc. 2020, 28, 221–227. [Google Scholar] [CrossRef]
  17. Doná, F.; Aquino, C.C.; Gazzola, J.M.; Borges, V.; Silva, S.M.; Ganança, F.F.; Caovilla, H.H.; Ferraz, H.B. Changes in postural control in patients with Parkinson’s disease: A posturographic study. Physiotherapy 2016, 102, 272–279. [Google Scholar] [CrossRef] [PubMed]
  18. Canning, C.G.; Allen, N.E.; Nackaerts, E.; Paul, S.S.; Nieuwboer, A.; Gilat, M. Virtual reality in research and rehabilitation of gait and balance in Parkinson disease. Nat. Rev. Neurol. 2020, 16, 409–425. [Google Scholar] [CrossRef]
  19. Garcia, J.A. A Virtual Reality Game-Like Tool for Assessing the Risk of Falling in the Elderly. Stud. Health Technol. Inf. 2019, 266, 63–69. [Google Scholar] [CrossRef]
  20. Garrett, B.; Taverner, T.; Gromala, D.; Tao, G.; Cordingley, E.; Sun, C. Virtual Reality Clinical Research: Promises and Challenges. JMIR Serious Games 2018, 6, e10839. [Google Scholar] [CrossRef]
  21. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Int. J. Surg. 2021, 88, 105906. [Google Scholar] [CrossRef]
  22. Covidence. Covidence Systematic Review Software. Available online: https://www.covidence.org/ (accessed on 20 January 2023).
  23. Brosseau, L.; Laroche, C.; Sutton, A.; Guitard, P.; King, J.; Poitras, S.; Casimiro, L.; Tremblay, M.; Cardinal, D.; Cavallo, S.; et al. Une version franco-canadienne de la Physiotherapy Evidence Database (PEDro) SCale: L’Échelle PEDro. Physiother. Can. 2015, 67, 232–239. [Google Scholar] [CrossRef] [PubMed]
  24. Foley, N.C.; Teasell, R.W.; Bhogal, S.K.; Speechley, M.R. Stroke Rehabilitation Evidence-Based Review: Methodology. Top. Stroke Rehabil. 2003, 10, 1–7. [Google Scholar] [CrossRef] [PubMed]
  25. Cashin, A.G.; McAuley, J.H. Clinimetrics: Physiotherapy Evidence Database (PEDro) Scale. J. Physiother. 2020, 66, 59. [Google Scholar] [CrossRef]
  26. Centre for Evidence Based Medicine. Critical Appraisal Tools. Available online: https://www.cebm.ox.ac.uk/resources/ebm-tools/critical-appraisal-tools (accessed on 20 January 2023).
  27. Jovell, A.J.; Navarro-Rubio, M.D. [Evaluation of scientific evidence]. Med. Clin. 1995, 105, 740–743. [Google Scholar]
  28. Paré, G.; Moqadem, K.; Pineau, G.; St-Hilaire, C. Clinical effects of home telemonitoring in the context of diabetes, asthma, heart failure and hypertension: A systematic review. J. Med. Internet Res. 2010, 12, e21. [Google Scholar] [CrossRef]
  29. Cohen, J. Statistical Power Analysis for the Behavioral Sciences; Routledge: New York, NY, USA, 2013. [Google Scholar]
  30. Appel, L.; Appel, E.; Bogler, O.; Wiseman, M.; Cohen, L.; Ein, N.; Abrams, H.B.; Campos, J.L. Older Adults With Cognitive and/or Physical Impairments Can Benefit From Immersive Virtual Reality Experiences: A Feasibility Study. Front. Med. 2020, 6, 329. [Google Scholar] [CrossRef]
  31. Barsasella, D.; Liu, M.F.; Malwade, S.; Galvin, C.J.; Dhar, E.; Chang, C.-C.; Li, Y.-C.J.; Syed-Abdul, S. Effects of virtual reality sessions on the quality of life, happiness, and functional fitness among the older people: A randomized controlled trial from Taiwan. Comput. Methods Programs Biomed. 2021, 200, 105892. [Google Scholar] [CrossRef]
  32. Benham, S.; Kang, M.; Grampurohit, N. Immersive Virtual Reality for the Management of Pain in Community-Dwelling Older Adults. OTJR Occup. Particip. Health 2019, 39, 90–96. [Google Scholar] [CrossRef]
