Search Results (153)

Robot-assisted telerehabilitation (RAT) combines rehabilitation robotics with digital health workflows to extend access to upper-limb (UL) therapy after stroke. Mixed reality (MR) may support therapist–patient interaction and task visualization; however, early-stage systems require rigorous evaluation of safety and usability before deployment in the home. In a formative, mixed-methods usability study conducted in a controlled setting using a telerehabilitation workflow, six individuals post-stroke (≥3 months) and six occupational therapists (OTs) completed a single supervised session with a desktop-mounted end-effector type therapeutic robot (iTbot) integrated with Microsoft HoloLens 2. Participants performed structured passive and active UL exercises while therapists supervised and interacted with the system via the MR control interfaces. Safety was evaluated by documenting observed adverse events and safety-stop activations. Usability and user experience were assessed using the System Usability Scale (SUS), study-specific satisfaction questionnaires (reported with scale ranges), and semi-structured follow-up interviews analyzed using thematic analysis. All participants completed the session without observed adverse events or safety-stop activations. Overall usability was favorable, with a mean (SD) SUS total score of 78.3 (15.9) out of 100 (stroke: 74.2 [18.1]; occupational therapists: 82.5 [13.5]). Qualitative feedback indicated that MR was perceived as engaging and intuitive by many users, while also identifying implementation needs relevant to real-world telerehabilitation, including clearer onboarding, simplification of certain MR interactions, and improved physical interfaces (e.g., handle options). Therapists highlighted workflow considerations for remote supervision and patient independence. Together, these findings support progression to multi-session, in-home studies to quantify remote assistance needs, technical reliability, adherence, and clinical outcomes. Full article

Background and Objectives: Breast cancer remains the most frequently diagnosed malignancy among women worldwide. As survival rates continue to improve, rehabilitation interventions focusing on functional recovery and quality of life have become increasingly important. Emerging technologies such as virtual reality, augmented reality, and telerehabilitation have recently been integrated into physiotherapy programs. This systematic review aimed to evaluate the effectiveness of technology-assisted physiotherapy interventions on quality of life, psychological outcomes, and functional recovery in women with breast cancer. Materials and Methods: A systematic search was conducted in PubMed, CINAHL Complete, and MEDLINE Complete for randomized controlled trials published between January 2010 and March 2026. Studies were included if they investigated exercise-based physiotherapy interventions incorporating technological modalities such as virtual reality, augmented reality, mixed reality, robotics, or telerehabilitation. Outcomes included quality of life, fatigue, pain, upper limb function, and psychological health. Results: Six randomized controlled trials involving approximately 398 participants (mean age range: 30–60 years) were included in the qualitative synthesis. The studies included women across different stages of the disease trajectory, including postoperative patients and long-term survivors. Interventions comprised virtual reality-based exercise programs, Kinect-based mixed reality systems, augmented reality telerehabilitation platforms, and internet-based rehabilitation programs. Across studies, significant improvements were consistently observed within groups in outcomes such as quality of life, upper limb function, pain reduction, and shoulder range of motion (e.g., p < 0.001). However, between-group differences were not consistently statistically significant, with several studies reporting comparable improvements in both intervention and control groups. Conclusions: Technology-assisted physiotherapy interventions may support functional recovery and improve quality of life among women with breast cancer. However, the available evidence remains limited, with important methodological constraints, as improvements were predominantly observed within groups, while consistent between-group differences were not demonstrated. Therefore, the comparative effectiveness of these interventions over standard rehabilitation remains inconclusive, highlighting the need for further high-quality randomized controlled trials. Full article

