Search Results (216)

Urban navigation in dynamic environments remains a challenging problem for blind and visually impaired users due to the presence of unpredictable obstacles and the limitations of conventional navigation systems, which rely primarily on static map-based information and lack real-time environmental awareness. This paper presents a real-time sensor-driven navigation system based on a multi-agent architecture incorporating a reinforcement-learning navigation policy for assistive mobility in urban environments. The proposed system integrates GPS-based global localization with vision-based perception to enable continuous fusion of global route planning and local obstacle detection. This integration allows the system to dynamically adjust navigation strategies in response to changing environmental conditions. The architecture is designed as a modular multi-agent system comprising agents for perception, navigation, sensor fusion, personalization, safety arbitration, interface management, and system monitoring. The reinforcement learning component formulates local navigation as a sequential decision-making problem, where the navigation policy is trained to balance path efficiency, obstacle avoidance, and safety constraints through interaction with simulated environments. Prototype implementation is developed and evaluated in both simulation and controlled real-world scenarios. Experimental results demonstrate that the proposed system shows improved obstacle avoidance performance and navigation stability under the evaluated conditions while maintaining low-latency responsiveness compared to baseline navigation approaches. The system also exhibits robust behaviour under varying environmental conditions, supporting its potential applicability to assistive navigation tasks in controlled urban environments. The proposed approach contributes to a scalable architecture that integrates a reinforcement-learning navigation policy within a multi-agent coordination framework and real-time sensor perception, providing a foundation for the development of intelligent and deployable assistive navigation systems. Full article

Background and Objectives: This research aimed to compare Type D personality characteristics and self-esteem between individuals with chronic NSLBP and healthy controls, while also exploring their relationships with functional status, psychological symptoms, and quality of life within the patient group. Materials and Methods: In this cross-sectional investigation, 34 patients with chronic NSLBP were compared with 34 healthy controls with similar age and sex distribution. Pain intensity was quantified via the Visual Analog Scale (VAS), while functional impairment was evaluated using the Oswestry Disability Index (ODI). Psychological profiling included the Type D Scale-14 (DS14) for personality traits, the Rosenberg Self-Esteem Scale (RSES) for self-worth, and the Hospital Anxiety and Depression Scale (HADS) for emotional distress. Health-related quality of life was captured through the 12-Item Short Form Health Survey (SF-12). Results: Type D personality was significantly more prevalent in the NSLBP group than in controls (50% vs. 20.6%, p = 0.011). Patients with NSLBP had significantly higher negative affectivity (NA) scores (p < 0.001) and anxiety scores (p = 0.007) and lower SF-12 Physical Component Summary scores (p < 0.001) than controls. Pain intensity and disability were positively correlated with Type D personality traits, particularly NA and the Type D composite score. In exploratory subgroup analyses, patients with Type D personality also had higher pain intensity, disability, anxiety, and depression scores and lower SF-12 Mental Component Summary (MCS) scores than those without Type D personality. In adjusted regression analyses within the NSLBP group, Type D personality was associated with higher VAS (p = 0.004) and ODI scores (p = 0.007) and lower SF-12 MCS scores (p = 0.003). Conclusions: Type D personality characteristics were more frequent in patients with chronic NSLBP than in healthy controls and were associated with higher pain intensity, greater disability, higher anxiety and depressive symptom scores, and poorer mental quality-of-life scores within the patient group. In contrast, self-esteem did not differ significantly between patients and controls. Due to the inherent constraints of a cross-sectional framework and the potential construct redundancy between NA and emotional distress, the current results signify correlational links rather than definitive causality. Consequently, subsequent prospective research is vital to delineate the temporal dynamics and the long-term predictive value of Type D personality traits in the progression of chronic NSLBP. Full article

