Search Results (729)

(1) Background: Integrating assessment with training helps to enhance precision prosthetic rehabilitation of trans-radial amputees. This study aimed to validate a self-developed closed-loop rehabilitation platform combining accurate measurement in comprehensive assessment and immediate interaction in virtual reality (VR) training in refining patient-centered myoelectric prosthesis rehabilitation. (2) Methods: The platform consisted of two modules, a multimodal assessment module and an sEMG-driven VR game training module. The former included clinical scales (OPUS, DASH), task performance metrics (modified Box and Block Test), kinematics analysis (inertial sensors), and surface electromyography (sEMG) recording, verified on six trans-radial amputees and four healthy subjects. The latter aimed for muscle coordination training driven by four-channel sEMG, tested on three amputees. Post 1-week training, task performance and sEMG metrics (wrist flexion/extension activation) were re-evaluated. (3) Results: The sEMG in the residual limb of the amputees upgraded by 4.8%, either the subjects’ number of gold coins or game scores after 1-week training. Subjects uniformly agreed or strongly agreed with all the items on the user questionnaire. In reassessment after training, the average completion time (CT) of all three amputees in both tasks decreased. CTs of the A1 and A3 in the placing tasks were reduced by 49.52% and 50.61%, respectively, and the CTs for the submitting task were reduced by 19.67% and 55.44%, respectively. Average CT of all three amputees in the ADL task after training was 9.97 s, significantly lower than the pre-training time of 15.17 s. (4) Conclusions: The closed-loop platform promotes patients’ prosthesis motor-control tasks through accurate measurement and immediate interaction according to the sensorimotor recalibration principle, demonstrating a potential tool for precision rehabilitation. Full article

Background/Objective: The use of immersive virtual reality (VR) for cognitive training in older adults has shown promising results in recent years. However, the number of well-designed studies remains limited, and variability in methodologies makes it difficult to draw generalizable conclusions. This systematic review aims to examine the effects of VR-based cognitive training in older adults, describe the technological characteristics of these interventions, identify current gaps in the literature, and suggest future research directions. Methods: Following PRISMA guidelines, a search was conducted across major databases (PubMed, PsycINFO, Scopus, ProQuest, ACM, and Web of Science) from 2018 to 2025. The database search identified 156 studies, of which 12 met the inclusion criteria after screening and eligibility assessment. Across these studies, a total of 3202 older adult participants (aged 60 years or older) were included. Interventions varied in duration from 4 to 36 sessions, targeting domains such as memory, executive function, attention, and global cognition. Most interventions were based on cognitive training, with a few employing cognitive stimulation or cognitive rehabilitation approaches. Quality was assessed using the Effective Public Health Practice Project tool. Results: Most studies reported positive effects of VR interventions on cognitive domains such as attention, executive functions, and global cognition. Fewer studies showed improvements in memory. The majority used head-mounted displays connected to computers and custom-built software, often without public access. Sample sizes were generally small, and blinding procedures were often unclear. The average methodological quality was moderate. Conclusions: Immersive VR has potential as an effective tool for cognitive training in older adults. Future research should include larger randomized controlled trials, long-term follow-up, standardized intervention protocols, and the development of accessible software to enable replication and broader application in clinical and community settings. Full article

Low back pain (LBP) remains one of the most prevalent and disabling musculoskeletal conditions globally, with profound social, economic, and healthcare implications. The rising incidence and chronic nature of LBP highlight the need for more objective, personalized, and effective approaches to assessment and rehabilitation. In this context, bioengineering has emerged as a transformative field, offering novel tools and methodologies that enhance the understanding and management of LBP. This narrative review examines current bioengineering applications in both diagnostic and therapeutic domains. For assessment, technologies such as wearable inertial sensors, three-dimensional motion capture systems, surface electromyography, and biomechanical modeling provide real-time, quantitative insights into posture, movement patterns, and muscle activity. On the therapeutic front, innovations including robotic exoskeletons, neuromuscular electrical stimulation, virtual reality-based rehabilitation, and tele-rehabilitation platforms are increasingly being integrated into multimodal treatment protocols. These technologies support precision medicine by tailoring interventions to each patient’s biomechanical and functional profile. Furthermore, the incorporation of artificial intelligence into clinical workflows enables automated data analysis, predictive modeling, and decision support systems, while future directions such as digital twin technology hold promise for personalized simulation and outcome forecasting. While these advancements are promising, further validation in large-scale, real-world settings is required to ensure safety, efficacy, and equitable accessibility. Ultimately, bioengineering provides a multidimensional, data-driven framework that has the potential to significantly improve the assessment, rehabilitation, and overall management of LBP. Full article

