Research Status and Emerging Trends in Virtual Reality Rehabilitation: Bibliometric and Knowledge Graph Study

Effectiveness of Immersive Virtual Reality-Based Hand Rehabilitation Games for Improving Hand Motor Functions in Subacute Stroke Patients

Stroke rehabilitation faces challenges in attaining enduring improvements in hand motor function and is frequently constrained by interventional limitations. This research aims to present an innovative approach to the integration of cognitive engagement within visual feedback incorporated into fully immersive virtual reality (VR) based games to achieve enduring improvements. These innovative aspects of interaction provide more functional advantages beyond motivation to efficiently execute repeatedly hand motor tasks. The effectiveness of virtual reality games incorporated with innovative aspects has been investigated for improvements in hand motor functions. A randomized controlled trial was conducted, a total of (n=56) subacute stroke patients were assessed for eligibility and (n=52) patients fulfilled the inclusion criteria. (n=26) patients were assigned to the experimental group and (n=26) patients were assigned to the control group. VR intervention involves four VR based games, developed based on hand movements including flexion/extension, close/open, supination/pronation and pinch. All patients got therapy of 24 sessions, lasting 4 days/week for a total of 6 weeks. Five clinical outcome measures were Fugl- Meyer Assessment-Upper Extremity, Action Research Arm Test, Box and Block Test, Modified Barthel Index, and Stroke-Specific Quality of Life were assessed to evaluate patients' performance. Results revealed that after therapy there was significant improvement between the groups (p<0.05) and within groups (p<0.05) in all assessment weeks in all clinical outcome measures however, improvement was observed significantly greater in the experimental group due to fully immersive VR-based games. Results indicated that cognitive engagement within visual feedback incorporated in VR-based hand games effectively improved hand motor functions.

An exploration of knowledge-organizing technologies to advance transdisciplinary back pain research

Chronic low back pain (LBP) is influenced by a broad spectrum of patient-specific factors as codified in domains of the biopsychosocial model (BSM). Operationalizing the BSM into research and clinical care is challenging because most investigators work in silos that concentrate on only one or two BSM domains. Furthermore, the expanding, multidisciplinary nature of BSM research creates practical limitations as to how individual investigators integrate current data into their processes of generating impactful hypotheses. The rapidly advancing field of artificial intelligence (AI) is providing new tools for organizing knowledge, but the practical aspects for how AI may advance LBP research and clinical are beginning to be explored. The goals of the work presented here are to: (1) explore the current capabilities of knowledge integration technologies (large language models (LLM), similarity graphs (SGs), and knowledge graphs (KGs)) to synthesize biomedical literature and depict multimodal relationships reflected in the BSM, and; (2) highlight limitations, implementation details, and future areas of research to improve performance. We demonstrate preliminary evidence that LLMs, like GPT-3, may be useful in helping scientists analyze and distinguish cLBP publications across multiple BSM domains and determine the degree to which the literature supports or contradicts emergent hypotheses. We show that SG representations and KGs enable exploring LBP's literature in novel ways, possibly providing, trans-disciplinary perspectives or insights that are currently difficult, if not infeasible to achieve. The SG approach is automated, simple, and inexpensive to execute, and thereby may be useful for early-phase literature and narrative explorations beyond one's areas of expertise. Likewise, we show that KGs can be constructed using automated pipelines, queried to provide semantic information, and analyzed to explore trans-domain linkages. The examples presented support the feasibility for LBP-tailored AI protocols to organize knowledge and support developing and refining trans-domain hypotheses.

Limitations and solutions of low cost virtual reality mirror therapy for post-stroke patients

Mirror therapy is applied to reduce phantom pain and as a rehabilitation technique in post-stroke patients. Using Virtual Reality and head-mounted displays this therapy can be performed in virtual scenarios. However, for its efficient use in clinical settings, some hardware limitations need to be solved. A new system to perform mirror therapy in virtual scenarios for post-stroke patients is proposed. The system requires the patient a standalone virtual reality headset with hand-tracking features and for the rehabilitator an external computer or tablet device. The system provides functionalities for the rehabilitator to prepare and follow-up rehabilitation sessions and a virtual scenario for the patient to perform rehabilitation. The system has been tested on a real scenario with the support of three experienced rehabilitators and considering ten post-stroke patients in individual sessions focused on upper limb motor rehabilitation. The development team observed all the sessions and took note of detected errors regarding technological aspects. Solutions to solve detected problems will be proposed and evaluated in terms of feasibility, performance cost, additional system cost, number of solved issues, new limitations, or advantages for the patient. Three types of errors were detected and solved. The first error is related to the position of the hands relative to the head-mounted display. To solve it the exercise area can be limited to avoid objectives that require turning the head too far. The second error is related to the interaction between the hands and the virtual objects. It can be solved making the main hand non-interactive. The last type of error is due to patient limitations and can be mitigated by having a virtual hand play out an example motion to bring the patient's attention back to the exercise. Other solutions have been evaluated positively and can be used in addition or instead of the selected ones. For mirror therapy based on virtual reality to be efficient in post-stroke rehabilitation the current head-mounted display-based solutions need to be complemented with specific strategies that avoid or mitigate the limitations of the technology and the patient. Solutions that help with the most common issues have been proposed.