Background/Objectives: Diabetic retinopathy (DR) is a major microvascular complication of type 1 diabetes mellitus (T1DM) and remains an important cause of preventable visual impairment. Region-specific data on the incidence and clinical predictors of DR among patients with T1DM in Saudi Arabia remain limited. This study aimed to determine the incidence of DR and identify associated demographic and systemic risk factors among patients with T1DM at a tertiary care center in Riyadh, Saudi Arabia. Methods: This retrospective cohort study included 449 patients with T1DM aged ≥9 years who were followed at King Abdulaziz Medical City, Riyadh, between 2015 and 2025. Patients were selected using a consecutive non-probability sampling technique. Data were extracted from the BESTCare 2.0A electronic medical record system and supplemented, when required, by phone-based interviews to verify selected clinical and demographic variables. Patients were classified as controls without DR or cases with DR, including non-vision-threatening DR and vision-threatening DR (VTDR), according to the International Clinical Diabetic Retinopathy Severity Scale. Multivariable logistic regression, Cox proportional hazards models, and temporal trend analysis were performed, with statistical significance set at p < 0.05. Results: The overall incidence rate of DR was 92.66 per 1000 person-years, with similar rates among males and females. In multivariable logistic regression, older age at T1DM diagnosis, longer diabetes duration, hypertension, hyperlipidemia, and albuminuria were independently associated with DR. Mean HbA1c and HbA1c variability were not independently associated with DR after adjustment. In Cox regression, older age at T1DM diagnosis was associated with higher hazards of both DR and VTDR, while hypertension was associated with VTDR. Among patients with DR, younger age at T1DM diagnosis was associated with higher odds of proliferative disease in exploratory severity analysis. Conclusions: DR was common among patients with T1DM in this tertiary-care cohort and was mainly associated with disease duration, age at diagnosis, and systemic vascular comorbidities. These findings support the importance of routine ophthalmologic screening and integrated management of systemic risk factors in patients with T1DM. Full article

This case report documents the multi-season development of a 38-year-old elite F12 shot putter with macular degeneration (<10% functional vision) who improved from 13.00 m to a personal best of 14.41 m between 2021 and 2023. Athletes classified as F11–F13 compete with significant visual impairment that limits spatial feedback during rotational tasks, yet longitudinal evidence describing integrated training frameworks remains scarce. A 12-month macrocycle integrated phase-dependent velocity-based resistance training using mean concentric velocity targets (0.70–1.00 m·s⁻¹) monitored via linear position transducers with a 10% velocity loss threshold, combined with structured auditory and tactile cueing, including metronome pacing and environmental anchors. High-volume warm-ups and prehabilitation addressed a prior L4–L5 disk herniation. The athlete achieved 14.41 m at the 2023 U.S. Para Athletics Trials, with TrackMan^®-verified release velocity of 11.3 m·s⁻¹. Bench throw velocity improved by 35.4% (0.65 to 0.88 m·s⁻¹) and squat jump velocity improved by 22.9% (1.18 to 1.45 m·s⁻¹), while post-session RPE remained manageable, indicating improved neuromuscular readiness and training tolerance. No lumbar symptom recurrence occurred. This case illustrates that integrating velocity autoregulation, multisensory stabilization, and injury-informed preparation can support meaningful performance gains in visually impaired throwers and offers an applied framework for coaches working with F11–F13 athletes. Full article

Background: This study examines how medical consumption is discussed in online communities among individuals who are blind or visually impaired using the Social Ecological Model (SEM) to capture multilevel healthcare experiences within digital discourse. Methods: A total of 428 posts and comments were collected from Reddit’s r/Blind community. Term frequency–inverse document frequency keyword extraction and a theory-driven LLM-based classification approach were applied to categorize texts into five SEM levels: intrapersonal, interpersonal, institutional, community, and public policy. Results: The findings show that intrapersonal (44.4%) and public policy (29.8%) levels were the most prominent, indicating a strong emphasis on personal coping experiences alongside structural constraints in healthcare access. Institutional-level discourse accounted for 15.8%, whereas interpersonal (6.2%) and community (3.8%) discourse were relatively limited. Keywords and qualitative analyses revealed themes related to emotional adaptation, social support, service accessibility, mobility constraints, and welfare policy barriers. The Jaccard similarity analysis indicated stronger associations between institutional and policy levels, whereas community-level discourse remained relatively distinct. Conclusions: These findings highlight the importance of understanding healthcare experiences, both individually and structurally, in online environments. This study also demonstrated the potential of integrating LLM-based classification with theory-driven frameworks to enable an interpretable and scalable analysis of complex health-related discourse. Full article