Background: Technology such as telerehabilitation, virtual reality, robotics, and wearable systems are reshaping pediatric physiotherapy. While evidence remains fragmented, there is little guidance on how these approaches can be integrated into coherent, family-centered care pathways. Objective: To develop the Digital Pediatric Physiotherapy Framework (DPPF) based on a systematic review of randomized evidence on digital interventions in pediatric physiotherapy. Methods: Several databases were searched for randomized trials published after 1 January 2020, including PubMed, Web of Science Core Collection, and Google Scholar. The included studies assessed the results of physiotherapist-delivered or physiotherapist-supervised digital interventions in children and adolescents aged 18 and younger. Population, intervention, outcome, implementation, and safety data were extracted. Considering the substantial heterogeneity of the findings, they were synthesized narratively. Cochrane RoB 2 was used to assess risk of bias, and GRADE was used to evaluate certainty of evidence. Results: Twenty-nine trials involving 1196 participants were included. Most studies examined virtual reality and gaming-based interventions, with fewer evaluating telerehabilitation/tele-exercise and robotic or wearable technologies. Digital interventions were most often directed at body-function and activity-level outcomes, while participation outcomes were less frequently studied. The strongest evidence supported short-term benefits in balance, gross motor function, upper-limb activity, pain, and selected fitness outcomes, particularly in children with cerebral palsy. Evidence for telerehabilitation and robotic or wearable approaches was more limited but generally promising. Implementation, equity, cost, and long-term outcomes were rarely reported. No eligible trial directly evaluated electronic patient-reported outcome measures, digital triage, or clinical decision support as stand-alone interventions. Conclusions: Digital interventions have the potential to strengthen pediatric physiotherapy, particularly for short-term motor and functional outcomes. The proposed DPPF provides an implementation-informed structure to guide future research, pathway design, and more purposeful integration of digital health into pediatric rehabilitation practice. Full article

Background/Objectives: Telerehabilitation expands access to specialized neuropediatric physiotherapy for families facing barriers related to geography, work, or caregiving. This systematic review aimed to summarize the evidence regarding the effects of telerehabilitation on gross motor function (GMF) in children with cerebral palsy (CP). Methods: An electronic search was conducted in the following databases: PubMed, Web of Science, Embase, and the Cochrane Library; Google Scholar was consulted for additional literature. The search targeted randomized and non-randomized intervention studies evaluating the effects of telerehabilitation on GMF in children with CP at various levels of the Gross Motor Function Classification System (GMFCS), as well as related functional outcomes. The risk of bias in the included studies was assessed using the original Cochrane Collaboration risk of bias tool. The certainty of evidence was graded according to the GRADE framework. Results: Five studies involving 152 children were included, with CP aged 2.5 to 17 years. Telerehabilitation programs varied in duration, frequency, and type of intervention, as well as in caregiver involvement, comparator conditions, and outcome measures. The included studies suggested potential benefits in GMF and related functional outcomes; however, findings were heterogeneous, and superiority over comparison conditions was not consistently demonstrated. Conclusions: Although the reviewed studies suggest that telerehabilitation may be a feasible and potentially beneficial approach for children with CP, the limited number of studies and variability of interventions highlight the need for caution in interpreting these findings. Further high-quality studies with standardized outcome reporting are needed to clarify its contribution to GMF. Full article

Portugal’s demographic ageing calls for effective strategies to address mild cognitive impairment (MCI) and Alzheimer’s Disease (AD). However, fragmented evidence on digital tools limits their clinical application. This review aimed to map the landscape of validated digital cognitive rehabilitation platforms in Portugal for older adults with MCI and AD and to analyze their effectiveness, usability, and implementation barriers. Following PRISMA 2020 guidelines, seven studies published between 2015 and 2025 were identified from PubMed, Scopus, and ScienceDirect, complemented by manual searches and platform website analysis. Methodological quality, assessed using the Joanna Briggs Institute (JBI) tools, ranged from 69% to 100%. The included studies evaluated platforms such as the Systemic Lisbon Battery (SLB), Digi&Mind, NeuroVRehab.PT, and the Fit4Alz project. Findings indicate improvements in global cognition, executive functioning, and attention. Multimodal interventions combining digital cognitive training and physical exercise produced more consistent cognitive benefits than isolated approaches. Despite initially low digital literacy among older adults, high adherence and motivation were reported, supported by gamification, user-centred design, and cultural adaptation. Although Portuguese digital platforms show strong potential for cognitive rehabilitation, the evidence base is constrained by methodological heterogeneity, small sample sizes, and short intervention durations. Future research should prioritize long-term follow-up and remote monitoring through telerehabilitation. Full article

