Next Article in Journal
Geochemical Modeling from the Asteroid Belt to the Kuiper Belt: Systematic Review
Previous Article in Journal
Usage-Based Motivations for Diachronic Language Change
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Virtual Reality as a Potential Cornerstone for Remote Rehabilitative Therapies

by
Raviraj Nataraj
1,2
1
Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
2
Movement Control Rehabilitation (MOCORE) Laboratory, Altorfer Complex, Stevens Institute of Technology, Hoboken, NJ 07030, USA
Encyclopedia 2026, 6(2), 37; https://doi.org/10.3390/encyclopedia6020037
Submission received: 30 November 2025 / Revised: 13 January 2026 / Accepted: 28 January 2026 / Published: 2 February 2026
(This article belongs to the Section Medicine & Pharmacology)

Abstract

Therapeutic approaches using virtual reality (VR) have been effective in recovering function against various physical and cognitive disorders. Given its programmability and precise activity tracking, VR is a powerful tool for therapists to personalize treatments and monitor their patients more effectively. Due to the growing prevalence of VR systems for personal and work uses, and the high reliability of broadband telecommunication, the opportunity to standardize remote delivery of VR therapies is apparent. VR-based rehabilitation has high potential to be a cornerstone approach for remote therapies given critical features: (1) accessibility for home users, (2) patient–therapist engagement, (3) capacity for personalization, and (4) capabilities for precision monitoring. Unlike prior reviews that summarize established measures of efficacy of VR-based rehabilitation for various clinical populations, this perspective highlights the potency of applying VR rehabilitation methods remotely and ways to expand and optimize that usage such as its integration with wearables for monitoring and AI. Moreover, this paper restricts its focus to VR as opposed to augmented (AR) or mixed-mode (MR) reality platforms that are also increasing their prevalence in clinical settings. This perspective article broadly overviews VR-based therapies for rehabilitating physical and cognitive function for various disorder cases before postulating their potential as an effective platform for delivering remote treatment. This article concludes with essential considerations for advancing VR-based remote therapy in the future.

1. Introduction

Virtual reality (VR) methods are increasingly prevalent for physical and cognitive rehabilitation [1,2,3]. In this perspective, VR refers specifically to immersive systems delivered through head-mounted displays (HMDs) such as the Meta Quest, HTC Vive, or Pico headsets, combined with controllers or motion-tracking peripherals. This is distinct from augmented reality (AR), which overlays digital content on the real world, or mixed reality (MR), which blends both. While AR and MR have therapeutic potential, immersive VR offers the highest degree of environmental control and presence, which is particularly valuable for remote rehabilitation. Virtual reality provides immersive environments [4] for therapeutic regimes that can simulate realistic interactions [5] and better engage users in physical and cognitive practices through gamification [6]. Through programmable features that allow for greater accessibility and flexibility, VR platforms are increasingly recognized as a potent tool for remote therapy [7,8,9,10,11]; however, the current scope of application is still relatively limited. Computerized interfaces like VR can serve as another “bridge” for therapists to connect to patients in real-time within a shared environment. Furthermore, virtual reality therapy can be remotely accessed using affordable, commercial equipment compatible with personal computers, smart devices, and home networks.
The growing relevance of remote therapy more broadly is driven by several converging factors, including increasing prevalence of chronic neurological and musculoskeletal conditions, aging populations with limited mobility, and rising demand for home-based care that reduces travel burden and clinic congestion [12,13]. In parallel, clinicians have increasingly adopted telehealth and telerehabilitation approaches to improve patient convenience, continuity of care, and adherence, particularly when in-person access is limited by geography, transportation, or staffing constraints [14,15]. Advances in consumer networking infrastructure, audiovisual communication platforms, and cloud-based data services have further enabled remote therapeutic interactions with levels of audio–video quality, latency, and reliability that are generally acceptable to both patients and clinicians [16,17,18]. Within this evolving care landscape, VR provides a uniquely programmable and interactive modality that can unify therapeutic delivery, real-time interaction, and performance monitoring within a single remote platform. This article provides a narrative perspective informed by targeted literature synthesis (e.g., various Google Scholar searches coupling “virtual reality” with other related terms such as “remote therapy”, “rehabilitation”, and “artificial intelligence”) and reflections from clinical engineering practice.
The effectiveness of VR as a remote therapy tool is predicated on increased dosage, greater personalization, and more effective patient monitoring. VR rehabilitative training can supplement traditional approaches, exposing patients to larger therapeutic dosages to ensure positive cognitive and physical transformations [19,20]. Both therapists and patients can conveniently and consistently schedule remote sessions to ensure regular dosing. Virtual reality has already been proven to increase participation in therapy by motivating patients to engage in longer sessions or more training repetitions using gamified constructs and realistic task environments [21,22]. Still, the potential effectiveness of virtual reality as a rehabilitation tool is further realized when it is customized or adapted to each user, i.e., personalization. Even when delivering VR therapy remotely, capabilities to personalize treatments are preserved, if not enhanced, given the onus to monitor patient safety at a distance. Furthermore, computerized environments like VR facilitate digital time-stamping and activity tracking during therapeutic sessions, allowing therapists to monitor patient progress more accurately and precisely. Such quantifiable feedback should enable therapists to understand better how patients are responding and recommend adjustments to therapeutic courses in a more timely manner.
This perspective article discusses how remote therapies can benefit from VR based on its leading feature of supporting the creation of immersive, controlled, and customizable environments in which both patient and therapist can interact. This article will first briefly summarize various rehabilitation applications, both cognitive and physical, in which virtual reality approaches have gained traction. Then, how VR benefits the delivery of remote therapy will be described based on dosage (via accessibility and engagement), personalization, and monitoring. Finally, the article concludes with considerations, i.e., limitations and potential advancements, for implementing VR therapies in the future. The primary method for engaging literature to support this perspective article included searches on Google Scholar with various topics equivalent to: (1) virtual reality for remote therapy, (2) virtual reality physical rehabilitation, (3) virtual reality cognitive rehabilitation, (4) features and advantages of virtual reality therapies, and (5) virtual reality therapy artificial intelligence. These searches emphasized peer-reviewed studies of clinical relevance, including both foundational work and recent contributions, rather than an exhaustive enumeration of all available publications. Consistent with the scope of a narrative perspective, formal systematic review procedures (e.g., PRISMA-guided study identification and screening) were not applied. Instead, the literature was synthesized qualitatively to identify recurring therapeutic features and implementation considerations that informed the conceptual model proposed in this article.
These themes of dosage, personalization, and continuous monitoring provide the foundation for VR’s unique suitability for remote therapy delivery and inform the following guiding questions:
  • How can VR increase therapeutic dosage through accessibility and engagement when delivered remotely?
  • In what ways can VR enable greater personalization of therapy, especially when integrated with wearables and physiological monitoring?
  • What forms of precision monitoring can VR provide to reduce therapist burden while ensuring patient safety and progress tracking?
  • How can VR, in combination with artificial intelligence (AI) and telehealth platforms, advance the broader ecosystem of remote care?
This article is intentionally framed as a narrative perspective rather than a systematic review or meta-analysis. The literature was engaged through targeted searches of Google Scholar using thematically grouped keywords related to virtual reality, rehabilitation, remote therapy, and enabling technologies, with emphasis on peer-reviewed studies of clinical relevance. The goal of this approach was not to exhaustively catalogue or quantitatively compare all available studies, but rather to synthesize representative evidence and emerging trends to inform a conceptual discussion of the potential of immersive VR as a platform for remote rehabilitation. Accordingly, the article prioritizes integration of findings across cognitive, physical, and mental health domains to highlight common features, opportunities, and design considerations whether used remotely or in the clinic. As with any narrative synthesis, this approach has inherent limitations, including reduced reproducibility and potential selection bias compared with formal systematic reviews. These limitations are acknowledged, and the perspective offered here is intended to complement, rather than replace, future systematic and meta-analytic evaluations of VR-based rehabilitation efficacy. Findings were synthesized qualitatively to identify recurring design features, therapeutic mechanisms, and implementation considerations across cognitive, physical, and mental health domains. While this narrative approach limits strict reproducibility of study selection, analytical rigor is maintained by organizing the synthesis around explicit conceptual pillars—therapeutic dosage via accessibility and engagement, personalization, and monitoring—which provide a consistent logical framework for interpreting prior work.

