Search Results (3,860)

Hospitals are complex systems that function most effectively when operations are coordinated and supported by real-time information and feedback loops. Sustained growth, quality improvement, and financial viability increasingly rely on data-based management (DBM), yet adoption and use vary widely across healthcare institutions. This study examined the enabling and hindering factors influencing DBM, with the aim of generating insights to strengthen data use and improve management of eye hospitals. A qualitative multiple case study design was employed in six purposefully selected eye hospitals in India, varying in size and baseline capacity for DBM. At each site, five to six key personnel were interviewed. Data collection involved audio-recorded interviews, transcripts, and field notes, and analysis followed a grounded theory approach using open and axial coding to identify themes, relationships, and develop a conceptual framework. Findings reaffirmed the core enablers—leadership commitment, data availability, and technology adoption. Additional drivers included operational adaptability, regulatory demands, systematic improvement practices, daily reporting, information policies, and the use of communication platforms such as WhatsApp. Key barriers were incomplete data entry, software limitations, inadequate analytical reporting, and inconsistent adherence to processes. Overall, effective DBM requires both foundational enablers and contextual drivers, while addressing barriers to institutionalizing data use and improving outcomes. Full article

Electroencephalography is a widely used method for emotion recognition. However, it requires specialized equipment, leading to high costs. Additionally, attaching devices to the body during such procedures may cause physical and psychological stress to participants. These issues are addressed in this study by focusing on physiological signals that are noninvasive and contact-free, and a generalized method for estimating emotions is developed. Specifically, the facial skin temperature and eye-opening degree of participants captured via infrared thermography and visible cameras are utilized, and emotional states are estimated while Japanese older adults view digital content. Emotional responses while viewing digital content are often subtle and dynamic. Additionally, various emotions occur during such situations, both positive and negative. Fluctuations in facial skin temperature and eye-opening degree reflect activities in the autonomic nervous system. In particular, expressing emotions through facial expressions is difficult for older adults; as such, emotional estimation using such ecological information is required. Our study results demonstrated that focusing on skin temperature changes and eye movements during emotional arousal and non-arousal using bidirectional long short-term memory yields an F1 score of 92.21%. The findings of this study can enhance emotion recognition in digital content, improving user experience and the evaluation of digital content. Full article

Children with attention deficit hyperactivity disorder (ADHD) often exhibit different oculomotor behavior compared to their typically developing peers. Research shows that eye movement patterns can provide important information about attention mechanisms. While eye movements have been examined in various cognitive contexts, this study investigated their role in a task designed to assess their potential as indicators of attention functioning in children with ADHD. Specifically, we assessed tonic attention, attentional focus, and selective attention. Seventy participants aged 9–12 years with DSM-5 ADHD-I and ADHD-C types participated in our research. We then included the results of 57 participants in our study. We used the d2-R attention test and the Reaction alertness test to determine the specifics we were looking for. We used Eye Tracking Glasses (ETG) 2w to capture eye movements. The results show that quiet eye (QE) duration does not reliably predict visuomotor performance in this population. Our findings further suggest that in children with ADHD, the QE phase is not the primary period for acquiring visual information important for movement planning; rather, relevant information is gathered earlier in the process. Conversely, prolonged onset and duration of QE were associated with poorer attentional efficiency, suggesting that in ADHD, longer QE may reflect slower or less efficient cognitive processing rather than increased control. Full article