This paper addresses the problem of recognising and classifying hand movements to control an upper-limb exoskeleton. To solve this problem, a multisensory system based on the fusion of data from electromyography (EMG) sensors, inertial measurement units (IMUs), and virtual reality (VR) trackers is proposed, which provides highly accurate detection of users’ movements. Signal preprocessing (noise filtering, segmentation, normalisation) and feature extraction were performed to generate input data for regression and classification models. Various machine learning algorithms are used to recognise motor activity, ranging from classical algorithms (logistic regression, k-nearest neighbors, decision trees) and ensemble methods (random forest, AdaBoost, eXtreme Gradient Boosting, stacking, voting) to deep neural networks, including convolutional neural networks (CNNs), gated recurrent units (GRUs), and transformers. The algorithm for integrating machine learning models into the exoskeleton control system is considered. In experiments aimed at abandoning proprietary tracking systems (VR trackers), absolute position regression was performed using data from IMU sensors with 14 regression algorithms: The random forest ensemble provided the best accuracy (mean absolute error = 0.0022 metres). The task of classifying activity categories out of nine types is considered below. Ablation analysis showed that IMU and VR trackers produce a sufficient informative minimum, while adding EMG also introduces noise, which degrades the performance of simpler models but is successfully compensated for by deep networks. In the classification task using all signals, the maximum result (99.2%) was obtained on Transformer; the fully connected neural network generated slightly worse results (98.4%). When using only IMU data, fully connected neural network, Transformer, and CNN–GRU networks provide 100% accuracy. Experimental results confirm the effectiveness of the proposed architectures for motor activity classification, as well as the use of a multi-sensor approach that allows one to compensate for the limitations of individual types of sensors. The obtained results make it possible to continue research in this direction towards the creation of control systems for upper exoskeletons, including those used in rehabilitation and virtual simulation systems. Full article

Background/Objectives: The aim of this systematic review was to compare the effectiveness of virtual reality (VR)-based training with conventional exercise programs in improving functional outcomes related to fall risk among older adults with various health conditions. Methods: The review was conducted in accordance with the PRISMA 2020 guidelines and registered in PROSPERO (registration number CRD42022345678). The databases Scopus, PubMed, Web of Science, and EBSCO were searched up to 31 March 2025. Randomized controlled trials (RCTs) were included if they involved participants aged ≥60 years, a VR intervention lasting ≥6 weeks, and a control group performing traditional exercises or receiving usual care. Methodological quality was assessed using the PEDro scale, and a narrative synthesis was performed across four outcome domains: balance, mobility, cognitive function, and fall risk. Results: Seven RCTs were included in the analysis (totaling 664 participants). VR training was found to be at least as effective as conventional exercise in improving balance (e.g., Berg Balance Scale) and mobility (e.g., Timed Up and Go), with some studies showing superior effects of VR. One RCT demonstrated that combining VR with balance exercises (MIX) yielded the greatest improvements in muscle strength and physical performance. Additionally, two studies reported cognitive benefits (e.g., MoCA) and a 42% reduction in fall incidence within six months following VR intervention. The methodological quality of the included studies was moderate to high (PEDro score 5–9/10). Conclusions: VR-based training represents a safe and engaging supplement to geriatric rehabilitation, effectively improving balance, mobility, and, in selected cases, cognitive function, while also reducing fall risk. Full article