2. Virtual Reality Therapies for Cognitive and Physical Rehabilitation

VR therapy is as, if not more, effective than traditional rehabilitative methods due to greater patient satisfaction, motivation, and engagement [23,24]. Often, VR encourages more participation in therapy through gamified constructs, benefitting patients with greater dosage. Still, VR therapy can be further optimized through programmable features to increase its effectiveness per dose. Several studies (as described below) have already demonstrated significant measures for the efficacy of VR in treating disorders with either cognitive or physical foundations. Growing evidence shows how virtual reality can effectively support recovery from injuries and disorders challenging mental- and body-level function.
Recent quantitative evidence reinforces these observations. A 2024 umbrella review reported consistent improvements in upper-limb motor recovery and gait among stroke survivors completing VR-based rehabilitation, exceeding conventional therapy outcomes in several cases [25]. In musculoskeletal conditions, VR exercise significantly improves pain, quadriceps strength, and function in knee osteoarthritis [26]. A pilot RCT evaluating immersive VR-assisted lower-limb strengthening similarly found improvements in pain, mobility, and acceptability among knee osteoarthritis (OA) patients [27]. These findings demonstrate that VR’s motivational advantages translate into measurable clinical gains.
Cognitive and movement (motor) exercises within immersive VR environments have been shown to impact patients profoundly. Patients can be motivated and engaged more effectively with sensory-stimulating and gamified VR platforms compared to real-world training environments that may become monotonous. The programmability of VR platforms allows them to be re-designed and further adapted to satisfy ad hoc clinical objectives for recovering function and overcoming challenges to perform daily living activities.
Computerized interfaces like VR for rehabilitative training employ technologies whose capabilities advance substantially with each generation. Such capabilities include improved peripherals for increased responsiveness and interface control [28], more stimulating and realistic cues for greater sensations of immersion [29,30], and more accessibility based on portability, cost, and societal prevalence [31]. Virtual reality not only offers the potential to provide physical and cognitive training more effectively based on enhancing patient access and experience but also facilitates more options for precise and automated tracking of patient activity, reducing therapist onus for taking active measurements and options for additional movement training sessions to be done at home to supplement traditional therapy sessions. The following two sub-sections describe examples of research studies for VR rehabilitative therapies addressing cognitive and physical function. These prior works demonstrate the scope of impact of using VR platforms as a remote therapy tool.
Cognitive Rehabilitation: Virtual reality has been proven effective in treating anxiety [32], post-traumatic stress disorder (PTSD) [33], and mood-related conditions [34]. In each instance, VR is used to create immersive visual surroundings and soundscapes that can soothe and be combined with other techniques with similar objectives, such as meditation [35]. In more aggressive treatment approaches, virtual environments can be used for “exposure” therapy [36,37] to simulate contexts or scenarios (e.g., flying, heights, public speaking) that trigger anxious behavior. A supervising therapist can provide and monitor, even remotely, such exposures in controllable ways, allowing patients to confront and manage their fears gradually and safely.
Virtual reality has been examined for other cognitive-level therapies, such as social skills training for individuals with autism [38], addiction treatment [39], and support for cognitive impairments in conditions like Alzheimer’s disease [40]. In particular, cognitive behavioral therapy (CBT) can be administered through immersive example scenarios experienced in real-time that help patients practice coping strategies and cognitive restructuring in concurrent consultation with a therapist [41]. Real-time approaches can facilitate immediate therapist feedback, potentially reducing the need for more sessions and alleviating a patient’s burden to recall and retell their real-world experiences in practicing CBT-based strategies.
Physical Rehabilitation: Virtual reality is increasingly prevalent for physical exercising to recover function after injury or disease [42,43]. In VR, individuals are motivated to perform additional repetitions of physical practice based on gamified processes that engage through sensory-driven displays, immersive environments, and competitive constructs. VR can support neuroplasticity for improved function after neurological injuries by guiding improved performance and stimulating sensory-driven physiological processes [44,45,46]. Through its customizable environments and real-time feedback and tracking, VR-based therapies allow more robust assessments of progress from which therapists can make better decisions on personalizing treatments [47,48].
Leading features in applying VR to rehabilitate physical function are simulating task environments that encourage patients to practice ecological movements and gamification to motivate participation in more therapy [49,50]. The margins of benefit with VR motor rehabilitation over traditional approaches reduce when normalizing for dosage. However, the full potential of VR motor rehabilitation with its programmable features has yet to be realized. Motor learning principles [51] are still not standardly employed in VR regimes yet could notably increase effectiveness per dose (i.e., gains in function per training session or repetition). Such principles include multi-joint movement practices [52], error-based learning [53], and augmented sensory-driven guidance [54,55], all of which can be readily applied within computerized environments. Such considerations in improving the design of VR motor therapies would not be compromised if such therapies were delivered remotely. In addition to movement training, the capability of intensive sensory cueing has opened pathways to using VR more extensively for pain management [56]. Immersive VR experiences can distract patients from pain, providing a non-pharmacological option for pain relief in chronic and acute pain scenarios [57], varying from wound care to dental procedures. Table 1 highlights shared design elements and trends in the literature of such VR rehabilitation approaches, rather than to serve as a comprehensive systematic review.
Figure 1 depicts typical set-ups (e.g., patient position, related tools) for physical and cognitive rehabilitation done with VR at home that can be supervised remotely by a therapist. For physical rehabilitation, patients require sufficient open space to perform the targeted motor tasks, along with motion-tracking sensors in addition to the VR headset to accurately capture movements and project them into the VR environment. In contrast, cognitive rehabilitation—addressing neurological or mental health functions—is typically performed in a seated position and may rely on motion-based input, eye tracking, or audio interaction. In some cases, therapist instruction or guidance is delivered on a separate device (e.g., a computer and monitor), particularly if the VR environment itself does not support direct therapist participation or shared VR access.