This study seeks to determine the efficacy of a novel, virtual reality (VR)-based sensorimotor assessment tool, VIST Neuro-ID, in comparison to the gold standard. This was achieved through computing common postural sway metrics, as well as comparing these metrics across population groups including sex and age (50–60 vs. 61–75). Sensorimotor assessments were conducted within the VIST Neuro-ID VR software while participants stood on a force plate. A proxy for center-of-pressure measurement was developed using the six-degree-of-freedom data collected from the head-mounted display used with the VR system. Moderate-to-high (r = 0.542–0.906) Pearson’s correlations were found between VIST Neuro-ID and the force plate for all eight postural sway metrics that were computed. Both systems detected significant differences (p < 0.05) across age groups for all metrics, except for two-dimensional path length from the force plate. Several significant differences were found across sexes, including AP and resultant sway velocity from the force plate, and resultant and AP root-mean-square from the HTC Vive Pro Eye. This indicates potential for VR to be used to collect vital postural sway metrics needed for assessing patient function, while also highlighting potential to identify balance patterns related to aging. Full article

Background: Iron oxide nanoparticles (IONPs) have broad-spectrum antimicrobial activity, with negligible potential for resistance development, excellent biocompatibility, and therefore, could be promising alternatives to conventional antimicrobials. However, their industrial-scale production relies on chemical synthesis that involves toxic reagents, imposing potential environmental hazards. In contrast, green synthesis offers an eco-friendly alternative, but our previous study found that green-synthesized IONPs (IONPs-G) exhibited a lower antibacterial activity and a higher cytotoxicity compared to chemically synthesized counterparts, likely due to nanoparticle aggregation. Objectives: To address this challenge, the current study presents a simple, effective, economic, scalable, and eco-friendly strategy to optimize the physicochemical properties of IONPs-G post-production without requiring extensive modifications to synthesis parameters. Methods: IONPs-G were dispersed in a solvent mixture containing Tween 80 (Tw80). Subsequently, in vitro antimicrobial and in vivo cytotoxicity studies on rabbits’ skin and eye were conducted. Results: The formed nanoparticles’ dispersion (IONPs-GTw80) had a particle size of 9.7 ± 2.1 nm, a polydispersity index of 0.111 ± 0.02, and a zeta potential of −11.4 ± 2.4 mV. MIC of IONPs-GTw80 values against S. aureus and E. coli were reduced by more than ten-fold compared to IONPs-G. MBC was twice MIC, confirming the bactericidal activity of IONPs-GTw80. In vivo studies of IONPs-GTw80 confirmed their biocompatibility with intact/abraded skin and eyes; this was further confirmed by histopathological and biochemical analyses. Conclusions: IONPs-GTw80 might be recommended as a disinfectant in healthcare settings or a topical antimicrobial agent for treatment of infected wounds. Nevertheless, further studies are required for their clinical translation. Full article

Background: Impaired balance is one of the most common and functionally limiting problems in children with cerebral palsy (CP), significantly affecting their motor abilities and quality of life. Although force platforms are considered the gold standard for evaluating postural stability, they are often costly, non-portable, and require specialized laboratory environments, limiting their accessibility in routine clinical settings. Objective: This study aimed to develop a novel software program based on image processing techniques to assess static balance in children with CP and to evaluate its validity against traditional force platform measurements. Methods: A total of 83 children aged 5–15 years (63 with CP, GMFCS levels I–II; 20 healthy controls) participated. Static balance was assessed under four different standing conditions using both a force platform and a newly developed video-based software tool. The software utilized the frame difference method to detect center of mass movements, and parameters such as velocity and total displacement were calculated. Correlation analyses were conducted between the image processing and force platform data. Results: The software demonstrated moderate to strong positive correlations with force platform parameters in the majority of test conditions, particularly when participants stood with eyes open. In more challenging balance scenarios (e.g., eyes closed, feet together), correlations were weaker but still significant. Conclusions: The findings suggest that this image-based software is a valid, low-cost, and portable alternative for static balance assessment in children with CP. It has the potential for use in diverse clinical or home settings, supporting individualized rehabilitation strategies. Full article