Background: Reverse total shoulder arthroplasty (RTSA) is increasingly used for managing cuff tear arthropathy, osteoarthritis, complex fractures, and revision procedures. As the demand for surgical precision and reproducibility grows, immersive technologies such as virtual reality (VR), augmented reality (AR), and metaverse-based platforms are being explored for surgical training, intraoperative guidance, and rehabilitation. While early data suggest potential benefits, a focused synthesis specific to RTSA is lacking. Methods: This systematic review was conducted in accordance with PRISMA 2020 guidelines. A comprehensive search of PubMed, Scopus, and Cochrane Library databases was performed through 30 May 2025. Eligible studies included those evaluating immersive technologies in the context of RTSA for skill acquisition or intraoperative guidance. Only peer-reviewed articles published in English were included. Data were synthesized narratively due to heterogeneity in study design and outcome metrics. Results: Out of 628 records screened, 21 studies met the inclusion criteria. Five studies evaluated immersive VR for surgical training: four randomized controlled trials and one retrospective case series. VR training improved procedural efficiency and showed non-inferiority to cadaveric training. Sixteen studies investigated intraoperative navigation or AR guidance. Clinical and cadaveric studies consistently reported improved accuracy in glenoid baseplate positioning with reduced angular and linear deviations in postoperative controls as compared to preoperative planning. Conclusions: Immersive technologies show promise in enhancing training, intraoperative accuracy, and procedural consistency in RTSA. VR and AR platforms may support standardized surgical education and precision-based practice, but their broad clinical impact remains limited by small sample sizes, heterogeneous methodologies, and limited long-term outcomes. Further multicenter trials with standardized endpoints and cost-effectiveness analyses are warranted. Postoperative rehabilitation using immersive technologies in RTSA remains underexplored and presents an opportunity for future research. Full article

Burn injuries result in complex physiological and psychological sequelae, including hypermetabolism, muscle wasting, mobility impairment, scarring, and disrupted body image. While advances in acute care have improved survival, comprehensive rehabilitation strategies are critical for restoring function, appearance, and psychosocial well-being. Structured physical activity, including resistance and aerobic training, plays a central role in counteracting muscle atrophy, improving cardiovascular function, enhancing scar quality, and promoting psychological resilience and body image restoration. This narrative review synthesizes the current evidence on the effects of exercise-based interventions on post-burn recovery, highlighting their therapeutic mechanisms, clinical applications, and implementation challenges. In addition to physical training, emerging technologies such as virtual reality, aquatic therapy, and compression garments offer promising adjunctive benefits. Notably, artificial intelligence (AI) is gaining traction in burn rehabilitation through its integration into wearable biosensors and telehealth platforms that enable real-time monitoring, individualized feedback, and predictive modeling of recovery outcomes. These AI-driven tools have the potential to personalize exercise regimens, support remote care, and enhance scar assessment and wound tracking. Overall, the integration of exercise-based interventions with digital technologies represents a promising, multimodal approach to burn recovery. Future research should focus on optimizing exercise prescriptions, improving access to personalized rehabilitation tools, and advancing AI-enabled systems to support long-term recovery, functional independence, and positive self-perception among burn survivors. Full article

This study presents a systematic review regarding the use of augmented reality and virtual reality in exergaming by analyzing studies published during 2010–2025. This study focuses on providing an overview of the field and on examining and synthesizing the findings of related studies to identify the contexts, applications, and domains in which extended reality exergames are being used and the related implications, benefits, and challenges. Based on the results, augmented reality and virtual reality exergames offer immersive, enjoyable, engaging, and personalized experiences that support physical, cognitive, and emotional well-being, while enhancing physical performance, cognitive functioning, psychological outcomes, and mental health. They promote motivation, active lifestyles, and sustainable health behaviors across diverse populations, including older adults, individuals with disabilities, and neurological groups, as well as the general adult and youth populations. Although emphasis is placed on their use in physical and cognitive rehabilitation and treatment, they also show great potential to be effectively used in different domains, including education. Among the technologies examined, the significant majority of studies focused on virtual reality exergames, a limited number of studies involved augmented reality, and only a few studies examined mixed reality, extended reality, and the metaverse. Finally, nine main topics were identified through topic modeling, providing a clear representation of the core themes within the literature. Full article

Stroke often leads to severe motor impairment, especially in the upper limbs, greatly reducing a patient’s ability to perform daily tasks. Effective rehabilitation is essential to restore function and improve quality of life. Traditional therapies, while useful, may lack engagement, leading to low motivation and poor adherence. Gamification—using game-like elements in non-game contexts—offers a promising way to make rehabilitation more engaging. The authors explore a gamified rehabilitation system designed in Unity 3D using a Kinect V2 camera. The game includes key features such as adjustable difficulty, real-time and predominantly positive feedback, user friendliness, and data tracking for progress. The evaluations were conducted with 18 healthy participants, most of whom had prior virtual reality experience. About 77% found the application highly motivating. While the gameplay was well received, the visual design was noted as lacking engagement. Importantly, all users agreed that the game offers a broad range of difficulty levels, making it accessible to various users. The results suggest that the system has strong potential to improve rehabilitation outcomes and encourage long-term use through enhanced motivation and interactivity. Full article