Neurological injuries and disorders affecting hand motor control can severely impair the ability to perform activities of daily living and substantially reduce quality of life. Technologies such as virtual reality (VR) are increasingly used to address fundamental challenges in therapy, including motivation and engagement; further, programmable features of digital interfaces offer additional opportunities to personalize and optimize motor training. In this proof-of-concept study, we developed and evaluated a novel VR-based training framework to support improved dexterity and hand function using physiological (sensory-driven) and cognitive (memory) cues designed to promote greater task-relevant neural engagement. The proposed approach leverages the integration of augmented sensory feedback (ASF) with memory-anchored cues for motor learning of target hand gestures. Using a within-subjects design, thirteen neurotypical adults completed four training conditions: (1) control (baseline gesture-matching in VR), (2) visual ASF (enhanced visualization and feedback of gesture accuracy), (3) memory-anchored cues (associating gestures with semantically meaningful entities, loosely analogous to American Sign Language), and (4) hybrid multimodal (visual ASF + memory-anchored cues). Training with the hybrid condition produced the fastest skill acquisition (9.3 trials to reach an 80% accuracy threshold) and the steepest initial learning slope (1.86 ± 0.12%/trial), with all conditions differing significantly in initial slope (all p < 0.002). Post-training assessment showed that the hybrid condition achieved the highest gesture accuracy (95.2%), greatest normalized post-training accuracy gain (14.3% above baseline), fastest execution time to target gesture (1.14 s), and lowest variability in gestural kinematics (SD = 3.9%). Both ASF and memory-anchored cue conditions each also independently outperformed the control condition on gesture accuracy (both p ≤ 0.002), with omnibus ANOVAs indicating significant condition effects across metrics. Together, these findings suggest that pairing ASF cues with memory-based cognitive scaffolding can yield additive benefits for motor skill acquisition and stability. Pending validation in clinical populations, such approaches may inform the design of VR-based motor training frameworks for rehabilitation. Full article

Diabetic retinopathy (DR) is a leading cause of vision loss worldwide and represents a complex neurovascular complication of diabetes mellitus driven by chronic hyperglycemia. Increasing evidence identifies oxidative stress—defined as an imbalance between reactive oxygen species (ROS) production and antioxidant defenses—as a central pathogenic mechanism linking metabolic dysregulation to retinal injury. The retina is particularly vulnerable to oxidative damage due to its high metabolic demand, elevated oxygen consumption, and abundance of polyunsaturated fatty acids. Hyperglycemia activates multiple interconnected biochemical pathways, including the polyol and hexosamine pathways, protein kinase C signaling, advanced glycation end-product formation, and lipid peroxidation, all of which converge on excessive ROS production and mitochondrial dysfunction. Growing attention has focused on oxidative stress biomarkers as tools to characterize DR severity and progression. Elevated systemic markers of lipid, protein, and DNA oxidation, together with impaired antioxidant capacity, correlate with disease stage, while oxidative biomarkers detected in aqueous and vitreous humor reflect localized retinal injury. Importantly, oxidative stress biomarkers are also associated with functional outcomes, including best-corrected visual acuity and diabetic macular edema. Integration of systemic and ocular oxidative biomarkers with clinical staging may improve risk stratification and support personalized therapeutic strategies in DR. Full article

Automated video-based detection of cognitive disorders can enable a scalable non-invasive health monitoring. However, existing methods focus on a single disease and provide limited interpretability, whereas real-world videos often contain co-occurring conditions. We propose a novel unified multi-task method to detect depression and Parkinson’s disease (PD) from in-the-wild video data called DEPART (DEpression and PArkinson’s Recognition Technique). It performs body region extraction, Contrastive Language-Image Pre-training (CLIP)-based visual encoding, Transformer-based temporal modeling, and prototype-aware classification with a gated fusion technique. Gradient-based attention maps are used to visualize task-specific regions that drive predictions. Experiments on the In-the-Wild Speech Medical (WSM) corpus demonstrate competitive performance: the multi-task model achieves Recall of 82.39% for depression and 78.20% for PD, compared with 87.76% and 78.20%, for the best single-task models. The multi-task learning initially increases false positives for healthy persons in the PD subset, mainly due to annotation–modality mismatches, static visual content misinterpreted as motor impairments, and occasional body detection failures. After cleaning the test data, Recall for healthy individuals becomes comparable across models; the multi-task model improves Recall for both depression (from 82.39% to 87.50%) and PD (from 78.20% to 86.14%), suggesting better robustness for real-life clinical applications. Full article