3. Beneficial Features of VR as a Remote Therapy

Remote forms of therapy are a crucial advancement in modern-day care for patients seeking to recover function due to injury or disease. A primary challenge with any treatment, including virtual reality, is ensuring sufficient dosage for more effective gain in function [58,59,60,61]. Extending options for remote therapy fosters opportunities for greater dosage as persons can more flexibly receive treatment at home. Remote sessions can supplement those with traditional in-person therapy and allow the patient and therapist to more easily find mutual availability to meet. Furthermore, VR has unique features as an incredibly potent instrument for delivering therapies remotely, namely, accessibility, motivation, personalization, and precision monitoring.
Accessibility: Patients can readily receive VR therapies from their homes, which is crucial for those having challenges with mobility or commuting. Online gaming is commonplace due to high bandwidths for internet communication that ensure real-time interactions with minimal delays or stoppages [62,63]. These same high-fidelity networks can be leveraged for a therapist and a patient, or possibly multiple patients and clinicians simultaneously, to interact in guided therapy sessions.
Engagement: The immersive nature of VR increases patient engagement and adherence to therapy protocols compared to traditional methods by presenting colorful displays, rich sounds, and interactive tasking, promoting high attention [64]. Furthermore, gamifying aspects of the assigned tasks further incentivizes more training repetitions through feelings of enjoyment and stoking competitive instincts [65,66]. Most importantly, remote delivery of a VR protocol can support more engagement through communal frameworks. The lack of direct in-person interactions is an obvious limitation of a remote approach, especially for physical rehabilitation, whereby therapists cannot provide direct physical guidance for stretching and moving. Still, in VR, patients and therapists can share a common space through virtual avatars [5,67], from which patients can mirror a therapist’s movements and follow verbal cues. Furthermore, VR options for home-based therapy may inspire patients to pursue unsupervised training if it is safe and productively supplements sessions with a therapist. Cognitive-based therapies should be less affected by the lack of in-person interactions such that VR methods can sufficiently preserve traditional therapist-patient connections. Recent analyses of VR-enabled telerehabilitation emphasize the importance of sustained engagement, and interactive virtual tasks have been shown to improve adherence in older adults and neurological populations [68]. Social and immersive features—such as therapist–patient co-presence in a shared virtual environment—may further reduce barriers associated with remote care delivery.
Personalization: The programmability of computerized environments allows VR applications to be highly customized for a given rehabilitative task and to each person [69]. The user interface can include options for therapists or patients to specify training task parameters such as difficulty or level of assistance to ensure patients progressively make gains without frustration while training [70]. Incorporating wearables like smartwatches for monitoring could facilitate the next generation of personalized VR training systems that adjust parameters automatically based on a person’s active physiological responses (e.g., heart rate and electrodermal activity). Physiological responses have been demonstrated to be highly sensitive to how sensory-driven VR guidance cues are provided [45,55,71]. Integrating various devices (e.g., VR headsets, computers, smart wearables) commonly used at home for other purposes increases the viability of remote therapy in ways that ensure safer and better outcomes for each patient. Emerging VR-based rehabilitation protocols also integrate sensor-based feedback (e.g., kinematics, gait parameters, joint ROM) to individualize task difficulty. Systematic reviews show VR combined with wearable sensors enhances tailoring of exercises, particularly in gait and balance rehabilitation after stroke [72].
Precision Monitoring: Given the computerized interface with multiple sensors and controllers, VR systems readily track descriptions of patient activity in quantitative units. Motion capture cameras [73] and haptic-driven (i.e., forces, vibrations) peripherals [74] provide precise tracking of a wide array of activity markers to characterize patient activity accurately across multiple therapy sessions. Even for cognitive-based therapies, which rely less on motion- and force-based tracking, VR platforms can record verbal responses that a remote therapist can use for post-session cognitive-level behaviors [7,43,75]. VR sensing and tracking of patient activity within remote sessions can provide essential insights for therapists to adjust treatment plans. Furthermore, automated recording of patient progress allows therapists to put less effort into in-person measurements (e.g., notes) and to focus more energy on the guidance and support of the patient. Figure 2 illustrates a conceptual model of immersive VR with pillar features, including precision monitoring, as a remote-rehabilitation platform.
Comparing VR Benefits to Those of AR and MR: VR provides the highest level of immersion through fully enclosed head-mounted displays (e.g., Meta Quest, Pico, HTC Vive). This immersion allows the therapist to fully control the patient’s sensory environment and create structured, gamified tasks with consistent conditions. VR systems include built-in six-degree-of-freedom motion tracking and can integrate with wearable sensors for more detailed biomechanical and physiological measurements. VR environments have demonstrated positive effects on motor recovery, gait, pain, and functional performance across stroke, osteoarthritis, and chronic pain populations [25,26,27]. These characteristics make VR particularly suitable for remote, repeatable, and quantifiable practice at home.
Augmented reality (AR) integrates virtual elements into the user’s real environment through smartphones, tablets, or optical see-through headsets. Because AR maintains real-world visual awareness and typically uses familiar devices, it has a comparatively low barrier to adoption and may be easier for patients to incorporate into daily routines than immersive VR. A systematic review and meta-analysis found that AR-based physical therapy programs improved pain, range of motion, and functional performance compared with conventional exercise, while also enhancing motivation and engagement [76]. Additional meta-analytic evidence indicates that AR significantly improves upper- and lower-limb motor function after stroke, although many trials remain small and methodologically heterogeneous [77]. AR has also demonstrated feasibility as a remotely deployable modality, as shown in a clinical usability study of a smartphone-based AR game for upper-limb stroke rehabilitation, which reported high acceptance among both patients and clinicians [78]. Overall, AR is best suited for rehabilitation scenarios that prioritize accessibility, safety, and real-world task integration, but its lower immersion and reduced environmental control limit its ability to deliver high-intensity, repetitive motor practice compared with VR.
Mixed reality (MR) merges the real and virtual worlds, enabling patients to interact with holographic objects that are spatially anchored within their physical environment. This hybrid mode allows for more three-dimensional, spatially aware training than AR while maintaining visibility of the real world, making MR especially useful for tasks requiring coordinated functional movement. Recent clinical work has demonstrated the feasibility of MR for motor rehabilitation. A wearable MR platform using the Microsoft HoloLens enabled users to modulate their overground walking speed with visual holographic cues, showing accurate tracking without adversely affecting gait variability [79]. MR has also been integrated with wireless sensors to support rehabilitation after unilateral lower-limb amputation, improving aspects of motor recovery and demonstrating strong user acceptability in early-stage evaluations [80]. Broader reviews of augmented and mixed reality in rehabilitation emphasize MR’s potential for personalized, gamified, spatially anchored rehabilitation, while noting that most MR prototypes face challenges such as higher hardware cost, calibration demands, and limited clinical validation [81]. As a result, MR is promising for specialized clinical applications involving spatial motor planning or cognitive–motor integration, but it remains less deployable for routine home-based remote rehabilitation due to complexity and comparatively limited evidence relative to VR.
For practical reasons, immersive VR, while not yet proven to be definitively superior in functional recovery compared to AR and MR, may be particularly well aligned with scalable remote rehabilitation workflows that prioritize consistency, controllability, and ease of deployment. In the context of remote rehabilitation specifically, differences across extended reality (XR) modalities are shaped by environmental controllability and setup requirements rather than therapeutic potential alone. Immersive VR encloses the user’s sensory environment, allowing therapeutic content to be delivered in a consistent and therapist-controlled manner that is largely independent of the patient’s physical surroundings at home. By contrast, augmented reality (AR) overlays virtual elements onto the real world, making therapeutic delivery inherently dependent on individualized home environments, where background clutter, lighting conditions, and distractions may vary across sessions. Mixed reality (MR), while enabling richer interaction with real-world objects, typically requires additional setup and calibration to accurately register and synchronize physical and virtual elements, increasing system complexity in home-based settings [82,83,84].