  33. Brown, J.A. An Exploration of Virtual Reality Use and Application Among Older Adult Populations. Gerontol. Geriatr. Med. 2019, 5, 2333721419885287. [Google Scholar] [CrossRef]
  34. Burin, D.; Kawashima, R. Repeated exposure to illusory sense of body ownership and agency over a moving virtual body improves executive functioning and increases prefrontal cortex activity in the elderly. Front. Hum. Neurosci. 2021, 15, 674326. [Google Scholar] [CrossRef]
  35. Campo-Prieto, P.; Rodríguez-Fuentes, G.; Cancela-Carral, J.M. Immersive virtual reality exergame promotes the practice of physical activity in older people: An opportunity during COVID-19. Multimodal Technol. Interact. 2021, 5, 52. [Google Scholar] [CrossRef]
  36. Campo-Prieto, P.; Cancela-Carral, J.M.; Rodríguez-Fuentes, G. Wearable Immersive Virtual Reality Device for Promoting Physical Activity in Parkinson’s Disease Patients. Sensors 2022, 22, 3302. [Google Scholar] [CrossRef] [PubMed]
  37. Campo-Prieto, P.; Cancela-Carral, J.M.; Alsina-Rey, B.; Rodríguez-Fuentes, G. Immersive virtual reality as a novel physical therapy approach for nonagenarians: Usability and effects on balance outcomes of a game-based exercise program. J. Clin. Med. 2022, 11, 3911. [Google Scholar] [CrossRef] [PubMed]
  38. Campo-Prieto, P.; Cancela-Carral, J.M.; Rodríguez-Fuentes, G. Feasibility and Effects of an Immersive Virtual Reality Exergame Program on Physical Functions in Institutionalized Older Adults: A Randomized Clinical Trial. Sensors 2022, 22, 6742. [Google Scholar] [CrossRef] [PubMed]
  39. Cikajlo, I.; Peterlin Potisk, K. Advantages of using 3D virtual reality based training in persons with Parkinson’s disease: A parallel study. J. Neuroeng. Rehabil. 2019, 16, 119. [Google Scholar] [CrossRef]
  40. Crosbie, J.H.; Lennon, S.; McNeill, M.D.J.; McDonough, S.M. Virtual reality in the rehabilitation of the upper limb after stroke: The user’s perspective. Cyberpsychol. Behav. Impact Internet Multimed. Virtual Real. Behav. Soc. 2006, 9, 137–141. [Google Scholar] [CrossRef]
  41. Høeg, E.R.; Bruun-Pedersen, J.R.; Cheary, S.; Andersen, L.K.; Paisa, R.; Serafin, S.; Lange, B. Buddy biking: A user study on social collaboration in a virtual reality exergame for rehabilitation. Virtual Real. 2021, 1–18. [Google Scholar] [CrossRef]
  42. Janeh, O.; Fründt, O.; Schönwald, B.; Gulberti, A.; Buhmann, C.; Gerloff, C.; Steinicke, F.; Pötter-Nerger, M. Gait Training in Virtual Reality: Short-Term Effects of Different Virtual Manipulation Techniques in Parkinson’s Disease. Cells 2019, 8, 419. [Google Scholar] [CrossRef]
  43. Thapa, N.; Park, H.J.; Yang, J.-G.; Son, H.; Jang, M.; Lee, J.; Kang, S.W.; Park, K.W.; Park, H. The effect of a virtual reality-based intervention program on cognition in older adults with mild cognitive impairment: A randomized control trial. J. Clin. Med. 2020, 9, 1283. [Google Scholar] [CrossRef]
  44. Jung, J.; Yu, J.; Kang, H. Effects of Virtual Reality Treadmill Training on Balance and Balance Self-efficacy in Stroke Patients with a History of Falling. J. Phys. Ther. Sci. 2012, 24, 1133–1136. [Google Scholar] [CrossRef]
  45. Kanyılmaz, T.; Topuz, O.; Ardıç, F.N.; Alkan, H.; Öztekin, S.N.S.; Topuz, B.; Ardıç, F. Effectiveness of conventional versus virtual reality-based vestibular rehabilitation exercises in elderly patients with dizziness: A randomized controlled study with 6-month follow-up. Braz. J. Otorhinolaryngol. 2022, 88, S41–S49. [Google Scholar] [CrossRef]