Background/Objectives: Stroke is a leading cause of mortality and disability in Saudi Arabia; however, national estimates of stroke-related rehabilitation needs remain limited. This study quantified temporal trends in stroke incidence, prevalence, premature mortality, and disability from 1990 to 2021. It also examined disparities in stroke-related disability by subtype, sex, and age in 2021 and projected rehabilitation demand to 2030 to inform health system planning under Vision 2030. Methods: We conducted a secondary analysis of Global Burden of Disease (GBD) 2021 estimates for Saudi Arabia. Age-standardized rates for incidence, prevalence, years of life lost (YLLs), and years lived with disability (YLDs) were extracted for overall stroke and three subtypes: ischemic stroke, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). Temporal trends were evaluated using log-linear regression to estimate the average annual percentage change (AAPC). YLDs were mapped to severity levels and four rehabilitation modalities, physiotherapy (PT), occupational therapy (OT), speech–language therapy (SLT), and multidisciplinary comprehensive rehabilitation (MCR), using utilization probabilities informed by the literature. Projections to 2030 incorporated national population forecasts and included 95% prediction intervals and sensitivity analyses. Results: From 1990 to 2021, age-standardized stroke incidence declined from 166.3 to 130.7 per 100,000 (−21.4%; AAPC, −0.86%, p = 0.004), prevalence from 982.4 to 965.2 per 100,000 (−1.8%; AAPC, −0.10%, p = 0.056), and YLL rates from 3209.0 to 1893.4 per 100,000 (−41.0%; AAPC, −1.76%, p < 0.001). In contrast, YLD rates declined modestly from 133.5 to 129.9 per 100,000 (−2.7%; AAPC, −0.13%; p = 0.032). Despite these reductions in age-standardized rates, absolute stroke-related YLDs more than tripled, increasing from approximately 10,900 (95% UI: 8100–13,900) in 1990 to 36,245 (95% UI: 26,600–46,100) in 2021, largely driven by population growth and aging. In 2021, ischemic stroke accounted for 71.1% of total YLDs, followed by ICH (20.3%) and SAH (8.5%). Among adults aged 15–49 years, females had higher hemorrhagic YLD rates than males, with particularly pronounced differences for SAH (female-to-male ratio, 1.5–1.7). By 2030, the projected YLD-equivalent workload, a standardized proxy measure of relative service demand rather than a direct headcount of required therapists, is expected to increase to 29,758 for PT, 21,809 for OT, 14,879 for SLT, and 15,083 for MCR. Sensitivity analyses showed that rehabilitation demand estimates were sensitive to assumptions regarding severity distribution, with a hemorrhagic-weighted scenario increasing projected MCR demand by 6.8%. Conclusions: The increasing absolute burden of stroke-related disability in Saudi Arabia, despite declining age-standardized rates and substantial reductions in premature mortality, highlights the necessity to expand rehabilitation capacity. Scaling community-based, outpatient, and telerehabilitation services in alignment with the Health Sector Transformation Program and integrating disability-informed planning into Vision 2030 should be prioritized. Full article