4. Considerations for Advancing Implementation of VR Remote Therapies in the Future

Compared to traditional therapy, incorporating advanced technologies such as VR necessitates the setup of additional hardware and software required to deploy the VR approach. Hardware and software platforms for VR therapy are becoming more sophisticated, offering a wide range of therapeutic scenarios. Still, these components can take up physical space, must be additionally purchased, and require a learning and accommodation curve for therapists and patients in their usage and maintenance. Virtual reality systems and associated peripheral equipment can be expensive; however, VR systems are increasingly prevalent for multiple daily activities (e.g., gaming, movies, work meetings, and social gatherings). Several companies offer their own commercial VR system, and such broad market competition naturally reduces costs against the benefits of entertainment and productivity, thereby making customers perceive such purchases as a worthwhile investment. Another challenge with implementing new hardware and software in home or clinical environments is training patients and therapists in using and maintaining such systems. Specifically, hardware firmware and software packages require updates, and equipment must be set up and cared for at multiple locations for remote sessions. Persistent barriers include digital literacy limitations, device-setup challenges, and cyber-sickness, particularly in older adults. Remotely collected biomechanical and physiological data also introduce privacy and security concerns, which must be addressed in distributed rehabilitation workflows [85].
The VR interface must be learned at an intuitive level to maximize the therapeutic benefit by allowing the therapist and patient to focus efforts and attention on making therapeutic progress. Therapists need to understand how to manage and interpret the data generated by VR sessions as part of the broader treatment plan for each patient. Patients need to adapt to such protocols as some may initially feel uncomfortable or disoriented in a VR environment. Continual assessments by the therapist and patient will need to be made as to whether the given patient can acclimate to this approach or needs to rely only on traditional methods. Thus, gradually introducing VR protocols and more user-friendly interfaces is critical to potentially easing patients through such transitions, especially under remote conditions.
A potential solution to optimize learning curves and accommodation to VR-based interfacing with remote therapies may be artificial intelligence (AI) [86]. Integrating AI-based approaches with VR therapy can improve personalized treatment plans, real-time adjustments, and predictive analytics to anticipate therapist and patient needs [87]. Ultimately, AI methods should optimize the VR interface to reduce burdens for patients and therapists and maximize therapeutic effects. Furthermore, AI supervision of therapy sessions over remote channels could facilitate synergy with other telehealth platforms. Combining VR with other telehealth platforms monitored by AI can offer more comprehensive and personalized remote therapy solutions [88,89]. Therapists can then monitor and guide patients in real-time more optimally, despite the physical distance. Information associated with each remote therapy session, including time, duration, and progress, could be logged in cloud-based information systems that inform insurance carriers or facilitate consultation and references to other clinicians and caregivers [90,91]. AI algorithms can mine pools of de-identified data across participants to identify underlying trends that lead to recommendations for optimizing particular protocols. An example finding may be that maximizing progress for persons with a specific demographic or clinical profile is achieved when undertaking remote VR-based therapy at certain times and doses. Artificial-intelligence–enhanced rehabilitation has been proposed to support automated error detection and performance tracking, although such systems remain largely developmental. Reviews of tele-physiotherapy emphasize that sensing technologies are advancing rapidly, but integration of predictive analytics into routine VR rehabilitation has yet to be established [85].
Despite growing interest in home-based VR rehabilitation, empirical studies have reported adherence challenges and early discontinuation in certain populations, particularly among older adults and individuals with neurological impairments [92]. Prior work has identified cybersickness, cognitive fatigue, digital literacy demands, and setup complexity as common contributors to non-adherence or dropout in VR interventions, even when therapeutic tasks are well designed [93]. In home-based settings, these challenges may be amplified by reduced technical support and variability in user familiarity with immersive technologies [94]. Importantly, reported dropout or usability limitations vary widely across studies depending on population, task design, session duration, and hardware, underscoring the need for careful protocol tailoring rather than one-size-fits-all deployment [92]. These findings highlight the importance of user-centered design, gradual acclimation, and adaptive task difficulty to mitigate barriers and support sustained engagement in remote VR therapy.

5. Discussion/Conclusions

Virtual reality as a remote therapy tool holds significant promise due to its ability to create immersive, controlled, and customizable therapeutic environments. Within these virtual settings, patients and therapists can interact in ways that are safe, adaptable, and approximately equal to in-person exchanges. This flexibility is particularly valuable for various therapeutic applications, including physical rehabilitation, cognitive therapy, mental health interventions, and pain management. As VR-related technologies become more affordable and convenient, they are more likely to be adopted for therapeutic practices in rehabilitating functions impaired by various physical or cognitive diseases and injuries. Such physical and cognitive conditions may emanate from stroke, traumatic brain injury, anxiety disorders, or even neurodegenerative diseases. Therapists, even while located remotely, can guide and monitor patients to participate in exercises and activities specifically tailored to each such condition. Compared with AR and MR systems—which are less commonly deployed in home settings due to higher cost and configuration demands—immersive VR offers a more scalable pathway for remote rehabilitation. VR systems also provide richer kinematic and behavioral data than video-only telehealth, facilitating more precise monitoring of patient progress [68,72].
Furthermore, VR features of programmability and logging activity across sessions make VR-based solutions highly potent for personalizing remote therapies for better patient outcomes. Therapists can design and adjust virtual environments to suit each patient’s needs or preferences while ensuring the therapy remains sufficiently challenging to continue promoting progress. Moreover, by the computerized interface, VR systems can more effectively track such progress across multiple sessions and help identify more nuanced considerations in specifying areas of difficulty or refining the treatment plan. Opening pathways for more intelligent, data-driven approaches can accelerate convergence upon better patient outcomes.
Incorporating AI may be a key to enhancing the personalization and accommodation of patients and therapists while acting in synergy with other telehealth platforms for more comprehensive care. AI algorithms can analyze the data collected during therapy sessions to provide insights that can help therapists tailor therapies more precisely and automatically. For example, AI could employ methods that offer real-time adjustments in the therapy protocol depending on subtle patterns in a patient’s behavioral dynamics being measured that the therapist cannot readily observe. Thus, AI can accelerate the responsiveness and effectiveness of an ongoing therapeutic experience.
VR-based therapy solutions, with or without AI, have the potential to integrate seamlessly with other telehealth platforms to create a more encompassing healthcare ecosystem. By combining VR with traditional telehealth services, such as video consultations and remote monitoring, healthcare providers can offer broader approaches to patient care. Such synergies are particularly beneficial in managing chronic conditions, where ongoing support and intervention are critical for long-term success.
Despite the transformative potential for remote VR therapies, some existing challenges limit their immediate translation. While prices for VR equipment are decreasing, VR systems are not yet standardly owned compared to devices such as smartphones. Furthermore, patients and therapists require time and effort to learn and deploy the systems. Cameras for motion-tracking need to be positioned and calibrated, and the complementary software platforms must be operated to load and use the VR task environments. Furthermore, therapists need to understand how to manage and interpret the data output by VR sessions. Thus, therapists may need further training to effectively use VR tools and incorporate their results into overarching treatment plans. Of course, patients may need to acclimate to the therapies provided in VR formats. Certain patients may have a lower tolerance and feel persistently uncomfortable or disoriented. While some low-tolerance patients may be able to transition with more gradual introductions to VR or more friendly user interfaces, VR therapies may not even be an option for some patients.
In comparison to AR and MR, immersive VR remains the most advanced and clinically supported modality for remote rehabilitation due to: (1) High immersion and task controllability; (2) Strong engagement and reward mechanisms; (3) Extensive rehabilitation software ecosystems; (4) Compatibility with wearable sensors for remote monitoring; (5) Demonstrated effectiveness across stroke, osteoarthritis, and chronic pain populations. AR and MR provide valuable complementary tools, especially in settings requiring environmental awareness or spatially anchored cues, but they currently lack VR’s combination of accessibility, maturity, and evidence in home-based remote therapeutic contexts.
In conclusion, as VR technology continues to evolve and become more accessible, its role in remote therapy will likely expand, offering new opportunities for personalized, effective, and engaging therapeutic interventions. Integrating AI and telehealth platforms will only enhance these capabilities, potentially making VR an indispensable tool in the future of healthcare. Still, these conclusions should be interpreted with some caution. This article offers a narrative perspective rather than a systematic review, as there are only limited demonstrations of VR rehabilitation for remote therapies. Many such VR rehabilitation studies rely on small cohorts, short-term follow-ups, or pilot designs.

Funding

This work is funded in part by U.S. National Science Foundation CAREER award no. 2238880.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

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

Acknowledgments

The author acknowledges Sophie Dewil, Yu Shi, and Zachary Marvin, and the Schaefer School of Engineering and Science at Stevens Institute of Technology for providing support in writing this article.

Conflicts of Interest

The author declares no conflicts of interest.