Retinal vein occlusion (RVO) is the second most common retinal vascular disorder after diabetic retinopathy and represents a major cause of visual impairment worldwide. In addition to venous congestion, endothelial dysfunction, and inflammation, accumulating evidence indicates that oxidative stress plays a pivotal role in the pathogenesis of RVO. The excessive production of reactive oxygen species (ROS) during ischemia–reperfusion injury induces endothelial damage, disruption of the blood–retinal barrier, and upregulation of inflammatory cytokines and vascular endothelial growth factor (VEGF), thereby contributing to macular edema and progressive visual dysfunction. This review summarizes current knowledge from both experimental and clinical studies regarding the mechanisms of oxidative stress generation in RVO and its underlying molecular pathways, highlighting the pathological consequences of impaired antioxidant defense systems. We further review reported alterations in oxidative stress markers and antioxidant factors in serum, aqueous humor, and vitreous fluid, and discuss their potential associations with disease activity and visual prognosis. In addition, the interplay between oxidative stress and current standard treatments, including anti-VEGF therapy and corticosteroids, is discussed, together with the translational potential of antioxidant strategies such as polyphenols, vitamins, and Nrf2 pathway activators. At the same time, we address critical challenges limiting clinical application, including insufficient interventional evidence, the lack of validated biomarkers, and uncertainties regarding optimal timing of antioxidant intervention. By providing a comprehensive overview of oxidative stress in RVO, this review aims to identify emerging therapeutic targets and opportunities for personalized treatment approaches, and to outline future research directions toward improving long-term visual outcomes in patients with RVO. Full article

Diabetic retinopathy (DR) is a major complication of both Type 1 and Type 2 diabetes mellitus (T1DM and T2DM). Disease progression can result in visual impairment, primarily due to diabetic macular edema (DME) or proliferative diabetic retinopathy (PDR). Although several ocular treatments are available for DME, a subset of patients fails to respond, reflecting the multifactorial, complex, and systemic nature of DR. Inflammatory biomarkers can be classified according to different characteristics, including imaging biomarkers—most commonly assessed using optical coherence tomography (OCT)—and molecular biomarkers, which are defined by their biochemical and biophysical properties. Pro- and anti-inflammatory cytokines, chemokines, adipokines, and inflammation-related enzymes are recognized as key inflammatory biomarkers and can be detected in the vitreous humour, aqueous humour, tears, serum, and other biological tissues. The identification and characterization of reliable biomarkers may help determine disease severity, monitor disease progression, and predict the risk of specific outcomes, thereby aiding in the prevention of end-stage disease (prognostic biomarkers). In addition, biomarkers may serve as predictive tools for therapeutic response, guiding personalized treatment strategies and enabling ongoing monitoring. This review provides a comprehensive overview of the role of inflammatory biomarkers in the diagnosis and management of DR and DME. Full article

The safe and efficient integration of small unmanned aircraft systems (sUAS) into the National Airspace System (NAS) requires a systems-based understanding of the interrelations among human, technological, and regulatory components. Existing Federal Aviation Administration (FAA) guidelines restrict most operations to visual line of sight (VLOS), which constrains operational scalability and underscores the need for system-level innovations supporting beyond-visual-line-of-sight (BVLOS) operations. This study adopted a socio-technical systems approach to evaluate how first-person view (FPV) technologies influence operator workload and situational awareness (SA), key human performance elements within the broader sUAS safety system. Participants meeting FAA Part 107 eligibility criteria were assigned to one of three visual configurations: (a) traditional VLOS, (b) FPV using a 21-inch monitor, or (c) FPV with immersive goggles. Workload was measured with the NASA Task Load Index (NASA-TLX), and Level 1 SA was assessed via post-task recall. ANOVA results revealed no statistically significant differences across visual conditions, indicating no evidence that FPV integration either increased cognitive load or impaired perceptual awareness compared to traditional methods. Complementary analysis of NASA’s Aviation Safety Reporting System (ASRS) identified SA as the most recurrent human-factor issue, suggesting system-level implications for human–machine interaction and training design. These findings contribute to the systemic understanding of human factors in UAS operations, supporting FPV’s potential as a viable subsystem for achieving safe and effective BVLOS integration within complex socio-technical aviation systems. Full article

Age-related macular degeneration (AMD) is an increasingly prevalent source of permanent visual impairment in the aging population and is widely accepted as a multi-factorial neurodegenerative disorder of the retina. While there has been significant progress in treating neovascular AMD, there are currently no effective disease-sparing treatments for dry AMD and geographic atrophy. To date, research has begun to reveal the complex relationship between the environment and genetic predisposition in AMD pathogenesis. Various environmental factors responsible for AMD include oxidative stress, mitochondrial dysfunction, inflammation, abnormal complement activation, and epigenetic regulation, which interact dynamically to drive disease progression. This review summarizes recent data and provides a comprehensive model for understanding how these interacting factors lead to the progression of AMD from an early stage to advanced stages with complications associated with the disease. We highlight the central role of retinal pigment epithelial mitochondrial failure and impaired stress resilience as upstream drivers that amplify inflammation and complement-mediated injuries. We also discuss how dysregulated miRNAs and proteomic network remodeling contribute to disease heterogeneity. Emerging therapeutic strategies are reviewed in the context of molecular endotyping and personalized intervention. Finally, we outline future directions toward precision medicine in AMD, emphasizing early disease modification, rational combination therapies, and the need to bridge the translational gaps between molecular discovery and clinical trial design. Full article