Cardiac telerehabilitation has become a promising alternative to traditional programmes for preventing acute coronary syndrome (ACS) in the secondary phase. However, current implementations are still reactive and standardised, lacking personalisation and flexibility in clinical settings. By integrating artificial intelligence (AI), it may be possible to overcome these limitations and provide intelligent, scalable, and patient-centred care. Methods: We conducted a structured literature review across PubMed, Scopus, the Cochrane Library, and Web of Science, targeting English-language studies published from January 2015 to May 2025. Inclusion criteria included adult populations with a history of ACS or high cardiovascular risk, assessing interventions based on AI, telerehabilitation, or their combination. Studies are needed to report clinical, functional, behavioural, or technological outcomes. A thematic narrative synthesis was utilised. Results: AI-enhanced telerehabilitation demonstrates potential advantages over conventional digital care in selected domains, including adaptive risk prediction, personalised exercise modulation, and adherence support. Several systems report real-time adjustment of exercise protocols, early dropout detection, and predictive analytics for rehospitalisation. AI integration may also contribute to personalised behavioural feedback and psychosocial monitoring. Nevertheless, the overall level of evidence remains preliminary and heterogeneous, with most AI-based interventions evaluated in pilot, feasibility, or modelling studies rather than large-scale randomized trials. Conclusions: The integration of AI into telerehabilitation represents a promising evolution in post-ACS care, shifting from predominantly reactive monitoring toward more adaptive and data-driven support models. While early-phase studies suggest feasibility and potential clinical benefit, robust multicentre randomized controlled trials and cost-effectiveness analyses are required before definitive conclusions regarding superiority or widespread implementation can be drawn. Full article

Home based telerehabilitation has expanded after COVID-19, but delivering timely guidance and monitoring exercise performance outside the clinic remains difficult. Traditional physiotherapy often relies on repeated execution of simple routines, yet clinicians have limited visibility into adherence and movement quality during unsupervised sessions. From a systems perspective, many telerehabilitation approaches also face constraints in accessibility, bandwidth, and computational cost that can limit practical deployment. This paper presents a modular telerehabilitation framework and prototype that captures and records rehabilitation exercise sessions for asynchronous clinician review in a 3D visualisation environment. The system integrates skeletal motion capture with plantar pressure sensing, and stores sessions as portable artefacts to support replay, inspection, and downstream analysis. A connector-based architecture enables extension to additional sensors without redesigning the core application, and the design aims to support deployment under constrained home computing and networking conditions. The manuscript contributes an implementation blueprint and reference architecture for multimodal capture and replay. Clinical effectiveness, usability outcomes, and quantitative sensor accuracy benchmarking are outside the scope of this work and are identified as necessary future evaluation. Full article

Musculoskeletal disorders such as rheumatoid arthritis and osteoarthritis affect millions worldwide and are projected to rise sharply by 2050, highlighting the importance of scalable telerehabilitation. This paper introduces Rehabi, a mobile, user-friendly tele-rehabilitation platform that centrally integrates markerless motion for biomechanical assessment and monitoring. Rehabi development followed a user-centered methodology, combining questionnaires, interviews, and natural language processing to elicit requirements from patients and clinicians. The system architecture was implemented in accordance with Clean Architecture principles to ensure modularity and scalability. In a pilot clinical validation of the markerless motion algorithm integrated into Rehabi, 14 post-arthroplasty patients showed moderate agreement for hip flexion (ICC = 0.686) and good agreement for knee flexion (ICC = 0.801). Although the sample was small, the results show a promising trend suggesting that mobile markerless motion capture may be a viable option for remote assessment and monitoring. Full article