References

  1. Baldominos, A.; Saez, Y.; Del Pozo, C.G. An approach to physical rehabilitation using state-of-the-art virtual reality and motion tracking technologies. Procedia Comput. Sci. 2015, 64, 10–16. [Google Scholar] [CrossRef]
  2. Faria, A.L.; Andrade, A.; Soares, L.; Bermúdez i Badia, S. Benefits of virtual reality based cognitive rehabilitation through simulated activities of daily living: A randomized controlled trial with stroke patients. J. Neuroeng. Rehabil. 2016, 13, 96. [Google Scholar] [CrossRef]
  3. Fan, T.; Wang, X.; Song, X.; Zhao, G.; Zhang, Z. Research status and emerging trends in virtual reality rehabilitation: Bibliometric and knowledge graph study. JMIR Serious Games 2023, 11, e41091. [Google Scholar] [CrossRef] [PubMed]
  4. Demeco, A.; Zola, L.; Frizziero, A.; Martini, C.; Palumbo, A.; Foresti, R.; Buccino, G.; Costantino, C. Immersive virtual reality in post-stroke rehabilitation: A systematic review. Sensors 2023, 23, 1712. [Google Scholar] [CrossRef]
  5. Rogers, S.L.; Broadbent, R.; Brown, J.; Fraser, A.; Speelman, C.P. Realistic motion avatars are the future for social interaction in virtual reality. Front. Virtual Real. 2022, 2, 750729. [Google Scholar] [CrossRef]
  6. Kern, F.; Winter, C.; Gall, D.; Käthner, I.; Pauli, P.; Latoschik, M.E. Immersive virtual reality and gamification within procedurally generated environments to increase motivation during gait rehabilitation. In Proceedings of the 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Osaka, Japan, 23–27 March 2019; IEEE: New York, NY, USA, 2019; pp. 500–509. [Google Scholar]
  7. Postolache, O.; Hemanth, D.J.; Alexandre, R.; Gupta, D.; Geman, O.; Khanna, A. Remote monitoring of physical rehabilitation of stroke patients using IoT and virtual reality. IEEE J. Sel. Areas Commun. 2020, 39, 562–573. [Google Scholar] [CrossRef]
  8. Kreimeier, J.; Schieber, H.; Lewis, N.; Smietana, M.; Reithmeier, J.; Cnejevici, V.; Prasad, P.; Eid, A.; Maier, M.; Roth, D. Towards Continuous Patient Care with Remote Guided VR-Therapy. In Proceedings of the 2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Orlando, FL, USA, 16–21 March 2024; IEEE: New York, NY, USA, 2024; pp. 959–960. [Google Scholar] [CrossRef]
  9. Vibhuti; Kumar, N.; Kataria, C. Efficacy assessment of virtual reality therapy for neuromotor rehabilitation in home environment: A systematic review. Disabil. Rehabil. Assist. Technol. 2023, 18, 1200–1220. [Google Scholar] [CrossRef]
  10. Pedram, S.; Palmisano, S.; Perez, P.; Mursic, R.; Farrelly, M. Examining the potential of virtual reality to deliver remote rehabilitation. Comput. Hum. Behav. 2020, 105, 106223. [Google Scholar] [CrossRef]
  11. McGirt, M.J.; Holland, C.M.; Farber, S.H.; Zuckerman, S.L.; Spertus, M.S.; Theodore, N.; Pfortmiller, D.; Stanley, G. Remote cognitive behavioral therapy utilizing an in-home virtual reality toolkit (Vx Therapy) reduces pain, anxiety, and depression in patients with chronic cervical and lumbar spondylytic pain: A potential alternative to opioids in multimodal pain management. N. Am. Spine Soc. J. 2023, 16, 100287. [Google Scholar]
  12. Cieza, A.; Causey, K.; Kamenov, K.; Hanson, S.W.; Chatterji, S.; Vos, T. Global estimates of the need for rehabilitation based on the Global Burden of Disease study 2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020, 396, 2006–2017. [Google Scholar] [CrossRef] [PubMed]
  13. Gimigliano, F.; Negrini, S. The World Health Organization “rehabilitation 2030: A call for action”. Eur. J. Phys. Rehabil. Med. 2017, 53, 155–168. [Google Scholar] [CrossRef]
  14. Cramer, S.C.; Dodakian, L.; Le, V.; See, J.; Augsburger, R.; McKenzie, A.; Zhou, R.J.; Chiu, N.L.; Heckhausen, J.; Cassidy, J.M. Efficacy of home-based telerehabilitation vs in-clinic therapy for adults after stroke: A randomized clinical trial. JAMA Neurol. 2019, 76, 1079–1087. [Google Scholar] [CrossRef]
  15. Kairy, D.; Lehoux, P.; Vincent, C.; Visintin, M. A systematic review of clinical outcomes, clinical process, healthcare utilization and costs associated with telerehabilitation. Disabil. Rehabil. 2009, 31, 427–447. [Google Scholar] [CrossRef]
  16. Greenhalgh, T.; Shaw, S.E.; Nishio, A.A.; Booth, A.; Byng, R.; Clarke, A.; Dakin, F.; Davies, R.; Faulkner, S.; Hemmings, N. Protocol: Remote care as the ‘new normal’? Multi-site case study in UK general practice. NIHR Open Res. 2022, 2, 46. [Google Scholar] [CrossRef] [PubMed]
  17. Kruse, C.; Heinemann, K. Facilitators and barriers to the adoption of telemedicine during the first year of COVID-19: Systematic review. J. Med. Internet Res. 2022, 24, e31752. [Google Scholar] [CrossRef]
  18. Dorsey, E.R.; Topol, E.J. State of Telehealth. N. Engl. J. Med. 2016, 375, 154–161. [Google Scholar] [CrossRef]
  19. Sveistrup, H. Motor rehabilitation using virtual reality. J. Neuroeng. Rehabil. 2004, 1, 10. [Google Scholar] [CrossRef]
  20. Grealy, M.A.; Johnson, D.A.; Rushton, S.K. Improving cognitive function after brain injury: The use of exercise and virtual reality. Arch. Phys. Med. Rehabil. 1999, 80, 661–667. [Google Scholar] [CrossRef] [PubMed]
  21. Howard, M.C. A meta-analysis and systematic literature review of virtual reality rehabilitation programs. Comput. Hum. Behav. 2017, 70, 317–327. [Google Scholar] [CrossRef]
  22. Strong, B.; Zeng, B.; McCarthy, P.; Roula, A.; Guo, L. A Framework to Design Virtual Reality Mirror Therapy (VRMT) for Motor Rehabilitation in Post-Stroke Survivors: Dosage, Motivation, Task Difficulty, Feedback and Mechanism. In Proceedings of the 2024 IEEE Gaming, Entertainment, and Media Conference (GEM), Turin, Italy, 5–7 June 2024; IEEE: New York, NY, USA, 2024; pp. 1–6. [Google Scholar] [CrossRef]
  23. 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]
  24. Monardo, G.; Pavese, C.; Giorgi, I.; Godi, M.; Colombo, R. Evaluation of Patient Motivation and Satisfaction During Technology-Assisted Rehabilitation: An Experiential Review. Games Health J. 2021, 10, 13–27. [Google Scholar] [CrossRef]
  25. Hao, J.; Crum, G.; Siu, K. Effects of virtual reality on stroke rehabilitation: An umbrella review of systematic reviews. Health Sci. Rep. 2024, 7, e70082. [Google Scholar] [CrossRef]
  26. Wei, W.; Tang, H.; Luo, Y.; Yan, S.; Ji, Q.; Liu, Z.; Li, H.; Wu, F.; Yang, S.; Yang, X. Efficacy of virtual reality exercise in knee osteoarthritis rehabilitation: A systematic review and meta-analysis. Front. Physiol. 2024, 15, 1424815. [Google Scholar] [CrossRef] [PubMed]
  27. Lo, H.H.M.; Ng, M.; Fong, P.Y.H.; Lai, H.H.K.; Wang, B.; Wong, S.Y.; Sit, R.W.S. Examining the feasibility, acceptability, and preliminary efficacy of an immersive virtual reality–assisted lower limb strength training for knee osteoarthritis: Mixed methods pilot randomized controlled trial. JMIR Serious Games 2024, 12, e52563. [Google Scholar] [CrossRef] [PubMed]