Background and Clinical Significance: The retreatment of failed dental implants remains a challenging clinical scenario, particularly when complicated by peri-implantitis and as sociated bone loss. Successful management requires a comprehensive and predictable approach that addresses both hard and soft tissue deficiencies. Case Presentation: This case report illustrates a fully digital, prosthetically driven workflow for the rehabilitation of a posterior mandibular site following implant failure. A 44-year-old female patient underwent removal of a failing implant and adjacent tooth due to advanced peri-implantitis and periodontitis. After healing, a digital workflow—including intraoral scanning, cone-beam computed tomography (CBCT), and virtual planning—was employed to design and fabricate a customized CAD/CAM titanium mesh for vertical guided bone regeneration. The grafting procedure utilized a composite mixture of autogenous bone and anorganic bovine bone (A-Oss). After nine months of healing, two implants with a hydrophilic surface (SOI) were placed using a fully guided surgical protocol (OneGuide system). Subsequent soft tissue grafting and final prosthetic rehabilitation with monolithic zirconia restorations resulted in stable functional and aesthetic outcomes. Conclusions: This case highlights how the integration of modern digital technologies with advanced regenerative procedures and innovative implant surfaces can enhance the predictability and long-term success of implant retreatment in compromised posterior sites. Full article

Digital transformation is reshaping the healthcare field by streamlining diagnostic workflows and improving disease management. Within this transformation, Digital Twins (DTs), which are virtual representations of physical systems continuously updated by real-world data, stand out for their ability to capture the complexity of human physiology and behavior. When coupled with Artificial Intelligence (AI), DTs enable data-driven experimentation, precise diagnostic support, and predictive modeling without posing direct risks to patients. However, their integration into healthcare requires careful consideration of ethical, regulatory, and safety constraints in light of the sensitivity and nonlinear nature of human data. In this review, we examine recent progress in DTs over the past seven years and explore broader trends in AI-augmented DTs, focusing particularly on movement rehabilitation. Our goal is to provide a comprehensive understanding of how DTs bolstered by AI can transform healthcare delivery, medical research, and personalized care. We discuss implementation challenges such as data privacy, clinical validation, and scalability along with opportunities for more efficient, safe, and patient-centered healthcare systems. By addressing these issues, this review highlights key insights and directions for future research to guide the proactive and ethical adoption of DTs in healthcare. Full article

This in vitro study aims to compare the trueness of digital impressions obtained using two intraoral scanners (IOS) and one photogrammetry device for full-arch implant-supported rehabilitations. According to the Caramês Classification I, three models were produced with Straumann implants arranged in different spatial distributions: Option A with six implants and Options B and C with four implants each. The three models were scanned using a 12-megapixel scanner to create digital master casts. For each reference model, 30 digital impressions were acquired: 10 with the 3Shape Trios 3 intraoral scanner, 10 with the Medit i500 intraoral scanner, and 10 with the PIC Dental photogrammetry device. Trueness was assessed through best-fit superimpositions between the digital master casts and the corresponding virtual models. The Shapiro–Wilk test was applied to assess the normality of the data distribution, and Levene’s test was used to evaluate the homogeneity of variances. The non-parametric Kruskal–Wallis test was employed to compare group differences, with post hoc adjustments made using the Bonferroni correction. A significance threshold of p = 0.05 was adopted for all statistical tests. Statistically significant differences were observed in the root mean square values among the three devices. The Medit i500 demonstrated the highest trueness, with a median (interquartile range) deviation of 24.45 (18.18) µm, whereas the PIC Dental exhibited the lowest trueness, with a median deviation of 49.45 (9.17) µm. Among the implant distribution, the Option C showed the best trueness, with a median deviation of 19.00 (27.83). Considering the results of this in vitro study, intraoral scanners demonstrated comparable trueness, whereas the photogrammetry-based system exhibited lower trueness values. Additionally, a smaller number of implants and reduced inter-implant distances were associated with improved trueness in digital impressions for full-arch implant rehabilitation. Full article