This study presents a mathematical model to understand the dynamics of eye vision disability, incorporating key physiological and environmental variables such as visual acuity, lens power, pupil diameter, and environmental influence. The novel model developed in this work consists of four state variables that describe their interactions, aiming to simulate changes in visual acuity and the progression of vision disability under different circumstances. Various mathematical aspects including positivity and equilibrium points along with local and global stability are demonstrated. In addition, the sensitivity analysis is also presented to examine the impact of variations in parameters on the model’s outcomes, highlighting the factors that significantly influence visual acuity and pupil adjustments. Furthermore, the phase portraits explore the dynamic interactions between variables, revealing different insights into the stability of the system and adaptive responses. These results provide a thorough understanding of factors influencing eye vision, offering new insights into vision disability dynamics through an integrated, non-autonomous model and practical applications in developing corrective strategies. Full article

The ciliary marginal zone (CMZ) is a region in the peripheral-most retina that displays ongoing retinogenesis during growth and expansion of the eye in adulthood. While there is evidence that this capacity also exists in birds and mammals, it is far more robust in fish and amphibians. The process of CMZ retinogenesis is essentially equivalent to that seen early in the central retina; however, its regulation is not fully understood. In a previous study, we attempted to uncover novel regulatory genes by using a forward genetics screen in zebrafish, looking for recessive CMZ mutants. One of the mutants found was called no marginal zone (nmz). The nmz mutant showed relatively normal central retina development, but a lack of cells in the CMZ by 5 days post fertilization (dpf). Mapping, genomic sequencing, and complementation analysis using a second mutant line (m863) isolated in another laboratory showed that a mutation in damage-specific DNA binding protein-1 (ddb-1) gene underlies the phenotype seen in nmz. BrdU labeling suggested that later expansion and differentiation of CMZ retinal progenitors is more affected by ddb-1 loss than the earlier process of stem cell asymmetric division. As was seen for the m863 mutant and in other studies with mice, one profound effect of ddb-1 loss in nmz was the upregulation in expression of tp53 and several of its downstream effectors. Several important genes important in CMZ retinogenesis are also downregulated in the nmz mutant. The change in gene expression would suggest that ddb-1 loss leads to increased cell cycle disruption and apoptosis at the expense of CMZ retinogenesis. While homozygosity is lethal, heterozygous fish appear to be completely normal in morphology, visual function, and behavior. Full article

Background/Objectives: Glaucoma is a multifactorial eye disease that can cause optic nerve damage and irreversible blindness. It is considered a significant public health problem worldwide. Topical intraocular pressure (IOP)-lowering eye preparations are used to prevent or slow further damage. Previously, we demonstrated that nimodipine (NMD), a calcium channel blocker, significantly reduced IOP after a single drop of NMD/HPMC suspension. The current study was designed to develop NMD chitosan nanoparticles (NMD-CS NPs) to improve the NMD IOP-lowering efficacy. Methods: NMD-CS NPs were prepared using the spontaneous-emulsification solvent diffusion method. Three different types of chitosan, carboxymethyl CS (CMCS), low molecular weight CS (LCS), and medium molecular weight CS (MCS), were used. Different concentrations of polymers, various stabilizers, and two pHs were used for formulation optimization. NMD-CS NPs were characterized regarding their particle size, polydispersity index (PDI), zeta potential, DSC, FTIR, and encapsulation efficiency. NMD-CS NPs were incorporated into eye drops and characterized in terms of their in vitro release, cytotoxicity, transcorneal permeability, and in vivo efficacy. Results: The optimized NMD-CS NPs demonstrate a small particle size with a narrow size distribution and acceptable zeta potential values. DSC and FTIR results confirmed the complete entrapment of NMD inside the NPs. NMD-CS NP eye drops successfully sustained NMD release without any burst effect. These NPs demonstrated a Higuchi non-Fickian diffusion mechanism and 79.41% improved corneal permeability. Cytotoxicity studies revealed that NMD formulations are nontoxic. After a single topical ocular application, NMD-MCS NP eye drops induced a significantly superior effect to Timolol maleate eye drops with regard to the %IOP reduction and duration of action. Conclusions: Evaluation results of NMD-CS NP eye drops show their positive effect in a preclinical animal model as a promising glaucoma therapy. Full article