  46. Kim, A.; Darakjian, N.; Finley, J.M. Walking in fully immersive virtual environments: An evaluation of potential adverse effects in older adults and individuals with Parkinson’s disease. J. Neuroeng. Rehabil. 2017, 14, 16. [Google Scholar] [CrossRef]
  47. Kiper, P.; Przysiężna, E.; Cieślik, B.; Broniec-Siekaniec, K.; Kucińska, A.; Szczygieł, J.; Turek, K.; Gajda, R.; Szczepańska-Gieracha, J. Effects of Immersive Virtual Therapy as a Method Supporting Recovery of Depressive Symptoms in Post-Stroke Rehabilitation: Randomized Controlled Trial. Clin. Interv. Aging 2022, 17, 1673–1685. [Google Scholar] [CrossRef]
  48. Kruse, L.; Karaosmanoglu, S.; Rings, S.; Ellinger, B.; Steinicke, F. Enabling immersive exercise activities for older adults: A comparison of virtual reality exergames and traditional video exercises. Societies 2021, 11, 134. [Google Scholar] [CrossRef]
  49. Li, X.; Niksirat, K.S.; Chen, S.; Weng, D.; Sarcar, S.; Ren, X. The impact of a multitasking-based virtual reality motion video game on the cognitive and physical abilities of older adults. Sustainability 2020, 12, 9106. [Google Scholar] [CrossRef]
  50. Liepa, A.; Tang, J.; Jaundaldere, I.; Dubinina, E.; Larins, V. Feasibility randomized controlled trial of a virtual reality exergame to improve physical and cognitive functioning in older people. Acta Gymnica 2022. [Google Scholar] [CrossRef]
  51. Liu, J.; Lockhart, T.E.; Parijat, P.; McIntosh, J.D.; Chiu, Y.-P. Comparison of Slip Training in VR Environment And on Moveable Platform. Biomed. Sci. Instrum. 2015, 51, 189–197. [Google Scholar]
  52. Matamala-Gomez, M.; Slater, M.; Sanchez-Vives, M.V. Impact of virtual embodiment and exercises on functional ability and range of motion in orthopedic rehabilitation. Sci. Rep. 2022, 12, 5046. [Google Scholar] [CrossRef] [PubMed]
  53. Micarelli, A.; Viziano, A.; Micarelli, B.; Augimeri, I.; Alessandrini, M. Vestibular rehabilitation in older adults with and without mild cognitive impairment: Effects of virtual reality using a head-mounted display. Arch. Gerontol. Geriatr. 2019, 83, 246–256. [Google Scholar] [CrossRef] [PubMed]
  54. Muhla, F.; Clanché, F.; Duclos, K.; Meyer, P.; Maïaux, S.; Colnat-Coulbois, S.; Gauchard, G.C. Impact of using immersive virtual reality over time and steps in the Timed Up and Go test in elderly people. PLoS ONE 2020, 15, e0229594. [Google Scholar] [CrossRef] [PubMed]
  55. Parijat, P.; Lockhart, T. Can Virtual Reality Be Used As A Gait Training Tool For Older Adults? Proc. Hum. Factors Ergon. Soc. Annu. Meet. 2011, 55, 157–161. [Google Scholar] [CrossRef]
  56. Parijat, P.; Lockhart, T.E.; Liu, J. EMG and kinematic responses to unexpected slips after slip training in virtual reality. IEEE Trans. Bio-Med. Eng. 2015, 62, 593–599. [Google Scholar] [CrossRef] [PubMed]
  57. Phu, S.; Vogrin, S.; Al Saedi, A.; Duque, G. Balance training using virtual reality improves balance and physical performance in older adults at high risk of falls. Clin. Interv. Aging 2019, 14, 1567–1577. [Google Scholar] [CrossRef] [PubMed]
  58. Rebêlo, F.L.; de Souza Silva, L.F.; Doná, F.; Barreto, A.S.; Quintans, J.d.S.S. Immersive virtual reality is effective in the rehabilitation of older adults with balance disorders: A randomized clinical trial. Exp. Gerontol. 2021, 149, 111308. [Google Scholar] [CrossRef] [PubMed]