  28. De Paolis, L.T.; De Luca, V. The impact of the input interface in a virtual environment: The Vive controller and the Myo armband. Virtual Real. 2020, 24, 483–502. [Google Scholar] [CrossRef]
  29. Hillis, K. Digital Sensations: Space, Identity, and Embodiment in Virtual Reality; University of Minnesota Press: Minneapolis, MN, USA, 1999; Volume 1, Available online: https://books.google.com/books?hl=en&lr=&id=fFd1GcXoS7YC&oi=fnd&pg=PR7&dq=virtual+reality+immersion+sensations&ots=Rc7pFFoR6b&sig=dUmP1GqT3juCDv92hsJYyaNXMio (accessed on 29 June 2024).
  30. Han, P.-H.; Chen, Y.-S.; Lee, K.-C.; Wang, H.-C.; Hsieh, C.-E.; Hsiao, J.-C.; Chou, C.-H.; Hung, Y.-P. Haptic around: Multiple tactile sensations for immersive environment and interaction in virtual reality. In Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology, Tokyo, Japan, 28–30 November 2018; ACM: New York, NY, USA, 2018; pp. 1–10. [Google Scholar] [CrossRef]
  31. Ventola, C.L. Virtual reality in pharmacy: Opportunities for clinical, research, and educational applications. Pharm. Ther. 2019, 44, 267. [Google Scholar]
  32. Gorini, A.; Riva, G. Virtual reality in anxiety disorders: The past and the future. Expert Rev. Neurother. 2008, 8, 215–233. [Google Scholar] [CrossRef]
  33. Gonçalves, R.; Pedrozo, A.L.; Coutinho, E.S.F.; Figueira, I.; Ventura, P. Efficacy of virtual reality exposure therapy in the treatment of PTSD: A systematic review. PLoS ONE 2012, 7, e48469. [Google Scholar] [CrossRef]
  34. Diniz Bernardo, P.; Bains, A.; Westwood, S.; Mograbi, D.C. Mood induction using virtual reality: A systematic review of recent findings. J. Technol. Behav. Sci. 2021, 6, 3–24. [Google Scholar] [CrossRef]
  35. Kosunen, I.; Salminen, M.; Järvelä, S.; Ruonala, A.; Ravaja, N.; Jacucci, G. RelaWorld: Neuroadaptive and Immersive Virtual Reality Meditation System. In Proceedings of the 21st International Conference on Intelligent User Interfaces, Sonoma, CA, USA, 7–10 March 2016; ACM: New York, NY, USA, 2016; pp. 208–217. [Google Scholar] [CrossRef]
  36. North, M.M.; North, S.M.; Coble, J.R. Virtual reality therapy: An effective treatment for the fear of public speaking. Int. J. Virtual Real. 1998, 3, 1–6. [Google Scholar] [CrossRef]
  37. Rothbaum, B.O.; Anderson, P.; Zimand, E.; Hodges, L.; Lang, D.; Wilson, J. Virtual reality exposure therapy and standard (in vivo) exposure therapy in the treatment of fear of flying. Behav. Ther. 2006, 37, 80–90. [Google Scholar] [CrossRef]
  38. Bravou, V.; Oikonomidou, D.; Drigas, A.S. Applications of virtual reality for autism inclusion. A review. Retos Nuevas Tend. Educ. Física Deporte Recreación 2022, 45, 779–785. [Google Scholar]
  39. Mazza, M.; Kammler-Sücker, K.; Leménager, T.; Kiefer, F.; Lenz, B. Virtual reality: A powerful technology to provide novel insight into treatment mechanisms of addiction. Transl. Psychiatry 2021, 11, 617. [Google Scholar] [CrossRef]
  40. Clay, F.; Howett, D.; FitzGerald, J.; Fletcher, P.; Chan, D.; Price, A. Use of immersive virtual reality in the assessment and treatment of Alzheimer’s disease: A systematic review. J. Alzheimers Dis. 2020, 75, 23–43. [Google Scholar] [CrossRef] [PubMed]
  41. Lindner, P. Better, Virtually: The Past, Present, and Future of Virtual Reality Cognitive Behavior Therapy. Int. J. Cogn. Ther. 2021, 14, 23–46. [Google Scholar] [CrossRef]
  42. Fluet, G.G.; Deutsch, J.E. Virtual reality for sensorimotor rehabilitation post-stroke: The promise and current state of the field. Curr. Phys. Med. Rehabil. Rep. 2013, 1, 9–20. [Google Scholar] [CrossRef] [PubMed]
  43. Gomes, T.T.; Schujmann, D.S.; Fu, C. Rehabilitation through virtual reality: Physical activity of patients admitted to the intensive care unit. Rev. Bras. Ter. Intensiva 2020, 31, 456–463. [Google Scholar] [CrossRef]
  44. de Araújo, A.V.L.; de Oliveira Neiva, J.F.; de Mello Monteiro, C.B.; Magalhães, F.H. Efficacy of Virtual Reality Rehabilitation after Spinal Cord Injury: A Systematic Review. BioMed Res. Int. 2019, 2019, 7106951. [Google Scholar] [CrossRef] [PubMed]
  45. Liu, M.; Wilder, S.; Sanford, S.; Glassen, M.; Dewil, S.; Saleh, S.; Nataraj, R. Augmented feedback modes during functional grasp training with an intelligent glove and virtual reality for persons with traumatic brain injury. Front. Robot. AI 2023, 10, 1230086. [Google Scholar] [CrossRef]
  46. Cheung, K.L.; Tunik, E.; Adamovich, S.V.; Boyd, L.A. Neuroplasticity and Virtual Reality. In Virtual Reality for Physical and Motor Rehabilitation; Weiss, P.L., Keshner, E.A., Levin, M.F., Eds.; Virtual Reality Technologies for Health and Clinical Applications; Springer New York: New York, NY, USA, 2014; pp. 5–24. [Google Scholar] [CrossRef]
  47. Kritikos, J.; Alevizopoulos, G.; Koutsouris, D. Personalized virtual reality human-computer interaction for psychiatric and neurological illnesses: A dynamically adaptive virtual reality environment that changes according to real-time feedback from electrophysiological signal responses. Front. Hum. Neurosci. 2021, 15, 596980. [Google Scholar] [CrossRef]
  48. Pardini, S.; Gabrielli, S.; Dianti, M.; Novara, C.; Zucco, G.M.; Mich, O.; Forti, S. The role of personalization in the user experience, preferences and engagement with virtual reality environments for relaxation. Int. J. Environ. Res. Public. Health 2022, 19, 7237. [Google Scholar] [CrossRef]
  49. Berton, A.; Longo, U.G.; Candela, V.; Fioravanti, S.; Giannone, L.; Arcangeli, V.; Alciati, V.; Berton, C.; Facchinetti, G.; Marchetti, A. Virtual reality, augmented reality, gamification, and telerehabilitation: Psychological impact on orthopedic patients’ rehabilitation. J. Clin. Med. 2020, 9, 2567. [Google Scholar] [CrossRef]
  50. Mubin, O.; Alnajjar, F.; Jishtu, N.; Alsinglawi, B.; Al Mahmud, A. Exoskeletons with virtual reality, augmented reality, and gamification for stroke patients’ rehabilitation: Systematic review. JMIR Rehabil. Assist. Technol. 2019, 6, e12010. [Google Scholar] [CrossRef]
  51. Levin, M.F.; Weiss, P.L.; Keshner, E.A. Emergence of virtual reality as a tool for upper limb rehabilitation: Incorporation of motor control and motor learning principles. Phys. Ther. 2015, 95, 415–425. [Google Scholar] [CrossRef]
  52. Han, J.; Lian, S.; Guo, B.; Li, X.; You, A. Active rehabilitation training system for upper limb based on virtual reality. Adv. Mech. Eng. 2017, 9, 168781401774338. [Google Scholar] [CrossRef]
  53. Nataraj, R.; Sanford, S. Control Modification of Grasp Force Covaries Agency and Performance on Rigid and Compliant Surfaces. Front. Bioeng. Biotechnol. 2021, 8, 1544. [Google Scholar] [CrossRef] [PubMed]
  54. Sigrist, R.; Rauter, G.; Riener, R.; Wolf, P. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review. Psychon. Bull. Rev. 2013, 20, 21–53. [Google Scholar] [CrossRef]
  55. Sanford, S.; Collins, B.; Liu, M.; Dewil, S.; Nataraj, R. Investigating features in augmented visual feedback for virtual reality rehabilitation of upper-extremity function through isometric muscle control. Front. Virtual Real. 2022, 3, 943693. [Google Scholar] [CrossRef]