This feasibility study explored the integration of physiological monitoring into a virtual reality (VR) intervention for pediatric pain management. The goal of this study is to identify a feasible strategy for collecting physiologic data in the context of a VR intervention currently being developed for youth with chronic pain. We assess the potential of Cognitive Load (CL)—derived from heart rate and pupillometry/eye-tracking data—as a marker of arousal and user engagement in a VR simulation to promote school functioning in youth with chronic pain. The HP Reverb G2 Omnicept headset and Polar H10 heart-rate sensor were utilized. The Child Presence Questionnaire (CPQ) assessed participants’ self-reported immersion and engagement. Data collection focused on feasibility and utility of physiologic data in assessing arousal and correlations with self-reported experience. Nine participants engaged in the simulation, with eight yielding complete data. The simulation and headset were well tolerated. CPQ Transportation subscale showed trend-level correlation with mean CL. Due to small sample and feasibility focus, individual-level results were examined. Combining multiple physiologic markers into a construct like CL is intriguing, but data interpretability was limited. Pupillometry and related metrics show promise as feasible markers of engagement and arousal for VR-based intervention but require appropriate expertise to fully interpret. The study found that integration of physiologic monitoring is feasible, but further work is needed to standardize metrics and identify the most useful and user-friendly markers. Full article

Natural elements such as vegetation, water bodies, and sky, together with artificial elements including buildings and paved surfaces, constitute the core of urban visual environments. Their perception at the pedestrian level not only influences city image but also contributes to residents’ well-being and spatial experience. This study develops a hybrid 3D visibility assessment framework that integrates a city-scale LOD1 solid model with high-resolution mobile LiDAR point clouds to quantify five visual exposure indicators. The case study area is Yueya Lake Park in Nanjing, where a voxel-based line-of-sight sampling approach simulated eye-level visibility at 1.6 m along the southern lakeside promenade. Sixteen viewpoints were selected at 50 m intervals to capture spatial variations in visual exposure. Comparative analysis between the solid model (excluding vegetation) and the hybrid model (including vegetation) revealed that vegetation significantly reshaped the pedestrian visual field by reducing the dominance of sky and buildings, enhancing near-field greenery, and reframing water views. Artificial elements such as buildings and ground showed decreased exposure in the hybrid model, reflecting vegetation’s masking effect. The calculation efficiency remains a limitation in this study. Overall, the study demonstrates that integrating natural and artificial elements provides a more realistic and nuanced assessment of pedestrian visual perception, offering valuable support for sustainable landscape planning, canopy management, and the equitable design of urban public spaces. Full article

Background: Acquired ptosis is a common eyelid disorder in elderly patients, causing visual disturbance and cosmetic concerns. Accurate evaluation of periocular anatomy, including eyebrow and iris position, is essential for surgical planning, but current manual assessments are time-consuming and subjective. Objectives: This study aimed to develop deep-learning models for iris and eyebrow segmentation to automate eye landmark measurements and enable objective, standardized analysis in patients with acquired ptosis. Methods: We retrospectively collected 612 facial images from 209 ptosis patients. Images were labeled for iris and eyebrow segmentation and split into training, validation, and test sets (8:1:1). A deep-learning model was developed to automatically segment the iris and eyebrow regions and automatically measure seven landmarks: MRD1, MRD2, medial eyebrow end, medial limbus, pupil center, lateral limbus, and lateral eyebrow end. Results: The iris segmentation model achieved accuracy of 99.7%, precision of 97.6%, recall of 98.3%, an F1 score of 97.9%, and intersection over union of 95.9%. The corresponding metrics for the eyebrow segmentation model were 98.6%, 92.6%, 91.5%, 91.5%, and 85.0%. The mean absolute percentage error and root mean square error for the automated landmark measurements were 4.00% and 2.48 mm, respectively. Conclusions: The high performance of the segmentation models and the automated measurements supports their potential use for objective and standardized analyses of acquired ptosis. These findings may aid the future development of predictive tools for use in surgical planning. Full article