Background/Objective: Post-COVID survivors present significant respiratory deficiency that has been associated with ongoing shortness of breath and impaired lung function. Inspiratory muscle training (IMT) is increasingly used in survivors of COVID-19 rehabilitational programs as a means to facilitate recovery of the respiratory system. Yet, its home-based effectiveness across clinically relevant outcomes remains unclear. This systematic review aimed to present current evidence on home- or tele-delivered IMT in the post-COVID-19 population. Methods: PubMed, Scopus, Cochrane library and Science Direct were systematically searched for studies evaluating home-based (or telerehabilitation) IMT, alone or as part of a respiratory muscle training program, in adults with post-COVID-19 symptoms. The primary outcome was inspiratory muscle strength. Secondary outcomes included dyspnea, pulmonary function, exercise capacity and health-related quality of life. The methodological quality of the included studies was assessed via the PEDro scale. Owing to clinical and methodological heterogeneity, we performed only a qualitative synthesis. Results: Eight studies met the inclusion criteria. Two included both inspiratory and expiratory muscles training and three included physical training as well. The methodological quality was found to be good. IMT consistently increased inspiratory muscle strength across trials. Respiratory muscle training (RMT) programs that combined inspiratory and expiratory training also improved maximal expiratory pressure. IMT reduced dyspnea versus control/sham or baseline and several studies reported improvements in exercise capacity and physical function. Spirometry/DLCO changes were small or null in most cohorts. HRQoL gains were domain-specific in anxiety and depression. Adherence was generally good. No serious adverse events attributable to IMT were reported. Conclusions: Home-based IMT for adults with post-COVID-19 conditions is safe and seems to improve inspiratory muscle strength and dyspnea, with signs of benefit for exercise capacity, physical function, and selected HRQoL domains. Effects on ventilatory efficiency and conventional lung function appear limited. Future multicenter, sham-controlled RCTs should further explore the characteristics of IMT, employ core outcome sets, include longer follow-up, and predefine phenotype-based subgroups. Full article

Population ageing and chronic disease are increasing demand for rehabilitation, while resources remain limited. This review does not report an implemented end-to-end system; instead, it proposes a modular workflow framework for applying large AI foundation models across rehabilitation. Organised into four stages—assessment, prescription, execution, and monitoring—we summarise recent evidence and highlight techniques most suitable at each stage. In assessment, multimodal models can enable more continuous and objective functional measurement from heterogeneous sensor and imaging data. In prescription, large language models can support evidence-informed, personalised plan formulation by synthesising guidelines and patient context. In execution, vision–language–sensor models can provide real-time feedback for telerehabilitation and adherence support. In monitoring, longitudinal and cross-setting data integration can facilitate risk prediction and early warning for safety and long-term management. We also discuss practical adaptation options (e.g., parameter-efficient fine-tuning) and propose a clinimetric-oriented evaluation framework to assess validity, reliability, and generalisability. By mapping AI capabilities to concrete workflow tasks, the framework provides a theoretical foundation and roadmap for reproducible research and future translation toward a universal rehabilitation model. Full article

Artificial intelligence (AI), virtual reality (VR), gamification, and telerehabilitation are increasingly incorporated into neurorehabilitation to deliver adaptive, personalized, and remotely accessible interventions for individuals with stroke and other neurological disorders. These technologies aim to address key limitations in conventional rehabilitation by enhancing training intensity, patient engagement, accessibility, and real-time monitoring. This systematic review synthesizes evidence from clinical and simulation-based studies evaluating AI-assisted systems, non-AI gamified platforms, VR/exergames, telerehabilitation models, and simulation-driven architectures across neurological populations. A comprehensive search of PubMed, Scopus, Embase, CINAHL, and Web of Science (2010–2025) identified randomized controlled trials, pilot and quasi-experimental studies, telerehabilitation systems, VR/exergame interventions, AI-based adaptive tools, and computational or model-driven investigations, guided by a revised PICO framework. Data were extracted using a standardized template, with studies categorized by design, population, technological modality, and outcome domain. Risk of bias was assessed using validated tools, and GRADE was applied to stroke-specific clinical outcomes. Twenty-two studies met the inclusion criteria, encompassing both clinical trials and simulation/modeling research. Clinical studies reported improvements in motor function, balance, gait, swallowing, cognition, and psychosocial well-being, often accompanied by high usability and adherence. AI-enabled systems facilitated adaptive difficulty adjustment, automated feedback, and individualized progression, while non-AI platforms demonstrated strong engagement and meaningful functional gains. Simulation studies provided valuable insights into algorithm behavior, sensor-based modeling, and system optimization. Despite promising multi-domain benefits, methodological heterogeneity, limited long-term follow-up, and inconsistent AI transparency remain key challenges, underscoring the need for standardized outcomes, explainable AI, inclusive design, and robust multicenter trials. Full article