Background/Objectives: Hydroxychloroquine (HCQ) is widely used in the treatment of autoimmune rheumatologic diseases due to its immunomodulatory and anti-inflammatory properties. However, long-term HCQ therapy carries a risk of irreversible retinal toxicity caused by drug accumulation in the retinal pigment epithelium. The early identification of preclinical retinal changes is essential to prevent permanent visual impairment. Optical coherence tomography (OCT) and OCT-angiography (OCT-A) have emerged as key imaging modalities for the detection of structural and microvascular biomarkers of HCQ retinopathy. A narrative review of the literature was conducted using the PubMed database, focusing on studies published between January 2017 and February 2025. Search terms included “hydroxychloroquine” and “optical coherence tomography.” Eligible studies evaluated HCQ-related retinal toxicity using OCT and/or OCT-A in human subjects. Data were extracted regarding study population characteristics, treatment duration, cumulative HCQ dose, daily dose normalized to real body weight, and reported imaging findings. Results: We identified 223 scientific papers of which 88 studies met the inclusion criteria. Structural OCT parameters—particularly alterations in the ellipsoid zone, outer nuclear layer, and retinal pigment epithelium—were consistently associated with early HCQ toxicity, often preceding functional impairment. OCT-A studies demonstrated microvascular alterations, including reduced vessel density and foveal avascular zone enlargement, though interpretation may be confounded by underlying autoimmune-disease-related vasculopathy. Conclusions: HCQ retinopathy is a potentially vision-threatening condition associated with the cumulative dose, treatment duration, and patient-specific risk factors. OCT and OCT-A provide complementary structural and vascular biomarkers that aid in the detection of subclinical retinal toxicity. The integration of quantitative and automated OCT-derived metrics may improve screening strategies, facilitate early diagnosis, and support personalized care in patients receiving long-term HCQ therapy. Full article

Osteoarthritis (OA) is a progressive musculoskeletal disorder that affects not only older adults but also younger populations, often leading to chronic pain, joint stiffness, functional impairment, and a decline in quality of life. Non-invasive physical rehabilitation plays a critical role in slowing disease progression, alleviating symptoms, and maintaining joint mobility. However, rehabilitation tools such as compression gloves and manual exercise aids are typically passive and provide minimal real-time feedback to patients or clinicians. Others, such as exoskeletons and soft-actuated devices, can be costly or complex to use. This study presents the design and development of an electrically actuated glove integrated with force and flex sensors, intended to assist individuals diagnosed with Stage 2 OA in performing guided finger exercises. The system integrates a digital front-end application that offers real-time feedback and data visualization, enabling more personalized and trackable therapy sessions for both patients and healthcare providers. Preliminary results from an initial human trial with healthy participants demonstrate that the glove enables naturalistic movement without imposing excessive restriction or augmentation of motion. These findings support the glove’s potential in preserving hand coordination and dexterity, key objectives in early-stage OA intervention, and suggest its suitability for integration into home-based or clinical rehabilitation protocols. Full article

Rett syndrome (RTT) is a rare neurodevelopmental disorder that causes severe motor and cognitive impairments, limiting voluntary communication. Gaze-based technologies and virtual reality (VR) offer innovative ways to assess and enhance attention, happiness, and learning in individuals with minimal motor control. This study investigated and compared visual-attentional and emotional engagement in girls with RTT and typically developing (TD) peers during exploration of a virtual forest presented in 2D and immersive 3D (VR) formats across four progressively complex tasks. Twelve girls with RTT and 12 TD peers completed eye-tracking tasks measuring reaction time, fixation duration, disengagement events, and observed happiness. Girls with RTT showed slower responses and more disengagements overall, but VR significantly improved attentional efficiency in both groups, resulting in faster reaction times (η²_p = 0.36), longer fixations (η²_p = 0.31), and fewer disengagements (η²_p = 0.27). These effects were stronger in the RTT group. Both groups also showed greater happiness in VR settings (RTT: p = 0.011; TD: p = 0.015), and in participants with RTT, peaks in attention coincided with peak happiness, indicating a link between happiness and cognitive engagement. Immersive VR thus appears to enhance attention and affect in RTT, supporting its integration into personalized neurorehabilitation. Full article