  59. Rutkowski, S.; Szczegielniak, J.; Szczepańska-Gieracha, J. Evaluation of the efficacy of immersive virtual reality therapy as a method supporting pulmonary rehabilitation: A randomized controlled trial. J. Clin. Med. 2021, 10, 352. [Google Scholar] [CrossRef]
  60. Sakhare, A.; Stradford, J.; Ravichandran, R.; Deng, R.; Ruiz, J.; Subramanian, K.; Suh, J.; Pa, J. Simultaneous Exercise and Cognitive Training in Virtual Reality Phase 2 Pilot Study: Impact on Brain Health and Cognition in Older Adults. Brain Plast. 2021, 7, 111–130. [Google Scholar] [CrossRef]
  61. Saldana, S.J.; Marsh, A.P.; Rejeski, W.J.; Haberl, J.K.; Wu, P.; Rosenthal, S.; Ip, E.H. Assessing balance through the use of a low-cost head-mounted display in older adults: A pilot study. Clin. Interv. Aging 2017, 12, 1363–1370. [Google Scholar] [CrossRef]
  62. Stamm, O.; Dahms, R.; Reithinger, N.; Ruß, A.; Müller-Werdan, U. Virtual reality exergame for supplementing multimodal pain therapy in older adults with chronic back pain: A randomized controlled pilot study. Virtual Real. 2022, 26, 1291–1305. [Google Scholar] [CrossRef]
  63. Stamm, O.; Vorwerg, S.; Haink, M.; Hildebrand, K.; Buchem, I. Usability and Acceptance of Exergames Using Different Types of Training among Older Hypertensive Patients in a Simulated Mixed Reality. Appl. Sci. 2022, 12, 11424. [Google Scholar] [CrossRef]
  64. Syed-Abdul, S.; Malwade, S.; Nursetyo, A.A.; Sood, M.; Bhatia, M.; Barsasella, D.; Liu, M.F.; Chang, C.-C.; Srinivasan, K.; Raja, M.; et al. Virtual reality among the elderly: A usefulness and acceptance study from Taiwan. BMC Geriatr. 2019, 19, 223. [Google Scholar] [CrossRef]
  65. Szczepańska-Gieracha, J.; Cieślik, B.; Serweta, A.; Klajs, K. Virtual therapeutic garden: A promising method supporting the treatment of depressive symptoms in late-life: A randomized pilot study. J. Clin. Med. 2021, 10, 1942. [Google Scholar] [CrossRef]
  66. Valipoor, S.; Ahrentzen, S.; Srinivasan, R.; Akiely, F.; Gopinadhan, J.; Okun, M.S.; Ramirez-Zamora, A.; Shukla, A.A.W. The use of virtual reality to modify and personalize interior home features in Parkinson’s disease. Exp. Gerontol. 2022, 159, 111702. [Google Scholar] [CrossRef] [PubMed]
  67. Vieira, E.R.; Civitella, F.; Carreno, J.; Junior, M.G.; Amorim, C.F.; D’Souza, N.; Ozer, E.; Ortega, F.; Estrázulas, J.A. Using augmented reality with older adults in the community to select design features for an age-friendly park: A pilot study. J. Aging Res. 2020, 2020, 8341034. [Google Scholar] [CrossRef]
  68. Yalfani, A.; Abedi, M.; Raeisi, Z. Effects of an 8-Week Virtual Reality Training Program on Pain, Fall Risk, and Quality of Life in Elderly Women with Chronic Low Back Pain: Double-Blind Randomized Clinical Trial. Games Health J. 2022, 11, 85–92. [Google Scholar] [CrossRef] [PubMed]
  69. Yang, J.-G.; Thapa, N.; Park, H.-J.; Bae, S.; Park, K.W.; Park, J.-H.; Park, H. Virtual Reality and Exercise Training Enhance Brain, Cognitive, and Physical Health in Older Adults with Mild Cognitive Impairment. Int. J. Environ. Res. Public Health 2022, 19, 13300. [Google Scholar] [CrossRef]
  70. Yoon, S.; Son, H. Effects of full immersion virtual reality training on balance and knee function in total knee replacement patients: A randomized controlled study. J. Mech. Med. Biol. 2020, 20, 2040007. [Google Scholar] [CrossRef]