  56. Pourmand, A.; Davis, S.; Marchak, A.; Whiteside, T.; Sikka, N. Virtual reality as a clinical tool for pain management. Curr. Pain Headache Rep. 2018, 22, 53. [Google Scholar] [CrossRef]
  57. Chuan, A.; Zhou, J.J.; Hou, R.M.; Stevens, C.J.; Bogdanovych, A. Virtual reality for acute and chronic pain management in adult patients: A narrative review. Anaesthesia 2021, 76, 695–704. [Google Scholar] [CrossRef]
  58. Opriş, D.; Pintea, S.; García-Palacios, A.; Botella, C.; Szamosközi, Ş.; David, D. Virtual reality exposure therapy in anxiety disorders: A quantitative meta-analysis: Virtual Reality Exposure Therapy. Depress. Anxiety 2012, 29, 85–93. [Google Scholar] [CrossRef]
  59. Turner, W.A.; Casey, L.M. Outcomes associated with virtual reality in psychological interventions: Where are we now? Clin. Psychol. Rev. 2014, 34, 634–644. [Google Scholar] [CrossRef] [PubMed]
  60. Lohse, K.R.; Hilderman, C.G.; Cheung, K.L.; Tatla, S.; Van der Loos, H.M. Virtual reality therapy for adults post-stroke: A systematic review and meta-analysis exploring virtual environments and commercial games in therapy. PLoS ONE 2014, 9, e93318. [Google Scholar] [CrossRef]
  61. Lohse, K.R.; Lang, C.E.; Boyd, L.A. Is more better? Using metadata to explore dose–response relationships in stroke rehabilitation. Stroke 2014, 45, 2053–2058. [Google Scholar] [CrossRef]
  62. Wang, S.; Dey, S. Addressing response time and video quality in remote server based internet mobile gaming. In Proceedings of the 2010 IEEE Wireless Communication and Networking Conference, Sydney, NSW, Australia, 18–21 April 2010; IEEE: New York, NY, USA, 2010; pp. 1–6. [Google Scholar] [CrossRef]
  63. Jarschel, M.; Schlosser, D.; Scheuring, S.; Hoßfeld, T. Gaming in the clouds: QoE and the users’ perspective. Math. Comput. Model. 2013, 57, 2883–2894. [Google Scholar] [CrossRef]
  64. Zimmerli, L.; Jacky, M.; Lünenburger, L.; Riener, R.; Bolliger, M. Increasing patient engagement during virtual reality-based motor rehabilitation. Arch. Phys. Med. Rehabil. 2013, 94, 1737–1746. [Google Scholar] [CrossRef]
  65. Lyons, E.J. Cultivating Engagement and Enjoyment in Exergames Using Feedback, Challenge, and Rewards. Games Health J. 2015, 4, 12–18. [Google Scholar] [CrossRef]
  66. Radovick, S.; Hershkovitz, E.; Kalisvaart, A.; Koning, M.; Paridaens, K.; Kamel Boulos, M.N. Gamification concepts to promote and maintain therapy adherence in children with growth hormone deficiency. J 2018, 1, 71–81. [Google Scholar] [CrossRef]
  67. Emmelkamp, P.M.G.; Meyerbröker, K. Virtual Reality Therapy in Mental Health. Annu. Rev. Clin. Psychol. 2021, 17, 495–519. [Google Scholar] [CrossRef]
  68. Park, C.; Lee, B.-C. A systematic review of the effects of interactive telerehabilitation with remote monitoring and guidance on balance and gait performance in older adults and individuals with neurological conditions. Bioengineering 2024, 11, 460. [Google Scholar] [CrossRef]
  69. Baker, C.; Fairclough, S.H. Adaptive virtual reality. In Current Research in Neuroadaptive Technology; Elsevier: Amsterdam, The Netherlands, 2022; pp. 159–176. [Google Scholar] [CrossRef]
  70. Behar, C.; Lustick, M.; Foreman, M.H.; Webb, J.; Engsberg, J.R. Personalized virtual reality for upper extremity rehabilitation: Moving from the clinic to a home exercise program. J. Intellect. Disabil.-Diagn. Treat. 2016, 4, 160–169. [Google Scholar] [CrossRef]
  71. Liu, M.; Wilder, S.; Sanford, S.; Dewil, S.; Saleh, S.; Nataraj, R. EEG and Motor Effects of Multimodal Feedback to Train Functional Grasp after Traumatic Brain Injury. In Proceedings of the 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), L’Aquila, Italy, 22–24 June 2023. [Google Scholar]
  72. Caña-Pino, A.; Holgado-López, P. Wearable-Sensor and Virtual Reality-Based Interventions for Gait and Balance Rehabilitation in Stroke Survivors: A Systematic Review. Signals 2025, 6, 48. [Google Scholar] [CrossRef]
  73. Anthes, C.; García-Hernández, R.J.; Wiedemann, M.; Kranzlmüller, D. State of the art of virtual reality technology. In Proceedings of the 2016 IEEE Aerospace Conference, Big Sky, MT, USA, 5–12 March 2016; IEEE: New York, NY, USA, 2016; pp. 1–19. [Google Scholar] [CrossRef]
  74. Biswas, S.; Visell, Y. Haptic Perception, Mechanics, and Material Technologies for Virtual Reality. Adv. Funct. Mater. 2021, 31, 2008186. [Google Scholar] [CrossRef]
  75. Wiederhold, B.K.; Jang, D.P.; Kim, S.I.; Wiederhold, M.D. Physiological Monitoring as an Objective Tool in Virtual Reality Therapy. Cyberpsychol. Behav. 2002, 5, 77–82. [Google Scholar] [CrossRef] [PubMed]
  76. Gil, M.J.V.; Gonzalez-Medina, G.; Lucena-Anton, D.; Perez-Cabezas, V.; Ruiz-Molinero, M.D.C.; Martín-Valero, R. Augmented reality in physical therapy: Systematic review and meta-analysis. JMIR Serious Games 2021, 9, e30985. [Google Scholar] [CrossRef]
  77. Phan, H.L.; Le, T.H.; Lim, J.M.; Hwang, C.H.; Koo, K. Effectiveness of augmented reality in stroke rehabilitation: A meta-analysis. Appl. Sci. 2022, 12, 1848. [Google Scholar] [CrossRef]
  78. LaPiana, N.; Duong, A.; Lee, A.; Alschitz, L.; Silva, R.M.; Early, J.; Bunnell, A.; Mourad, P. Acceptability of a mobile phone–based augmented reality game for rehabilitation of patients with upper limb deficits from stroke: Case study. JMIR Rehabil. Assist. Technol. 2020, 7, e17822. [Google Scholar] [CrossRef] [PubMed]
  79. Evans, E.; Dass, M.; Muter, W.M.; Tuthill, C.; Tan, A.Q.; Trumbower, R.D. A wearable mixed reality platform to augment Overground walking: A feasibility study. Front. Hum. Neurosci. 2022, 16, 868074. [Google Scholar] [CrossRef] [PubMed]
  80. Lancere, L.; Jürgen, M.; Gapeyeva, H. Mixed reality and sensor real-time feedback to increase muscle engagement during deep core exercising. Virtual Real. 2023, 27, 3435–3449. [Google Scholar] [CrossRef]
  81. Farsi, A.; Cerone, G.L.; Falla, D.; Gazzoni, M. Emerging Applications of Augmented and Mixed Reality Technologies in Motor Rehabilitation: A Scoping Review. Sensors 2025, 25, 2042. [Google Scholar] [CrossRef]
  82. Mann, S.; Furness, T.; Yuan, Y.; Iorio, J.; Wang, Z. All Reality: Virtual, Augmented, Mixed (X), Mediated (X,Y), and Multimediated Reality. arXiv 2018. [Google Scholar] [CrossRef]
  83. Slater, M.; Sanchez-Vives, M.V. Enhancing our lives with immersive virtual reality. Front. Robot. AI 2016, 3, 74. [Google Scholar] [CrossRef]
  84. Billinghurst, M.; Clark, A.; Lee, G. A survey of augmented reality. Found. Trends® Human—Computer Interact. 2015, 8, 73–272. [Google Scholar] [CrossRef]
  85. Kakegawa, K.; Matsuda, T. Challenges and Prospects of Sensing Technology for the Promotion of Tele-Physiotherapy: A Narrative Review. Sensors 2024, 25, 16. [Google Scholar] [CrossRef] [PubMed]