Objectives: To develop a proof-of-concept machine learning (ML) neural network model to predict post-operative visual outcomes in children with congenital cataracts undergoing intraocular lens (IOL) implantation, thereby guiding the optimal timing for IOL insertion. Determining the ideal timing and predicting outcomes for IOL implantation in children remains clinically complex due to variability in eye development and measurement accuracy. Methods: Retrospective analysis using a publicly available dataset from 110 children diagnosed with congenital cataracts, who underwent IOL implantation at the Eye and ENT Hospital of Fudan University. A neural network model with a hidden layer of 10 nodes was developed in MATLAB 2024a using the scaled conjugate gradient algorithm. Input variables included demographic and clinical features; the target was achieving visual acuity greater than 20/40. Performance metrics were evaluated using cross-entropy loss, sensitivity, specificity, and accuracy. Results: Training completed after 14 epochs with the test set reaching the highest performance metrics: 88.2% accuracy, 88.9% sensitivity, and 87.5% specificity. ROC curve analysis showed AUC values of 0.942 (training), 0.920 (validation), 0.885 (test), and 0.917 (overall). Conclusions: The neural network effectively predicted post-operative visual outcomes, offering potential clinical utility in guiding IOL implantation decisions. Despite limitations in dataset diversity, this study lays the foundation for future development of personalized strategies in pediatric cataract care. Full article

The development of high-performance MEMS-based eye trackers, crucial for next-generation medical diagnostics and human–computer interfaces, is often hampered by the mechanical instability and time-consuming recalibration of physical prototypes. To address this bottleneck, we present the development and rigorous validation of a high-fidelity digital twin (DT) designed to accelerate the design–test–refine cycle. We conducted a comparative study of a physical MEMS scanning system and its corresponding digital twin using a USAF 1951 test target under both static and dynamic conditions. Our analysis reveals that the DT accurately replicates the physical system’s behavior, showing a geometric discrepancy of <30 µm and a matching feature shift (1 µm error) caused by tracking dynamics. Crucially, the DT effectively removes mechanical vibration artifacts, enabling the precise analysis of system parameters in a controlled virtual environment. The validated model was then used to develop a pupil detection algorithm that achieved an accuracy of 1.80 arc minutes, a result that surpasses the performance of a widely used commercial system in our comparative tests. This work establishes a validated methodology for using digital twins in the rapid prototyping and optimization of complex optical systems, paving the way for faster development of critical healthcare technologies. Full article

Climate change and the El Niño Southern Oscillation (ENSO) events have been increasingly linked to infectious disease outbreaks. While growing evidence has connected climate variability with systemic illnesses, the ocular implications remain underexplored. This study aimed to assess the relationships between ENSO-driven climate events and infectious diseases with ophthalmic consequences. A narrative review of 255 articles was conducted, focusing on infectious diseases influenced by ENSO and their associated ocular findings. 39 articles met criteria for full review, covering diseases such as dengue, zika, chikungunya, malaria, leishmaniasis, leptospirosis, and Rift Valley fever. Warmer temperatures, increased rainfall, and humidity associated with ENSO events were found to enhance vector activity and disease transmission. Ocular complications included uveitis, retinopathy, and optic neuropathy, but the specific disease findings varied by infectious disease syndrome. The climactic variable changes in response to ENSO events differed across diseases and regions and were influenced by geography, local infrastructure, and socioeconomic factors. ENSO event-related climate shifts significantly impact the spread of infectious diseases with ocular symptoms. These findings highlight the need for region-specific surveillance and predictive models that may provide insight related to the risk of ophthalmic disease during ENSO events. Further research is needed to clarify long-term ENSO effects and develop integrated strategies for systemic and eye disease detection, prevention, and management. Full article