Extended reality (XR)-based rehabilitation is an emerging therapeutic approach that combines real and virtual environments to enhance patient engagement and promote motor and cognitive recovery. Its clinical utility in children with cerebral palsy (CP), particularly regarding gross motor skills, balance, and psychosocial well-being, remains underexplored. This preliminary study aimed to evaluate the potential effects of XR-based rehabilitation on gross motor function, balance, parental stress, and quality of life in children with cerebral palsy. Thirty children with cerebral palsy were randomly assigned to an extended reality training group (XRT, n = 15) or a conventional physical therapy group (CPT, n = 15). Both groups received 30 min sessions, three times per week for 6 weeks. Outcome measures included the Gross Motor Function Measure-88 (GMFM-88), Pediatric Balance Scale (PBS), Functional Independence Measure (FIM), Parenting Stress Index (PSI), and Pediatric Quality of Life Inventory (PedsQL), assessed pre- and post-intervention. A 2 (group) × 2 (time) mixed ANOVA was conducted. The XR group demonstrated improvements in GMFM-88, PBS, and FIM scores, with decreased PSI and increased PedsQL scores. Although most interaction effects were not statistically significant (GMFM-88: η² = 0.035, p = 0.329; PBS: η² = 0.043, p = 0.274), a marginal interaction effect was observed for PSI (p = 0.065, η² = 0.059), suggesting a potential benefit of XR-based rehabilitation in reducing parental stress. This preliminary study indicates that XR-based rehabilitation may provide beneficial trends in motor function and psychosocial health in children with CP, particularly in reducing parental stress. Further studies with larger sample sizes are needed to confirm these findings. Full article

Background. Digital dentistry continues to evolve, offering improved accuracy, efficiency, and patient experience across various prosthodontic procedures. Many previous reviews have focused on digital applications in prosthodontics. But the use of a fully digital workflow for full-arch implant-supported prostheses in edentulous patients remains an emerging and underexplored area in the literature. Objective. This article presents a comprehensive methodological review of the digital workflow in full-arch implant-supported rehabilitation. It follows a structured literature exploration and synthesizes relevant technological processes from patient assessment to prosthetic delivery. Methods. The relevant literature was retrieved from the PubMed database on 20 June 2024, to identify the most recent and relevant studies. A total of 22 articles met the eligibility criteria and were included in the review. The majority included case and technical reports. Results. The review illustrates the integration and application of digital tools in implant dentistry, including cone-beam computed tomography (CBCT) exposure, intraoral scanning, digital smile design, virtual patients, guided surgery, and digital scanning. The key findings demonstrate multiple advantages of a fully digital workflow, such as reduced treatment time and cost, increased patient satisfaction, and improved interdisciplinary communication. Conclusions. Despite these benefits, limitations persist due to the low level of evidence, technological challenges, and the lack of standardized protocols. Further randomized controlled trials and long-term clinical evaluations are essential to validate the effectiveness and feasibility of a fully digital workflow for full-arch implant-supported rehabilitation. Full article

Sexual dysfunction is a prevalent and often under-addressed concern among prostate cancer survivors, significantly affecting quality of life for patients and their partners. The True North Sexual Health and Rehabilitation eClinic (SHAReClinic) is a virtual, biopsychosocial intervention developed to improve access to sexual health support for prostate cancer survivors and their partners. This study used a qualitative descriptive design to examine barriers and facilitators influencing the integration of SHAReClinic into oncology care across nine Canadian health care centres. Semi-structured interviews were conducted with 17 knowledge users, including health care providers and institutional leaders. Data were analyzed using a hybrid deductive–inductive thematic approach guided by the Consolidated Framework for Implementation Research (CFIR) 2.0. Participants described SHAReClinic as a much-needed resource, particularly in the absence of standardized sexual health pathways in oncology care. The virtual format was seen as accessible and well suited to addressing sensitive topics. However, limited funding, lack of institutional support, and workflow integration challenges emerged as primary barriers to implementation. Findings offer practical, theory-informed guidance for integrating SHAReClinic into oncology care and highlight key considerations for developing sustainable and scalable survivorship care models. Full article