Background: Attention Deficit Hyperactivity Disorder (ADHD) is associated with executive function deficits—such as planning, organization, and prospective memory—that impair autonomy and daily functioning, increase family stress, and create challenges in educational contexts. These consequences underscore the need for accessible and ecologically valid interventions addressing the cognitive, familial, and educational dimensions. Traditional approaches often lack ecological validity, and pharmacological treatment shows a limited impact on functional cognition. Objectives: This protocol outlines a feasibility study of DiverAcción, a web-based telerehabilitation system designed to enhance functional cognition through interactive and gamified tasks integrated into a comprehensive healthcare programme. Methods: A quasi-experimental feasibility study before and after the study will recruit 30 participants aged 9 to 17 years with ADHD. The study comprises an initial face-to-face session for instructions and baseline assessment (T0), followed by twelve supervised online sessions over six weeks. Therapeutic support is provided via integrated chat, email, and two scheduled videoconference check-ins. Feasibility Outcomes: include recruitment, adherence, retention, usability (SUS), acceptability (TAM), satisfaction, user-friendly design, therapeutic alliance (WAI-I), and professionals’ attitudes toward technology (e-TAP-T). Exploratory Measures: include parental self-efficacy (BPSES), parenting stress (PSI-4-SF), ADHD symptomatology (SNAP-IV), executive functioning (BRIEF-2), time management (Time-S), emotional regulation (ERQ-CA), prospective memory (PRMQ-C), and health-related quality of life (KIDSCREEN-52). Analyses emphasize descriptive statistics for feasibility metrics (recruitment, adherence, retention, dropout and fidelity). Assessments are conducted post-intervention (T1) and at three-month follow-up (T2) and analyzed relative to baseline using repeated-measures ANOVA or Friedman tests, depending on data distribution. Conclusions: This feasibility protocol will provide preliminary evidence on the usability, acceptability, and implementation of DiverAcción. Findings will guide refinements and inform the design of a subsequent randomized controlled trial. Full article

Stroke continues to impose an enormous morbidity and mortality burden worldwide. Stroke survivors often incur debilitating consequences that impair motor function, independence in activities of daily living and quality of life. Rehabilitation is a pivotal intervention to minimize disability and promote functional recovery following a stroke. The Internet of Medical Things, a network of connected medical devices, software and health systems that collect, store and analyze health data over the internet, is an emerging resource in neurorehabilitation for stroke survivors. Technologies such as asynchronous transmission to handle intermittent connectivity, edge computing to conserve bandwidth and lengthen device life, functional interoperability across platforms, security mechanisms scalable to resource constraints, and hybrid architectures that combine local processing with cloud synchronization help bridge the digital divide and infrastructure limitations in low-resource environments. This manuscript reviews emerging rehabilitation technologies such as robotic devices, virtual reality, brain–computer interfaces and telerehabilitation in the setting of neurorehabilitation for stroke patients. Full article

Experiencing weakness or paralysis on one side of the body is a common consequence of stroke, with approximately 8 out of 10 patients experiencing some degree of Hemiparesis. Rehabilitation through physiotherapy and occupational therapy is one of the primary methods used to alleviate these conditions. However, physiotherapy, provided by a therapist, is not always readily available. Rehabilitation robots have been studied as alternatives and supplements to conventional therapy. These robots, based on their interaction with the user, can be categorized as end-effector and exoskeleton-based robots. This work aims to examine end-effector rehabilitation robots targeting hemiplegic arm’s proximal joints (shoulder and elbow) for post-stroke recovery. Additionally, we analyze their mechanical design, training modes, user interfaces, and clinical outcomes, highlighting trends and gaps in these systems. Furthermore, we suggest design considerations for home-based therapy and future integration with tele-rehabilitation, based on our findings. This review uniquely focuses on end-effector robots for proximal joints, synthesizing design trends and clinical evidence to guide future development. Full article