  86. Ribeiro De Oliveira, T.; Biancardi Rodrigues, B.; Moura Da Silva, M.; Antonio, N.; Spinassé, R.; Giesen Ludke, G.; Ruy Soares Gaudio, M.; Iglesias Rocha Gomes, G.; Guio Cotini, L.; Da Silva Vargens, D.; et al. Virtual Reality Solutions Employing Artificial Intelligence Methods: A Systematic Literature Review. ACM Comput. Surv. 2023, 55, 214. [Google Scholar] [CrossRef]
  87. Le, D.-N.; Van Le, C.; Tromp, J.G.; Nguyen, G.N. Emerging Technologies for Health and Medicine: Virtual Reality, Augmented Reality, Artificial Intelligence, Internet of Things, Robotics, Industry 4.0; John Wiley & Sons: Hoboken, NJ, USA, 2018; Available online: https://books.google.com/books?hl=en&lr=&id=amatDwAAQBAJ&oi=fnd&pg=PR18&dq=artificial+intelligence+with+virtual+reality+for+predictive+analytics+patient+therapy&ots=HNcKUCXIwD&sig=8Z2pv8kBOkSPBKyBrmPMgHssWUU (accessed on 29 June 2024).
  88. Schork, N.J. Artificial Intelligence and Personalized Medicine. In Precision Medicine in Cancer Therapy; Von Hoff, D.D., Han, H., Eds.; Cancer Treatment and Research; Springer International Publishing: Cham, Switzerland, 2019; Volume 178, pp. 265–283. [Google Scholar] [CrossRef]
  89. Johnson, K.B.; Wei, W.; Weeraratne, D.; Frisse, M.E.; Misulis, K.; Rhee, K.; Zhao, J.; Snowdon, J.L. Precision Medicine, AI, and the Future of Personalized Health Care. Clin. Transl. Sci. 2021, 14, 86–93. [Google Scholar] [CrossRef] [PubMed]
  90. Kyriazakos, S.; Prasad, R.; Mihovska, A.; Pnevmatikakis, A.; op den Akker, H.; Hermens, H.; Barone, P.; Mamelli, A.; De Domenico, S.; Pocs, M. eWALL: An open-source cloud-based eHealth platform for creating home caring environments for older adults living with chronic diseases or frailty. Wirel. Pers. Commun. 2017, 97, 1835–1875. [Google Scholar] [CrossRef]
  91. Morland, L.A.; Poizner, J.M.; Williams, K.E.; Masino, T.T.; Thorp, S.R. Home-based clinical video teleconferencing care: Clinical considerations and future directions. Int. Rev. Psychiatry 2015, 27, 504–512. [Google Scholar] [CrossRef]
  92. Laver, K.E.; Lange, B.; George, S.; Deutsch, J.E.; Saposnik, G.; Crotty, M. Virtual reality for stroke rehabilitation. Cochrane Database Syst. Rev. 2017, 2018, CD008349. [Google Scholar] [CrossRef] [PubMed]
  93. Rebenitsch, L.; Owen, C. Review on cybersickness in applications and visual displays. Virtual Real. 2016, 20, 101–125. [Google Scholar] [CrossRef]
  94. Kairy, D.; Tousignant, M.; Leclerc, N.; Côté, A.-M.; Levasseur, M.; Researchers, T. The patient’s perspective of in-home telerehabilitation physiotherapy services following total knee arthroplasty. Int. J. Environ. Res. Public. Health 2013, 10, 3998–4011. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Illustrative depiction of set-ups for physical and cognitive rehabilitation using virtual reality (VR) under remote therapist supervision. Notable elements of both set-ups in context of therapist interactions and workflow are shown.
Figure 1. Illustrative depiction of set-ups for physical and cognitive rehabilitation using virtual reality (VR) under remote therapist supervision. Notable elements of both set-ups in context of therapist interactions and workflow are shown.
Encyclopedia 06 00037 g001
Figure 2. Conceptual model of immersive virtual reality (VR) as a remote-rehabilitation platform. Four core pillars—Accessibility, Engagement, Personalization, and Precision Monitoring—provide the technological and experiential foundation for VR-based therapy. These pillars collectively enable key rehabilitation outcomes, including increased practice intensity, greater adherence over time, tailored and adaptive training, and functional gains across motor, cognitive, or pain-related domains, thereby supporting scalable remote-rehabilitation paradigms.
Figure 2. Conceptual model of immersive virtual reality (VR) as a remote-rehabilitation platform. Four core pillars—Accessibility, Engagement, Personalization, and Precision Monitoring—provide the technological and experiential foundation for VR-based therapy. These pillars collectively enable key rehabilitation outcomes, including increased practice intensity, greater adherence over time, tailored and adaptive training, and functional gains across motor, cognitive, or pain-related domains, thereby supporting scalable remote-rehabilitation paradigms.
Encyclopedia 06 00037 g002
Table 1. Representative features of VR-based rehabilitation relevant to remote therapy.
Table 1. Representative features of VR-based rehabilitation relevant to remote therapy.
Clinical DomainRepresentative Therapeutic TasksKey Outcomes ReportedMonitoring and Feedback Features
Neurological rehabilitation (e.g., stroke, TBI, Parkinson’s disease)Upper-limb reaching and grasping, balance training, gait-related motor tasksImproved motor function, increased practice repetitions, functional recoveryMotion tracking, kinematic metrics, task performance logging, augmented sensory feedback
Cognitive rehabilitation (e.g., mild cognitive impairment, Alzheimer’s disease)Memory exercises, spatial navigation, attention and executive-function tasksImproved cognitive performance, task accuracy, engagementResponse timing, task completion metrics, behavioral logging
Mental health therapy (e.g., anxiety disorders, PTSD)Exposure therapy scenarios, stress-regulation and coping exercisesSymptom reduction, improved coping strategies, reduced avoidance behaviorsSession duration, therapist observation, optional physiological proxies
Musculoskeletal rehabilitation (e.g., orthopedic injury, osteoarthritis)Guided therapeutic exercises, range-of-motion training, strengthening tasksReduced pain, improved range of motion, increased adherenceRepetition counts, joint kinematics, progress tracking
Pain management (acute and chronic)Immersive distraction-based virtual experiencesReduced perceived pain, decreased reliance on pharmacological interventionSession timing, subjective pain reporting
Mixed cognitive–motor rehabilitationDual-task training combining motor actions with cognitive demandsImproved functional performance, dual-task ability, engagementMultimodal sensing, adaptive task difficulty, performance trend analysis
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Nataraj, R. Virtual Reality as a Potential Cornerstone for Remote Rehabilitative Therapies. Encyclopedia 2026, 6, 37. https://doi.org/10.3390/encyclopedia6020037

AMA Style

Nataraj R. Virtual Reality as a Potential Cornerstone for Remote Rehabilitative Therapies. Encyclopedia. 2026; 6(2):37. https://doi.org/10.3390/encyclopedia6020037

Chicago/Turabian Style

Nataraj, Raviraj. 2026. "Virtual Reality as a Potential Cornerstone for Remote Rehabilitative Therapies" Encyclopedia 6, no. 2: 37. https://doi.org/10.3390/encyclopedia6020037

APA Style

Nataraj, R. (2026). Virtual Reality as a Potential Cornerstone for Remote Rehabilitative Therapies. Encyclopedia, 6(2), 37. https://doi.org/10.3390/encyclopedia6020037

Article Metrics

Back to TopTop