  71. Zak, M.; Sikorski, T.; Krupnik, S.; Wasik, M.; Grzanka, K.; Courteix, D.; Dutheil, F.; Brola, W. Physiotherapy Programmes Aided by VR Solutions Applied to the Seniors Affected by Functional Capacity Impairment: Randomised Controlled Trial. Int. J. Environ. Res. Public Health 2022, 19, 6018. [Google Scholar] [CrossRef]
  72. Bank, P.J.M.; Cidota, M.A.; Ouwehand, P.E.W.; Lukosch, S.G. Patient-Tailored Augmented Reality Games for Assessing Upper Extremity Motor Impairments in Parkinson’s Disease and Stroke. J. Med. Syst. 2018, 42, 246. [Google Scholar] [CrossRef]
  73. Cerdán de Las Heras, J.; Tulppo, M.; Kiviniemi, A.; Hilberg, O.; Løkke, A.; Ekholm, S.; Catalán-Matamoros, D.; Bendstrup, E. Augmented reality glasses as a new tele-rehabilitation tool for home use: Patients’ perception and expectations. Disabil. Rehabil. Assist. Technol. 2022, 17, 480–486. [Google Scholar] [CrossRef]
  74. Chen, P.-J.; Penn, I.-W.; Wei, S.-H.; Chuang, L.-R.; Sung, W.-H. Augmented reality-assisted training with selected Tai-Chi movements improves balance control and increases lower limb muscle strength in older adults: A prospective randomized trial. J. Exerc. Sci. Fit. 2020, 18, 142–147. [Google Scholar] [CrossRef]
  75. Ferreira, S.; Marmeleira, J.; del Pozo-Cruz, J.; Bernardino, A.; Leite, N.; Brandão, M.; Raimundo, A. Acute Effects of Augmented Reality Exergames versus Cycle Ergometer on Reaction Time, Visual Attention, and Verbal Fluency in Community Older Adults. Int. J. Environ. Res. Public Health 2022, 19, 14667. [Google Scholar] [CrossRef] [PubMed]
  76. Fischer, H.C.; Stubblefield, K.; Kline, T.; Luo, X.; Kenyon, R.V.; Kamper, D.G. Hand rehabilitation following stroke: A pilot study of assisted finger extension training in a virtual environment. Top. Stroke Rehabil. 2007, 14, 1–12. [Google Scholar] [CrossRef]
  77. Jeon, S.; Kim, J. Effects of augmented-reality-based exercise on muscle parameters, physical performance, and exercise self-efficacy for older adults. Int. J. Environ. Res. Public Health 2020, 17, 3260. [Google Scholar] [CrossRef] [PubMed]
  78. Koroleva, E.S.; Tolmachev, I.V.; Alifirova, V.M.; Boiko, A.S.; Levchuk, L.A.; Loonen, A.J.; Ivanova, S.A. Serum BDNF’s role as a biomarker for motor training in the context of AR-based rehabilitation after ischemic stroke. Brain Sci. 2020, 10, 623. [Google Scholar] [CrossRef]
  79. Koroleva, E.S.; Kazakov, S.D.; Tolmachev, I.V.; Loonen, A.J.; Ivanova, S.A.; Alifirova, V.M. Clinical evaluation of different treatment strategies for motor recovery in poststroke rehabilitation during the first 90 days. J. Clin. Med. 2021, 10, 3718. [Google Scholar] [CrossRef]
  80. Muñoz, G.F.; Cardenas, R.A.M.; Pla, F. A kinect-based interactive system for home-assisted active aging. Sensors 2021, 21, 417. [Google Scholar] [CrossRef]
  81. Yoo, H.-N.; Chung, E.; Lee, B.-H. The Effects of Augmented Reality-based Otago Exercise on Balance, Gait, and Falls Efficacy of Elderly Women. J. Phys. Ther. Sci. 2013, 25, 797–801. [Google Scholar] [CrossRef]
  82. Pedroli, E.; Greci, L.; Colombo, D.; Serino, S.; Cipresso, P.; Arlati, S.; Mondellini, M.; Boilini, L.; Giussani, V.; Goulene, K.; et al. Characteristics, Usability, and Users Experience of a System Combining Cognitive and Physical Therapy in a Virtual Environment: Positive Bike. Sensors 2018, 18, 2343. [Google Scholar] [CrossRef]
  83. Biernacki, M.; Kennedy, R.; Dziuda, L. Zjawisko choroby symulatorowej oraz jej pomiar na przykładzie kwestionariusza do badania choroby symulatorowej—SSQ, [Simulator sickness and its measurement with Simulator Sickness Questionnaire (SSQ)]. Med. Pract. 2016, 67, 545–555. [Google Scholar] [CrossRef]
  84. Borg, G.A. Psychophysical bases of perceived exertion. Med. Sci. Sport. Exerc. 1982, 14, 377–381. [Google Scholar] [CrossRef]
  85. Hong, S.; Joung, D.; Lee, J.; Kim, D.-Y.; Kim, S.; Park, B.-J. The Effects of Watching a Virtual Reality (VR) Forest Video on Stress Reduction in Adults. J. People Plants Environ. 2019, 22, 309–319. [Google Scholar] [CrossRef]
  86. Tarrant, J.; Viczko, J.; Cope, H. Virtual Reality for Anxiety Reduction Demonstrated by Quantitative EEG: A Pilot Study. Front. Psychol. 2018, 9, 1280. [Google Scholar] [CrossRef] [PubMed]
  87. Kennedy, R.S.; Lane, N.E.; Berbaum, K.S.; Lilienthal, M.G. Simulator Sickness Questionnaire: An Enhanced Method for Quantifying Simulator Sickness. Int. J. Aviat. Psychol. 1993, 3, 203–220. [Google Scholar] [CrossRef]
  88. Jaeger, B.; Mourant, R. Comparison of Simulator Sickness Using Static and Dynamic Walking Simulators. Proc. Hum. Factors Ergon. Soc. Annu. Meet. 2001, 45, 1896–1900. [Google Scholar] [CrossRef]
  89. Zhao, Y.; Cutrell, E.; Holz, C.; Morris, M.R.; Ofek, E.; Wilson, A.D. SeeingVR: A set of tools to make virtual reality more accessible to people with low vision. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Scotland, UK, 4–9 May 2019; pp. 1–14. [Google Scholar]
  90. Younis, O.; Al-Nuaimy, W.; Al-Taee, M.A.; Al-Ataby, A. Augmented and virtual reality approaches to help with peripheral vision loss. In Proceedings of the 2017 14th International Multi-Conference on Systems, Signals & Devices (SSD), Mahdia, Tunisia, 20–23 February 2023; pp. 303–307. [Google Scholar]
  91. Burton, Q.; Lejeune, T.; Dehem, S.; Lebrun, N.; Ajana, K.; Edwards, M.G.; Everard, G. Performing a shortened version of the Action Research Arm Test in immersive virtual reality to assess post-stroke upper limb activity. J. NeuroEng. Rehabil. 2022, 19, 133. [Google Scholar] [CrossRef]
  92. Troy, K.L.; Grabiner, M.D. Recovery responses to surrogate slipping tasks differ from responses to actual slips. Gait Posture 2006, 24, 441–447. [Google Scholar] [CrossRef]
  93. Gold, J.I.; Belmont, K.A.; Thomas, D.A. The neurobiology of virtual reality pain attenuation. CyberPsychol. Behav. 2007, 10, 536–544. [Google Scholar] [CrossRef]
  94. Liu, Z.; Ren, L.; Xiao, C.; Zhang, K.; Demian, P. Virtual reality aided therapy towards health 4.0: A two-decade bibliometric analysis. Int. J. Environ. Res. Public Health 2022, 19, 1525. [Google Scholar] [CrossRef]
  95. Petrigna, L.; Musumeci, G. The metaverse: A new challenge for the healthcare system: A scoping review. J. Funct. Morphol. Kinesiol. 2022, 7, 63. [Google Scholar] [CrossRef]
  96. Morris, L.D.; Louw, Q.A.; Crous, L.C. Feasibility and potential effect of a low-cost virtual reality system on reducing pain and anxiety in adult burn injury patients during physiotherapy in a developing country. Burns 2010, 36, 659–664. [Google Scholar] [CrossRef] [PubMed]
  97. Barteit, S.; Lanfermann, L.; Bärnighausen, T.; Neuhann, F.; Beiersmann, C. Augmented, mixed, and virtual reality-based head-mounted devices for medical education: Systematic review. JMIR Serious Games 2021, 9, e29080. [Google Scholar] [CrossRef] [PubMed]
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